This paper investigates the attitude tracking control problem for the cruise mode of a dual-system convertible unmanned aerial vehicle(UAV)in the presence of parameter uncertainties,unmodeled uncertainties and wind di...This paper investigates the attitude tracking control problem for the cruise mode of a dual-system convertible unmanned aerial vehicle(UAV)in the presence of parameter uncertainties,unmodeled uncertainties and wind disturbances.First,a fixed-time disturbance observer(FXDO)based on the bi-limit homogeneity theory is designed to estimate the lumped disturbance of the convertible UAV model.Then,a fixed-time integral sliding mode control(FXISMC)is combined with the FXDO to achieve strong robustness and chattering reduction.Bi-limit homogeneity theory and Lyapunov theory are applied to provide detailed proof of the fixed-time stability.Finally,numerical simulation experimental results verify the robustness of the proposed algorithm to model parameter uncertainties and wind disturbances.In addition,the proposed algorithm is deployed in a open-source UAV autopilot and its effectiveness is further demonstrated by hardware-in-the-loop experimental results.展开更多
Hydraulic actuators are highly nonlinear when they are subjected to different types of model uncertainties and dynamic disturbances.These unfavorable factors adversely affect the control performance of the hydraulic a...Hydraulic actuators are highly nonlinear when they are subjected to different types of model uncertainties and dynamic disturbances.These unfavorable factors adversely affect the control performance of the hydraulic actuator.Although various control methods have been employed to improve the tracking precision of the dynamic system,optimizing and adjusting control gain to mitigate the hydraulic actuator model uncertainties remains elusive.This study presents an adaptive back-stepping sliding mode controller(ABSMC)to enhance the trajectory tracking precision,where the virtual control law is constructed to replace the position error.The adaptive control theory is introduced in back-stepping controller design to compensate for the model uncertainties and time-varying disturbances.Based on Lyapunov theory,the finite-time convergence of the position tracking errors is proved.Furthermore,the effectiveness of the developed control scheme is conducted via extensive comparative experiments.展开更多
Parking difficulties have become a social issue that people have to solve.Automated parking system is practicable for quick par operations without a driver which can also greatly reduces the probability of parking acc...Parking difficulties have become a social issue that people have to solve.Automated parking system is practicable for quick par operations without a driver which can also greatly reduces the probability of parking accidents.The paper proposes a Lyapunov-based nonlinear model predictive controller embedding an instructable solution which is generated by the modified rear-wheel feedback method(RF-LNMPC)in order to improve the overall path tracking accuracy in parking conditions.Firstly,A discrete-time RF-LNMPC considering the position and attitude of the parking vehicle is proposed to increase the success rate of automated parking effectively.Secondly,the RF-LNMPC problem with a multi-objective cost function is solved by the Interior-Point Optimization,of which the iterative initial values are described as the instructable solutions calculated by combining modified rear-wheel feedback to improve the performance of local optimal solution.Thirdly,the details on the computation of the terminal constraint and terminal cost for the linear time-varying case is presented.The closed-loop stability is verified via Lyapunov techniques by considering the terminal constraint and terminal cost theoretically.Finally,the proposed RF-LNMPC is implemented on a selfdriving Lincoln MKZ platform and the experiment results have shown improved performance in parallel and vertical parking conditions.The Monte Carlo analysis also demonstrates good stability and repeatability of the proposed method which can be applied in practical use in the near future.展开更多
Automatic voltage regulators(AVR)are designed to manipulate a synchronous generator’s voltage level automatically.Proportional integral derivative(PID)controllers are typically used in AVR systems to regulate voltage...Automatic voltage regulators(AVR)are designed to manipulate a synchronous generator’s voltage level automatically.Proportional integral derivative(PID)controllers are typically used in AVR systems to regulate voltage.Although advanced PID tuning methods have been proposed,the actual voltage response differs from the theoretical predictions due to modeling errors and system uncertainties.This requires continuous fine tuning of the PID parameters.However,manual adjustment of these parameters can compromise the stability and robustness of the AVR system.This study focuses on the online self-tuning of PID controllers called indirect design approach-2(IDA-2)in AVR systems while preserving robustness.In particular,we indirectly tune the PID controller by shifting the frequency response.The new PID parameters depend on the frequency-shifting constant and the previously optimized PID parameters.Adjusting the frequency-shifting constant modifies all the PID parameters simultaneously,thereby improving the control performance and robustness.We evaluate the robustness of the proposed online PID tuning method by comparing the gain margins(GMs)and phase margins(PMs)with previously optimized PID parameters during parameter uncertainties.The proposed method is further evaluated in terms of disturbance rejection,measurement noise,and frequency response analysis during parameter uncertainty calculations against existing methods.Simulations show that the proposed method significantly improves the robustness of the controller in the AVR system.In summary,online self-tuning enables automated PID parameter adjustment in an AVR system,while maintaining stability and robustness.展开更多
This paper,evaluate the effectiveness of a proposed speed loop pseudo derivative feedforward(PDFF)controller-based direct torque controller(DTC)for a PMSM drive against the performance of existing PI speed controller-...This paper,evaluate the effectiveness of a proposed speed loop pseudo derivative feedforward(PDFF)controller-based direct torque controller(DTC)for a PMSM drive against the performance of existing PI speed controller-based DTC and hysteresis current controller(HCC).The proposed PDFF-based speed regulator effectively reduces oscillation and overshoot associated with rotor angular speed,electromagnetic torque,and stator current.Two case studies,one using forward-to-reverse motoring operation and the other involving reverse-to-forward braking operation,has been validated to show the effectiveness of the proposed control strategy.The proposed controller's superior performance is demonstrated through experimental verification utilizing an FPGA controller for a 1.5 kW PMSM drive laboratory prototype.展开更多
The controller is a main component in the Software-Defined Networking(SDN)framework,which plays a significant role in enabling programmability and orchestration for 5G and next-generation networks.In SDN,frequent comm...The controller is a main component in the Software-Defined Networking(SDN)framework,which plays a significant role in enabling programmability and orchestration for 5G and next-generation networks.In SDN,frequent communication occurs between network switches and the controller,which manages and directs traffic flows.If the controller is not strategically placed within the network,this communication can experience increased delays,negatively affecting network performance.Specifically,an improperly placed controller can lead to higher end-to-end(E2E)delay,as switches must traverse more hops or encounter greater propagation delays when communicating with the controller.This paper introduces a novel approach using Deep Q-Learning(DQL)to dynamically place controllers in Software-Defined Internet of Things(SD-IoT)environments,with the goal of minimizing E2E delay between switches and controllers.E2E delay,a crucial metric for network performance,is influenced by two key factors:hop count,which measures the number of network nodes data must traverse,and propagation delay,which accounts for the physical distance between nodes.Our approach models the controller placement problem as a Markov Decision Process(MDP).In this model,the network configuration at any given time is represented as a“state,”while“actions”correspond to potential decisions regarding the placement of controllers or the reassignment of switches to controllers.Using a Deep Q-Network(DQN)to approximate the Q-function,the system learns the optimal controller placement by maximizing the cumulative reward,which is defined as the negative of the E2E delay.Essentially,the lower the delay,the higher the reward the system receives,enabling it to continuously improve its controller placement strategy.The experimental results show that our DQL-based method significantly reduces E2E delay when compared to traditional benchmark placement strategies.By dynamically learning from the network’s real-time conditions,the proposed method ensures that controller placement remains efficient and responsive,reducing communication delays and enhancing overall network performance.展开更多
The pressure-preserving controller is the core part of deep in-situ pressure-preserving coring(IPP-Coring) system, and its pressure-preserving capability is the key to IPP-Coring technology. To achieve a good understa...The pressure-preserving controller is the core part of deep in-situ pressure-preserving coring(IPP-Coring) system, and its pressure-preserving capability is the key to IPP-Coring technology. To achieve a good understanding of the influence of mechanical properties of materials on the ultimate pressure-bearing capability(UPB-Capability) of the pressure-preserving controller, the IPP-Coring experimental platform was developed to test the UPB-Capability of pressure-preserving controllers of four different materials. The experimental results show that the UPB-Capability of pressure-preserving controllers with different material varies greatly. A numerical model of the pressure-preserving controller was developed to study the influences of mechanical parameters of materials on the UPB-Capability of the pressurepreserving controller after the accuracy of the numerical model is verified by experiments. The results indicate that the yield strength(YS) and Poisson's ratio(PR) of the material have little effect on the UPB-Capability of the pressure-preserving controller, whereas the elastic modulus(EM) of the material has a significant effect. A generalized model of the UPB-Capability of the pressure-preserving controller is developed to reveal the mechanism of the influence of material properties on the UPB-Capability of the pressure-preserving controllers. Considering these results, the future optimization direction of the pressure-preserving controller and material selection scheme in practical engineering applications of the pressure-preserving controller are suggested.展开更多
Software-Defined Networking(SDN)improves network management by separating its control logic from the underlying hardware and integrating it into a logically centralized control unit,termed the SDN controller.SDN adapt...Software-Defined Networking(SDN)improves network management by separating its control logic from the underlying hardware and integrating it into a logically centralized control unit,termed the SDN controller.SDN adaptation is essential for wireless networks because it offers enhanced and data-intensive services.The initial intent of the SDN design was to have a physically centralized controller.However,network experts have suggested logically centralized and physically distributed designs for SDN controllers,owing to issues such as a single point of failure and scalability.This study addressed the security,scalability,reliability,and consistency issues associated with the design of distributed SDN controllers.Moreover,the security issues of an enterprise related to multiple physically distributed controllers in a software-defined wireless local area network(SD-WLAN)were emphasized,and optimal solutions were suggested.展开更多
This paper proposes an adaptive nonlinear proportional-derivative(ANPD)controller for a two-wheeled self-balancing robot(TWSB)modeled by the Lagrange equation with external forces.The proposed control scheme is design...This paper proposes an adaptive nonlinear proportional-derivative(ANPD)controller for a two-wheeled self-balancing robot(TWSB)modeled by the Lagrange equation with external forces.The proposed control scheme is designed based on the combination of a nonlinear proportional-derivative(NPD)controller and a genetic algorithm,in which the proportional-derivative(PD)parameters are updated online based on the tracking error and the preset error threshold.In addition,the genetic algorithm is employed to adaptively select initial controller parameters,contributing to system stability and improved control accuracy.The proposed controller is basic in design yet simple to implement.The ANPD controller has the advantage of being computationally lightweight and providing high robustness against external forces.The stability of the closed-loop system is rigorously analyzed and verified using Lyapunov theory,providing theoretical assurance of its robustness.Simulations and experimental results show that the TWSB robot with the proposed ANPD controller achieves quick balance and tracks target values with very small errors,demonstrating the effectiveness and performance of the proposed controller.The proposed ANPD controller demonstrates significant improvements in balancing and tracking performance for two-wheeled self-balancing robots,which has great applicability in the field of robot control systems.This represents a promising solution for applications requiring precise and stable motion control under varying external conditions.展开更多
Detumbling operation toward a rotating target with nutation is meaningful for debris removal but challenging. In this study, a deformable end-effector is first designed based on the requirements for contacting the nut...Detumbling operation toward a rotating target with nutation is meaningful for debris removal but challenging. In this study, a deformable end-effector is first designed based on the requirements for contacting the nutating target. A dual-arm robotic system installed with the deformable end-effectors is modeled and the movement of the end-tips is analyzed. The complex operation of the contact toward a nutating target places strict requirements on control accuracy and controller robustness. Thus, an improvement of the tracking error transformation is proposed and an adaptive sliding mode controller with prescribed performance is designed to guarantee the fast and precise motion of the effector during the contact detumbling.Finally, by employing the proposed effector and the controller,numerical simulations are carried out to verify the effectiveness and efficiency of the contact detumbling toward a nutating target.展开更多
Linear temporal logic(LTL)is an intuitive and expressive language to specify complex control tasks,and how to design an efficient control strategy for LTL specification is still a challenge.In this paper,we implement ...Linear temporal logic(LTL)is an intuitive and expressive language to specify complex control tasks,and how to design an efficient control strategy for LTL specification is still a challenge.In this paper,we implement the dynamic quantization technique to propose a novel hierarchical control strategy for nonlinear control systems under LTL specifications.Based on the regions of interest involved in the LTL formula,an accepting path is derived first to provide a high-level solution for the controller synthesis problem.Second,we develop a dynamic quantization based approach to verify the realization of the accepting path.The realization verification results in the necessity of the controller design and a sequence of quantization regions for the controller design.Third,the techniques of dynamic quantization and abstraction-based control are combined together to establish the local-to-global control strategy.Both abstraction construction and controller design are local and dynamic,thereby resulting in the potential reduction of the computational complexity.Since each quantization region can be considered locally and individually,the proposed hierarchical mechanism is more efficient and can solve much larger problems than many existing methods.Finally,the proposed control strategy is illustrated via two examples from the path planning and tracking problems of mobile robots.展开更多
This study presents a tracking and fault-tolerant controller architecture for uncertain steer-by-wire(SbW)systems using model predictive control in the presence of actuator malfunction and the nonlinear properties of ...This study presents a tracking and fault-tolerant controller architecture for uncertain steer-by-wire(SbW)systems using model predictive control in the presence of actuator malfunction and the nonlinear properties of tire lateral stiffness coefficients.By changing the internal model,the model predictive control(MPC)technique was used to achieve optimal tracking performance under the actuator output limitation variation problem and uncertain system parameters.System parameters and state estimates were simultaneously provided by the fault detection and isolation modules to detect actuator failure using the coupling estimation approach.The estimation accuracy was further improved by considering the replacement errors as virtual noise,which was also estimated during the estimation process.Simulation and experimental results demonstrate that the proposed fault-tolerant control technique can identify motor faults and conduct fault-tolerant control based on fault identification,showing good front-wheel steering angle tracking performance under both normal and fault conditions.展开更多
The primary factor contributing to frequency instability in microgrids is the inherent intermittency of renewable energy sources.This paper introduces novel dual-backup controllers utilizing advanced fractional order ...The primary factor contributing to frequency instability in microgrids is the inherent intermittency of renewable energy sources.This paper introduces novel dual-backup controllers utilizing advanced fractional order proportional integral derivative(FOPID)controllers to enhance frequency and tie-line power stability in microgrids amid increasing renewable energy integration.To improve load frequency control,the proposed controllers are applied to a two-area interconnectedmicrogrid system incorporating diverse energy sources,such as wind turbines,photovoltaic cells,diesel generators,and various storage technologies.A novelmeta-heuristic algorithm is adopted to select the optimal parameters of the proposed controllers.The efficacy of the advanced FOPID controllers is demonstrated through comparative analyses against traditional proportional integral derivative(PID)and FOPID controllers,showcasing superior performance inmanaging systemfluctuations.The optimization algorithm is also evaluated against other artificial intelligent methods for parameter optimization,affirming the proposed solution’s efficiency.The robustness of the intelligent controllers against system uncertainties is further validated under extensive power disturbances,proving their capability to maintain grid stability.The dual-controller configuration ensures redundancy,allowing them to operate as mutual backups,enhancing system reliability.This research underlines the importance of sophisticated control strategies for future-proofing microgrid operations against the backdrop of evolving energy landscapes.展开更多
An autonomous microgrid that runs on renewable energy sources is presented in this article.It has a supercon-ducting magnetic energy storage(SMES)device,wind energy-producing devices,and an energy storage battery.Howe...An autonomous microgrid that runs on renewable energy sources is presented in this article.It has a supercon-ducting magnetic energy storage(SMES)device,wind energy-producing devices,and an energy storage battery.However,because such microgrids are nonlinear and the energy they create varies with time,controlling and managing the energy inside them is a difficult issue.Fractional-order proportional integral(FOPI)controller is recommended for the current research to enhance a standalone microgrid’s energy management and performance.The suggested dedicated control for the SMES comprises two loops:the outer loop,which uses the FOPI to regulate the DC-link voltage,and the inner loop,responsible for regulating the SMES current,is constructed using the intelligent FOPI(iFOPI).The FOPI+iFOPI parameters are best developed using the dandelion optimizer(DO)approach to achieve the optimum performance.The suggested FOPI+iFOPI controller’s performance is contrasted with a conventional PI controller for variations in wind speed and microgrid load.The optimal FOPI+iFOPI controller manages the voltage and frequency of the load.The behavior of the microgrid as a reaction to step changes in load and wind speed was measured using the proposed controller.MATLAB simulations were used to evaluate the recommended system’s performance.The results of the simulations showed that throughout all interruptions,the recommended microgrid provided the load with AC power with a constant amplitude and frequency.In addition,the required load demand was accurately reduced.Furthermore,the microgrid functioned incredibly well despite SMES and varying wind speeds.Results obtained under identical conditions were compared with and without the best FOPI+iFOPI controller.When utilizing the optimal FOPI+iFOPI controller with SMES,it was found that the microgrid performed better than the microgrid without SMES.展开更多
In many Eastern and Western countries,falling birth rates have led to the gradual aging of society.Older adults are often left alone at home or live in a long-term care center,which results in them being susceptible t...In many Eastern and Western countries,falling birth rates have led to the gradual aging of society.Older adults are often left alone at home or live in a long-term care center,which results in them being susceptible to unsafe events(such as falls)that can have disastrous consequences.However,automatically detecting falls fromvideo data is challenging,and automatic fall detection methods usually require large volumes of training data,which can be difficult to acquire.To address this problem,video kinematic data can be used as training data,thereby avoiding the requirement of creating a large fall data set.This study integrated an improved particle swarm optimization method into a double interactively recurrent fuzzy cerebellar model articulation controller model to develop a costeffective and accurate fall detection system.First,it obtained an optical flow(OF)trajectory diagram from image sequences by using the OF method,and it solved problems related to focal length and object offset by employing the discrete Fourier transform(DFT)algorithm.Second,this study developed the D-IRFCMAC model,which combines spatial and temporal(recurrent)information.Third,it designed an IPSO(Improved Particle Swarm Optimization)algorithm that effectively strengthens the exploratory capabilities of the proposed D-IRFCMAC(Double-Interactively Recurrent Fuzzy Cerebellar Model Articulation Controller)model in the global search space.The proposed approach outperforms existing state-of-the-art methods in terms of action recognition accuracy on the UR-Fall,UP-Fall,and PRECIS HAR data sets.The UCF11 dataset had an average accuracy of 93.13%,whereas the UCF101 dataset had an average accuracy of 92.19%.The UR-Fall dataset had an accuracy of 100%,the UP-Fall dataset had an accuracy of 99.25%,and the PRECIS HAR dataset had an accuracy of 99.07%.展开更多
Grid-tie voltage source converters(VSCs)can operate in three distinct modes:AC-dominant,DC-dominant,and balanced,depending on the placement of the stiff voltage sources.The distinct operation modes of the VSCs traditi...Grid-tie voltage source converters(VSCs)can operate in three distinct modes:AC-dominant,DC-dominant,and balanced,depending on the placement of the stiff voltage sources.The distinct operation modes of the VSCs traditionally demand different synchronization control techniques,leading to heterogeneous VSCs.It is challenging for the power system to accommodate and coordinate heterogeneous VSCs.A promising universal synchronization control technique for VSCs is the DC-link voltage synchronization control(DVSC)based on a lead compensator(LC).The LC DVSC stabilizes both the DC and AC voltages of a VSC while achieving synchronization with the AC grid.This results in a dual-port grid-forming(DGFM)characteristic for the VSC.However,there has been very limited study on the stability and synchronization controller design of the VSCs with the LC DVSC operating in various modes.To bridge this gap,the paper presents a quantitative analysis on the stability and steady-state performance of the LC DVSC in all three operation modes of the DGFM VSC.Based on the analysis,the paper provides step-by-step design guidelines for the LC DVSC.Furthermore,the paper uncovers an instability issue related to the LC DVSC when the DGFM VSC operates in the balanced mode.To tackle the instability issue,a virtual resistance control is proposed and integrated with the LC DVSC.Simulation results validate the analysis and demonstrate the effectiveness of the DGFM VSC with the LC DVSC designed using the proposed guidelines in all three operation modes.Overall,the paper demonstrates the feasibility of employing the DGFM VSC with the LC DVSC for all three possible operation modes,which can help overcome the challenges associated with accommodating and coordinating heterogeneous VSCs in the power system.展开更多
This paper addresses the problems faced in programmable logic controller(PLC)teaching in vocational colleges and proposes countermeasures to overcome these challenges.The study emphasizes the need for a deeper underst...This paper addresses the problems faced in programmable logic controller(PLC)teaching in vocational colleges and proposes countermeasures to overcome these challenges.The study emphasizes the need for a deeper understanding of fundamental concepts and the integration of practical application in PLC education.It suggests involving students in teacher-led projects to enhance their programming skills and problem-solving skills.Additionally,the paper highlights the importance of interactive learning and collaborative discussions to foster student engagement.Furthermore,it emphasizes the cultivation of innovation consciousness through participation in innovation competitions and projects.The implementation of these strategies has shown positive results in improving learning outcomes and preparing students for careers in automation and control.This research contributes to the development of effective teaching approaches in PLC education in vocational colleges.展开更多
基金supported by National Natural Science Foundation of China (Grant Nos.52072309 and 62303379)Beijing Institute of Spacecraft System Engineering Research Project (Grant NO.JSZL2020203B004)+1 种基金Natural Science Foundation of Shaanxi Province,Chinese (Grant NOs.2023-JC-QN-0003 and 2023-JC-QN-0665)Industry-University-Research Innovation Fund of Ministry of Education for Chinese Universities (Grant NO.2022IT189)。
文摘This paper investigates the attitude tracking control problem for the cruise mode of a dual-system convertible unmanned aerial vehicle(UAV)in the presence of parameter uncertainties,unmodeled uncertainties and wind disturbances.First,a fixed-time disturbance observer(FXDO)based on the bi-limit homogeneity theory is designed to estimate the lumped disturbance of the convertible UAV model.Then,a fixed-time integral sliding mode control(FXISMC)is combined with the FXDO to achieve strong robustness and chattering reduction.Bi-limit homogeneity theory and Lyapunov theory are applied to provide detailed proof of the fixed-time stability.Finally,numerical simulation experimental results verify the robustness of the proposed algorithm to model parameter uncertainties and wind disturbances.In addition,the proposed algorithm is deployed in a open-source UAV autopilot and its effectiveness is further demonstrated by hardware-in-the-loop experimental results.
基金supported by the fund of Henan Key Laboratory of Superhard Abrasives and Grinding Equipment,Henan University of Technology(Grant No.JDKFJJ2023005)the Key Science and Technology Program of Henan Province(Grant Nos.242102221001 and 232102220085)the Science and Technology Key Project Foundation of Henan Provincial Education Department(Grant No.23A460014).
文摘Hydraulic actuators are highly nonlinear when they are subjected to different types of model uncertainties and dynamic disturbances.These unfavorable factors adversely affect the control performance of the hydraulic actuator.Although various control methods have been employed to improve the tracking precision of the dynamic system,optimizing and adjusting control gain to mitigate the hydraulic actuator model uncertainties remains elusive.This study presents an adaptive back-stepping sliding mode controller(ABSMC)to enhance the trajectory tracking precision,where the virtual control law is constructed to replace the position error.The adaptive control theory is introduced in back-stepping controller design to compensate for the model uncertainties and time-varying disturbances.Based on Lyapunov theory,the finite-time convergence of the position tracking errors is proved.Furthermore,the effectiveness of the developed control scheme is conducted via extensive comparative experiments.
基金Supported by National Key R&D Program of China (Grant No.2021YFB2501800)National Natural Science Foundation of China (Grant No.52172384)+1 种基金Science and Technology Innovation Program of Hunan Province of China (Grant No.2021RC3048)State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle of China (Grant No.72275004)。
文摘Parking difficulties have become a social issue that people have to solve.Automated parking system is practicable for quick par operations without a driver which can also greatly reduces the probability of parking accidents.The paper proposes a Lyapunov-based nonlinear model predictive controller embedding an instructable solution which is generated by the modified rear-wheel feedback method(RF-LNMPC)in order to improve the overall path tracking accuracy in parking conditions.Firstly,A discrete-time RF-LNMPC considering the position and attitude of the parking vehicle is proposed to increase the success rate of automated parking effectively.Secondly,the RF-LNMPC problem with a multi-objective cost function is solved by the Interior-Point Optimization,of which the iterative initial values are described as the instructable solutions calculated by combining modified rear-wheel feedback to improve the performance of local optimal solution.Thirdly,the details on the computation of the terminal constraint and terminal cost for the linear time-varying case is presented.The closed-loop stability is verified via Lyapunov techniques by considering the terminal constraint and terminal cost theoretically.Finally,the proposed RF-LNMPC is implemented on a selfdriving Lincoln MKZ platform and the experiment results have shown improved performance in parallel and vertical parking conditions.The Monte Carlo analysis also demonstrates good stability and repeatability of the proposed method which can be applied in practical use in the near future.
基金the Malaysian Ministry of Higher Education(MOHE)for their support through the Fundamental Research Grant Scheme(FRGS/1/2021/ICT02/UMP/03/3)(UMPSA Reference:RDU 210117)。
文摘Automatic voltage regulators(AVR)are designed to manipulate a synchronous generator’s voltage level automatically.Proportional integral derivative(PID)controllers are typically used in AVR systems to regulate voltage.Although advanced PID tuning methods have been proposed,the actual voltage response differs from the theoretical predictions due to modeling errors and system uncertainties.This requires continuous fine tuning of the PID parameters.However,manual adjustment of these parameters can compromise the stability and robustness of the AVR system.This study focuses on the online self-tuning of PID controllers called indirect design approach-2(IDA-2)in AVR systems while preserving robustness.In particular,we indirectly tune the PID controller by shifting the frequency response.The new PID parameters depend on the frequency-shifting constant and the previously optimized PID parameters.Adjusting the frequency-shifting constant modifies all the PID parameters simultaneously,thereby improving the control performance and robustness.We evaluate the robustness of the proposed online PID tuning method by comparing the gain margins(GMs)and phase margins(PMs)with previously optimized PID parameters during parameter uncertainties.The proposed method is further evaluated in terms of disturbance rejection,measurement noise,and frequency response analysis during parameter uncertainty calculations against existing methods.Simulations show that the proposed method significantly improves the robustness of the controller in the AVR system.In summary,online self-tuning enables automated PID parameter adjustment in an AVR system,while maintaining stability and robustness.
基金supported by Prince Sultan University,Riyadh,Saudi Arabia,under research grant SEED-2022-CE-95。
文摘This paper,evaluate the effectiveness of a proposed speed loop pseudo derivative feedforward(PDFF)controller-based direct torque controller(DTC)for a PMSM drive against the performance of existing PI speed controller-based DTC and hysteresis current controller(HCC).The proposed PDFF-based speed regulator effectively reduces oscillation and overshoot associated with rotor angular speed,electromagnetic torque,and stator current.Two case studies,one using forward-to-reverse motoring operation and the other involving reverse-to-forward braking operation,has been validated to show the effectiveness of the proposed control strategy.The proposed controller's superior performance is demonstrated through experimental verification utilizing an FPGA controller for a 1.5 kW PMSM drive laboratory prototype.
基金supported by the Researcher Supporting Project number(RSPD2024R582),King Saud University,Riyadh,Saudi Arabia.
文摘The controller is a main component in the Software-Defined Networking(SDN)framework,which plays a significant role in enabling programmability and orchestration for 5G and next-generation networks.In SDN,frequent communication occurs between network switches and the controller,which manages and directs traffic flows.If the controller is not strategically placed within the network,this communication can experience increased delays,negatively affecting network performance.Specifically,an improperly placed controller can lead to higher end-to-end(E2E)delay,as switches must traverse more hops or encounter greater propagation delays when communicating with the controller.This paper introduces a novel approach using Deep Q-Learning(DQL)to dynamically place controllers in Software-Defined Internet of Things(SD-IoT)environments,with the goal of minimizing E2E delay between switches and controllers.E2E delay,a crucial metric for network performance,is influenced by two key factors:hop count,which measures the number of network nodes data must traverse,and propagation delay,which accounts for the physical distance between nodes.Our approach models the controller placement problem as a Markov Decision Process(MDP).In this model,the network configuration at any given time is represented as a“state,”while“actions”correspond to potential decisions regarding the placement of controllers or the reassignment of switches to controllers.Using a Deep Q-Network(DQN)to approximate the Q-function,the system learns the optimal controller placement by maximizing the cumulative reward,which is defined as the negative of the E2E delay.Essentially,the lower the delay,the higher the reward the system receives,enabling it to continuously improve its controller placement strategy.The experimental results show that our DQL-based method significantly reduces E2E delay when compared to traditional benchmark placement strategies.By dynamically learning from the network’s real-time conditions,the proposed method ensures that controller placement remains efficient and responsive,reducing communication delays and enhancing overall network performance.
基金financially supported by the National Natural Science Foundation of China (Grant Nos. 52225403, 52304146, 51827901)Sichuan Science and Technology Program (2023NSFSC0919)。
文摘The pressure-preserving controller is the core part of deep in-situ pressure-preserving coring(IPP-Coring) system, and its pressure-preserving capability is the key to IPP-Coring technology. To achieve a good understanding of the influence of mechanical properties of materials on the ultimate pressure-bearing capability(UPB-Capability) of the pressure-preserving controller, the IPP-Coring experimental platform was developed to test the UPB-Capability of pressure-preserving controllers of four different materials. The experimental results show that the UPB-Capability of pressure-preserving controllers with different material varies greatly. A numerical model of the pressure-preserving controller was developed to study the influences of mechanical parameters of materials on the UPB-Capability of the pressurepreserving controller after the accuracy of the numerical model is verified by experiments. The results indicate that the yield strength(YS) and Poisson's ratio(PR) of the material have little effect on the UPB-Capability of the pressure-preserving controller, whereas the elastic modulus(EM) of the material has a significant effect. A generalized model of the UPB-Capability of the pressure-preserving controller is developed to reveal the mechanism of the influence of material properties on the UPB-Capability of the pressure-preserving controllers. Considering these results, the future optimization direction of the pressure-preserving controller and material selection scheme in practical engineering applications of the pressure-preserving controller are suggested.
文摘Software-Defined Networking(SDN)improves network management by separating its control logic from the underlying hardware and integrating it into a logically centralized control unit,termed the SDN controller.SDN adaptation is essential for wireless networks because it offers enhanced and data-intensive services.The initial intent of the SDN design was to have a physically centralized controller.However,network experts have suggested logically centralized and physically distributed designs for SDN controllers,owing to issues such as a single point of failure and scalability.This study addressed the security,scalability,reliability,and consistency issues associated with the design of distributed SDN controllers.Moreover,the security issues of an enterprise related to multiple physically distributed controllers in a software-defined wireless local area network(SD-WLAN)were emphasized,and optimal solutions were suggested.
文摘This paper proposes an adaptive nonlinear proportional-derivative(ANPD)controller for a two-wheeled self-balancing robot(TWSB)modeled by the Lagrange equation with external forces.The proposed control scheme is designed based on the combination of a nonlinear proportional-derivative(NPD)controller and a genetic algorithm,in which the proportional-derivative(PD)parameters are updated online based on the tracking error and the preset error threshold.In addition,the genetic algorithm is employed to adaptively select initial controller parameters,contributing to system stability and improved control accuracy.The proposed controller is basic in design yet simple to implement.The ANPD controller has the advantage of being computationally lightweight and providing high robustness against external forces.The stability of the closed-loop system is rigorously analyzed and verified using Lyapunov theory,providing theoretical assurance of its robustness.Simulations and experimental results show that the TWSB robot with the proposed ANPD controller achieves quick balance and tracks target values with very small errors,demonstrating the effectiveness and performance of the proposed controller.The proposed ANPD controller demonstrates significant improvements in balancing and tracking performance for two-wheeled self-balancing robots,which has great applicability in the field of robot control systems.This represents a promising solution for applications requiring precise and stable motion control under varying external conditions.
基金supported by the National Natural Science Foundation of China(11972077,11672035)。
文摘Detumbling operation toward a rotating target with nutation is meaningful for debris removal but challenging. In this study, a deformable end-effector is first designed based on the requirements for contacting the nutating target. A dual-arm robotic system installed with the deformable end-effectors is modeled and the movement of the end-tips is analyzed. The complex operation of the contact toward a nutating target places strict requirements on control accuracy and controller robustness. Thus, an improvement of the tracking error transformation is proposed and an adaptive sliding mode controller with prescribed performance is designed to guarantee the fast and precise motion of the effector during the contact detumbling.Finally, by employing the proposed effector and the controller,numerical simulations are carried out to verify the effectiveness and efficiency of the contact detumbling toward a nutating target.
基金supported by the Fundamental Research Funds for the Central Universities(DUT22RT(3)090)the National Natural Science Foundation of China(61890920,61890921,62122016,08120003)Liaoning Science and Technology Program(2023JH2/101700361).
文摘Linear temporal logic(LTL)is an intuitive and expressive language to specify complex control tasks,and how to design an efficient control strategy for LTL specification is still a challenge.In this paper,we implement the dynamic quantization technique to propose a novel hierarchical control strategy for nonlinear control systems under LTL specifications.Based on the regions of interest involved in the LTL formula,an accepting path is derived first to provide a high-level solution for the controller synthesis problem.Second,we develop a dynamic quantization based approach to verify the realization of the accepting path.The realization verification results in the necessity of the controller design and a sequence of quantization regions for the controller design.Third,the techniques of dynamic quantization and abstraction-based control are combined together to establish the local-to-global control strategy.Both abstraction construction and controller design are local and dynamic,thereby resulting in the potential reduction of the computational complexity.Since each quantization region can be considered locally and individually,the proposed hierarchical mechanism is more efficient and can solve much larger problems than many existing methods.Finally,the proposed control strategy is illustrated via two examples from the path planning and tracking problems of mobile robots.
基金Supported by Youth Fund of Jiangsu Provincial Natural Science Foundation of China(Grant No.BK20200423)National Natural Science Foundation of China(Grant Nos.52102435,52072175)+2 种基金Jiangsu Outstanding Youth Fund Project of China(Grant No.BK20220078)Jiangsu Provincial Key R&D Plan of China(Grant No.BE2022053)Postgraduate Research&Practice Innovation Program of NUAA of China(Grant No.xcxjh20220210)。
文摘This study presents a tracking and fault-tolerant controller architecture for uncertain steer-by-wire(SbW)systems using model predictive control in the presence of actuator malfunction and the nonlinear properties of tire lateral stiffness coefficients.By changing the internal model,the model predictive control(MPC)technique was used to achieve optimal tracking performance under the actuator output limitation variation problem and uncertain system parameters.System parameters and state estimates were simultaneously provided by the fault detection and isolation modules to detect actuator failure using the coupling estimation approach.The estimation accuracy was further improved by considering the replacement errors as virtual noise,which was also estimated during the estimation process.Simulation and experimental results demonstrate that the proposed fault-tolerant control technique can identify motor faults and conduct fault-tolerant control based on fault identification,showing good front-wheel steering angle tracking performance under both normal and fault conditions.
文摘The primary factor contributing to frequency instability in microgrids is the inherent intermittency of renewable energy sources.This paper introduces novel dual-backup controllers utilizing advanced fractional order proportional integral derivative(FOPID)controllers to enhance frequency and tie-line power stability in microgrids amid increasing renewable energy integration.To improve load frequency control,the proposed controllers are applied to a two-area interconnectedmicrogrid system incorporating diverse energy sources,such as wind turbines,photovoltaic cells,diesel generators,and various storage technologies.A novelmeta-heuristic algorithm is adopted to select the optimal parameters of the proposed controllers.The efficacy of the advanced FOPID controllers is demonstrated through comparative analyses against traditional proportional integral derivative(PID)and FOPID controllers,showcasing superior performance inmanaging systemfluctuations.The optimization algorithm is also evaluated against other artificial intelligent methods for parameter optimization,affirming the proposed solution’s efficiency.The robustness of the intelligent controllers against system uncertainties is further validated under extensive power disturbances,proving their capability to maintain grid stability.The dual-controller configuration ensures redundancy,allowing them to operate as mutual backups,enhancing system reliability.This research underlines the importance of sophisticated control strategies for future-proofing microgrid operations against the backdrop of evolving energy landscapes.
基金This research was funded by the Deputyship for Research and Innovation,Ministry of Education,Saudi Arabia,through the University of Tabuk,Grant Number S-1443-0123.
文摘An autonomous microgrid that runs on renewable energy sources is presented in this article.It has a supercon-ducting magnetic energy storage(SMES)device,wind energy-producing devices,and an energy storage battery.However,because such microgrids are nonlinear and the energy they create varies with time,controlling and managing the energy inside them is a difficult issue.Fractional-order proportional integral(FOPI)controller is recommended for the current research to enhance a standalone microgrid’s energy management and performance.The suggested dedicated control for the SMES comprises two loops:the outer loop,which uses the FOPI to regulate the DC-link voltage,and the inner loop,responsible for regulating the SMES current,is constructed using the intelligent FOPI(iFOPI).The FOPI+iFOPI parameters are best developed using the dandelion optimizer(DO)approach to achieve the optimum performance.The suggested FOPI+iFOPI controller’s performance is contrasted with a conventional PI controller for variations in wind speed and microgrid load.The optimal FOPI+iFOPI controller manages the voltage and frequency of the load.The behavior of the microgrid as a reaction to step changes in load and wind speed was measured using the proposed controller.MATLAB simulations were used to evaluate the recommended system’s performance.The results of the simulations showed that throughout all interruptions,the recommended microgrid provided the load with AC power with a constant amplitude and frequency.In addition,the required load demand was accurately reduced.Furthermore,the microgrid functioned incredibly well despite SMES and varying wind speeds.Results obtained under identical conditions were compared with and without the best FOPI+iFOPI controller.When utilizing the optimal FOPI+iFOPI controller with SMES,it was found that the microgrid performed better than the microgrid without SMES.
基金supported by the National Science and Technology Council under grants NSTC 112-2221-E-320-002the Buddhist Tzu Chi Medical Foundation in Taiwan under Grant TCMMP 112-02-02.
文摘In many Eastern and Western countries,falling birth rates have led to the gradual aging of society.Older adults are often left alone at home or live in a long-term care center,which results in them being susceptible to unsafe events(such as falls)that can have disastrous consequences.However,automatically detecting falls fromvideo data is challenging,and automatic fall detection methods usually require large volumes of training data,which can be difficult to acquire.To address this problem,video kinematic data can be used as training data,thereby avoiding the requirement of creating a large fall data set.This study integrated an improved particle swarm optimization method into a double interactively recurrent fuzzy cerebellar model articulation controller model to develop a costeffective and accurate fall detection system.First,it obtained an optical flow(OF)trajectory diagram from image sequences by using the OF method,and it solved problems related to focal length and object offset by employing the discrete Fourier transform(DFT)algorithm.Second,this study developed the D-IRFCMAC model,which combines spatial and temporal(recurrent)information.Third,it designed an IPSO(Improved Particle Swarm Optimization)algorithm that effectively strengthens the exploratory capabilities of the proposed D-IRFCMAC(Double-Interactively Recurrent Fuzzy Cerebellar Model Articulation Controller)model in the global search space.The proposed approach outperforms existing state-of-the-art methods in terms of action recognition accuracy on the UR-Fall,UP-Fall,and PRECIS HAR data sets.The UCF11 dataset had an average accuracy of 93.13%,whereas the UCF101 dataset had an average accuracy of 92.19%.The UR-Fall dataset had an accuracy of 100%,the UP-Fall dataset had an accuracy of 99.25%,and the PRECIS HAR dataset had an accuracy of 99.07%.
基金supported in part by the Nebraska Center for Energy Sciences Research.
文摘Grid-tie voltage source converters(VSCs)can operate in three distinct modes:AC-dominant,DC-dominant,and balanced,depending on the placement of the stiff voltage sources.The distinct operation modes of the VSCs traditionally demand different synchronization control techniques,leading to heterogeneous VSCs.It is challenging for the power system to accommodate and coordinate heterogeneous VSCs.A promising universal synchronization control technique for VSCs is the DC-link voltage synchronization control(DVSC)based on a lead compensator(LC).The LC DVSC stabilizes both the DC and AC voltages of a VSC while achieving synchronization with the AC grid.This results in a dual-port grid-forming(DGFM)characteristic for the VSC.However,there has been very limited study on the stability and synchronization controller design of the VSCs with the LC DVSC operating in various modes.To bridge this gap,the paper presents a quantitative analysis on the stability and steady-state performance of the LC DVSC in all three operation modes of the DGFM VSC.Based on the analysis,the paper provides step-by-step design guidelines for the LC DVSC.Furthermore,the paper uncovers an instability issue related to the LC DVSC when the DGFM VSC operates in the balanced mode.To tackle the instability issue,a virtual resistance control is proposed and integrated with the LC DVSC.Simulation results validate the analysis and demonstrate the effectiveness of the DGFM VSC with the LC DVSC designed using the proposed guidelines in all three operation modes.Overall,the paper demonstrates the feasibility of employing the DGFM VSC with the LC DVSC for all three possible operation modes,which can help overcome the challenges associated with accommodating and coordinating heterogeneous VSCs in the power system.
基金The Project of China Vocational Education Association(ZJS2022YB024)。
文摘This paper addresses the problems faced in programmable logic controller(PLC)teaching in vocational colleges and proposes countermeasures to overcome these challenges.The study emphasizes the need for a deeper understanding of fundamental concepts and the integration of practical application in PLC education.It suggests involving students in teacher-led projects to enhance their programming skills and problem-solving skills.Additionally,the paper highlights the importance of interactive learning and collaborative discussions to foster student engagement.Furthermore,it emphasizes the cultivation of innovation consciousness through participation in innovation competitions and projects.The implementation of these strategies has shown positive results in improving learning outcomes and preparing students for careers in automation and control.This research contributes to the development of effective teaching approaches in PLC education in vocational colleges.
