The trajectory tracking control performance of nonholonomic wheeled mobile robots(NWMRs)is subject to nonholonomic constraints,system uncertainties,and external disturbances.This paper proposes a barrier function-base...The trajectory tracking control performance of nonholonomic wheeled mobile robots(NWMRs)is subject to nonholonomic constraints,system uncertainties,and external disturbances.This paper proposes a barrier function-based adaptive sliding mode control(BFASMC)method to provide high-precision,fast-response performance and robustness for NWMRs.Compared with the conventional adaptive sliding mode control,the proposed control strategy can guarantee that the sliding mode variables converge to a predefined neighborhood of origin with a predefined reaching time independent of the prior knowledge of the uncertainties and disturbances bounds.Another advantage of the proposed algorithm is that the control gains can be adaptively adjusted to follow the disturbances amplitudes thanks to the barrier function.The benefit is that the overestimation of control gain can be eliminated,resulting in chattering reduction.Moreover,a modified barrier function-like control gain is employed to prevent the input saturation problem due to the physical limit of the actuator.The stability analysis and comparative experiments demonstrate that the proposed BFASMC can ensure the prespecified convergence performance of the NWMR system output variables and strong robustness against uncertainties/disturbances.展开更多
This paper investigates the trajectory following problem of exoskeleton robots with numerous constraints. However, as a typical nonlinear system with variability and parameter uncertainty, it is difficult to accuratel...This paper investigates the trajectory following problem of exoskeleton robots with numerous constraints. However, as a typical nonlinear system with variability and parameter uncertainty, it is difficult to accurately achieve the trajectory tracking control for exoskeletons. In this paper, we present a robust control of trajectory tracking control based on servo constraints. Firstly, we consider the uncertainties (e.g., modelling errors, initial condition deviations, structural vibrations, and other unknown external disturbances) in the exoskeleton system, which are time-varying and bounded. Secondly, we establish the dynamic model and formulate a close-loop connection between the dynamic model and the real world. Then, the trajectory tracking issue is regarded as a servo constraint problem, and an adaptive robust control with leakage-type adaptive law is proposed with the guaranteed Lyapunov stability. Finally, we conduct numerical simulations to verify the performance of the proposed controller.展开更多
In order to design a suitable controller which can achieve accurate trajectory tracking and a good control performance, and guarantee the stability and robustness of a robot system due to external disturbances error a...In order to design a suitable controller which can achieve accurate trajectory tracking and a good control performance, and guarantee the stability and robustness of a robot system due to external disturbances error and internal parameter variations, an adaptive switching control strategy is proposed. The proposed scheme is designed under the condition of bounded distances and consists of an adaptive switching law and a PD controller. Based on the Lyapunov stability theory, it is proved that the proposed scheme can guarantee the tracking performance of the robotic manipulator and is adapted to varying unknown loads. Simulations are carded out on a two-link robotic manipulator, which illustrate the feasibility and validity of the proposed control scheme and the robustness for variational payloads.展开更多
This paper presents a pressure observer based adaptive robust controller (POARC) for posture trajectory tracking of a parallel manipulator driven by three pneumatic muscles without pressure sensors. Due to model error...This paper presents a pressure observer based adaptive robust controller (POARC) for posture trajectory tracking of a parallel manipulator driven by three pneumatic muscles without pressure sensors. Due to model errors of the static forces and friction forces of pneumatic muscles, simplified average flow rate characteristics of valves, unknown disturbances of entire system, and unmeasured pressures, there exist rather severe parametric uncertainties, nonlinear uncertainties and dynamic uncertainties in modeling of the parallel manipulator. A nonlinear pressure observer is constructed to estimate unknown pressures on the basis of a single-input-single-output (SISO) decoupling model that is simplified from the actual multiple-input-multiple-output (MIMO) coupling model of the parallel manipulator. Then, an adaptive robust controller integrated with the pressure observer is developed to accomplish high precision posture trajectory tracking of the parallel manipulator. The experimental results indicate that the system with the proposed POARC not only achieves good control accuracy and smooth movement but also maintains robustness to disturbances.展开更多
Friction compensation is particularly important for motion trajectory tracking control of pneumatic cylinders at low speed movement. However, most of the existing model-based friction compensation schemes use simple c...Friction compensation is particularly important for motion trajectory tracking control of pneumatic cylinders at low speed movement. However, most of the existing model-based friction compensation schemes use simple classical models, which are not enough to address applications with high-accuracy position requirements. Furthermore, the friction force in the cylinder is time-varying, and there exist rather severe unmodelled dynamics and unknown disturbances in the pneumatic system. To deal with these problems effectively, an adaptive robust controller with LuGre model-based dynamic friction compensation is constructed. The proposed controller employs on-line recursive least squares estimation（RLSE） to reduce the extent of parametric uncertainties, and utilizes the sliding mode control method to attenuate the effects of parameter estimation errors, unmodelled dynamics and disturbances. In addition, in order to realize LuGre model-based friction compensation, the modified dual-observer structure for estimating immeasurable friction internal state is developed. Therefore, a prescribed motion tracking transient performance and final tracking accuracy can be guaranteed. Since the system model uncertainties are unmatched, the recursive backstepping design technology is applied. In order to solve the conflicts between the sliding mode control design and the adaptive control design, the projection mapping is used to condition the RLSE algorithm so that the parameter estimates are kept within a known bounded convex set. Finally, the proposed controller is tested for tracking sinusoidal trajectories and smooth square trajectory under different loads and sudden disturbance. The testing results demonstrate that the achievable performance of the proposed controller is excellent and is much better than most other studies in literature. Especially when a 0.5 Hz sinusoidal trajectory is tracked, the maximum tracking error is 0.96 mm and the average tracking error is 0.45 mm. This paper constructs an adaptive robust controller which can compensate the friction force in the cylinder.展开更多
Wheeled mobile robot is one of the well-known nonholonomic systems. A two-wheeled sell-balance robot is taken as the research objective. This paper carried out a detailed force analysis of the robot and established a ...Wheeled mobile robot is one of the well-known nonholonomic systems. A two-wheeled sell-balance robot is taken as the research objective. This paper carried out a detailed force analysis of the robot and established a non-linear dynamics model. An adaptive tracking controller for the kinematic model of a nonhotonomic mobile robot with unknown parameters is also proposed. Using control Lyapunov function （CLF）, the controller＇s global asymptotic stability has been proven. The adaptive trajectory tracking controller decreases the disturbance in the course of tracking control and enhances the real-time control characteristics. The simulation result indicated that the wheeled mobile robot tracking can be effectively controlled.展开更多
In order to solve the problem of trajectory tracking for a class of novel serial-parallel hybrid humanoid arm（HHA）, which has parameters uncertainty, frictions, disturbance, abrasion and pulse forces derived from mo...In order to solve the problem of trajectory tracking for a class of novel serial-parallel hybrid humanoid arm（HHA）, which has parameters uncertainty, frictions, disturbance, abrasion and pulse forces derived from motors, a multistep dynamics modeling strategy is proposed and a robust controller based on neural network（NN）-adaptive algorithm is designed. At the first step of dynamics modeling, the dynamics model of the reduced HHA is established by Lagrange method. At the second step of dynamics modeling, the parameter uncertain part resulting mainly from the idealization of the HHA is learned by adaptive algorithm. In the trajectory tracking controller, the radial basis function（RBF） NN, whose optimal weights are learned online by adaptive algorithm, is used to learn the upper limit function of the total uncertainties including frictions, disturbances, abrasion and pulse forces. To a great extent, the conservatism of this robust trajectory tracking controller is reduced, and by this controller the HHA can impersonate mostly human actions. The proof and simulation results testify the validity of the adaptive strategy for parameter learning and the neural network-adaptive strategy for the trajectory tracking control.展开更多
This paper presents a two-wheeled differential spherical mobile robot in view of the problems that the motion of spherical robot is difficult to control and the sensor is limited by the spherical shell.The robot is si...This paper presents a two-wheeled differential spherical mobile robot in view of the problems that the motion of spherical robot is difficult to control and the sensor is limited by the spherical shell.The robot is simple in structure,flexible in motion and easy to control.The kinematics and dynamics model of spherical mobile robot is established according to the structure of spherical mobile robot.On the basis of the adaptive neural sliding mode control,the trajectory tracking controller of the system is designed.During the simulation of the s-trajectory and circular trajectory tracking control of the spherical mobile robot,it is concluded that the spherical mobile robot is flexible in motion and easy to control.In addition,the simulation results show that the adaptive neural sliding mode control can effectively track the trajectory of the spherical robot.The adaptive control eliminates the influence of unknown parameters and disturbances,and avoids the jitter of left and right wheels during the torque output.展开更多
To achieve high-precision trajectory following during helicopter maneuver tasks and reduce the disruptive influences of unknown variabilities,this study introduces a cascaded-loop helicopter trajectory tracking contro...To achieve high-precision trajectory following during helicopter maneuver tasks and reduce the disruptive influences of unknown variabilities,this study introduces a cascaded-loop helicopter trajectory tracking controller,whose parameters are set using an Ant Colony OptimizationSlime Mould Algorithm(ACO-SMA).Initially,a nonlinear flight dynamics model of the helicopter is constructed.Observer gain functions and nonlinear feedback from a vibrational suppression function to improve the tracking performance of the controller,addressing issues in disturbance estimation and compensation of the Active Disturbance Rejection Control(ADRC).Simultaneously,a cascaded loop system,comprising an internal attitude loop and an external position loop,is created,and the ant colony-slime mold hybrid algorithm optimizes the system parameters of the trajectory tracking controller.Finally,helicopter trajectory tracking simulation experiments are conducted,including spiral ascending and“8”shape climbing maneuvers.The findings indicate that the ADRC employed for helicopter trajectory tracking exhibits outstanding performance in rejecting disturbances caused by gusts and accurately tracking trajectories.The trajectory tracking controller,whose parameters are optimized by the ACO-SMA,shows higher tracking precision compared to the conventional PID and ADRC,thereby substantially improving the precision of maneuver tasks.展开更多
In this paper, an iterative learning control strategy is presented for a class of nonlinear time-varying systems, the timevarying parameters are expanded into Fourier series with bounded remainder term. The backsteppi...In this paper, an iterative learning control strategy is presented for a class of nonlinear time-varying systems, the timevarying parameters are expanded into Fourier series with bounded remainder term. The backstepping design technique is used to deal with system dynamics with non-global Lipschitz nonlinearities and the approach proposed in this paper solves the non-uniform trajectory tracking problem. Based on the Lyapunov-like synthesis, the proposed method shows that all signals in the closed-loop system remain bounded over a pre-specified time interval [0, T ]. And perfect non-uniform trajectory tracking of the system output is completed. A typical series is introduced in order to deal with the unknown bound of remainder term. Finally, a simulation example shows the feasibility and effectiveness of the approach.展开更多
This paper focuses on the trajectory tracking control problem of unmanned underwater vehicles(UUVs)with unknown dead-zone inputs.The primary objective is to design an adaptive trajectory tracking error constraint cont...This paper focuses on the trajectory tracking control problem of unmanned underwater vehicles(UUVs)with unknown dead-zone inputs.The primary objective is to design an adaptive trajectory tracking error constraint controller using the fully actuated systems(FAs)approach to enable UUVs to asymptotically track target signals.Firstly,a novel error constraint fully actuated systems(ECFAs)approach is proposed by incorporating the tracking error dependent normalized function and barrier function along with time-varying scaling.Secondly,in order to deal with the model uncertainties of the UUVs,adaptive radial basis function neural networks(RBFNNs)is combined with the ECFAs approach.Then,a positive time-varying integral function is introduced to completely eliminate the effect of the residual effect caused by unknown dead-zone inputs,and it is proved that the trajectory tracking error converges to zero asymptotically based on the Lyapunov functions.Finally,the simulation results demonstrate the effectiveness of the designed adaptive controller.展开更多
This paper mainly focuses on the development of a learning-based controller for a class of uncertain mechanical systems modeled by the Euler-Lagrange formulation.The considered system can depict the behavior of a larg...This paper mainly focuses on the development of a learning-based controller for a class of uncertain mechanical systems modeled by the Euler-Lagrange formulation.The considered system can depict the behavior of a large class of engineering systems,such as vehicular systems,robot manipulators and satellites.All these systems are often characterized by highly nonlinear characteristics,heavy modeling uncertainties and unknown perturbations,therefore,accurate-model-based nonlinear control approaches become unavailable.Motivated by the challenge,a reinforcement learning(RL)adaptive control methodology based on the actor-critic framework is investigated to compensate the uncertain mechanical dynamics.The approximation inaccuracies caused by RL and the exogenous unknown disturbances are circumvented via a continuous robust integral of the sign of the error(RISE)control approach.Different from a classical RISE control law,a tanh(·)function is utilized instead of a sign(·)function to acquire a more smooth control signal.The developed controller requires very little prior knowledge of the dynamic model,is robust to unknown dynamics and exogenous disturbances,and can achieve asymptotic output tracking.Eventually,co-simulations through ADAMS and MATLAB/Simulink on a three degrees-of-freedom(3-DOF)manipulator and experiments on a real-time electromechanical servo system are performed to verify the performance of the proposed approach.展开更多
In this paper, the problem of adaptive tracking control for a class of nonlinear large scale systems with unknown parameters entering linearly is discussed. Based on the theory of input output linearization of nonli...In this paper, the problem of adaptive tracking control for a class of nonlinear large scale systems with unknown parameters entering linearly is discussed. Based on the theory of input output linearization of nonlinear systems, direct adaptive control schemes are presented to achieve bounded tracking. The proposed control schemes are robust with respect to the uncertainties in interconnection structure as well as subsystem dynamics. A numerical example is given to illustrate the efficiency of this method.展开更多
One of the primary difficulties in using powered parafoil(PPF) systems is the lack of effective trajectory tracking controllers since the trajectory tracking control is the essential operation for PPF to accomplish au...One of the primary difficulties in using powered parafoil(PPF) systems is the lack of effective trajectory tracking controllers since the trajectory tracking control is the essential operation for PPF to accomplish autonomous tasks. The characteristic model(CM) based all-coefficient adaptive control(ACAC) designed for PPF systems in horizontal and vertical trajectory control is proposed. The method is easy to use and convenient to adjust and test. Just a few parameters are adapted during the control process. In application, vertical and horizontal CMs are designed and ACAC controllers are constructed to control vertical altitude and horizontal trajectory of PPF based on the proposed CMs, respectively. Result analysis of different simulations shows that the applied ACAC control method is effective for trajectory tracking of the PPF systems and the approach guarantees the transient performance of the PPF systems with better disturbance rejection ability.展开更多
An adaptive decentralized asymptotic tracking control scheme is developed in this paper for a class of large-scale nonlinear systems with unknown strong interconnections,unknown time-varying parameters,and disturbance...An adaptive decentralized asymptotic tracking control scheme is developed in this paper for a class of large-scale nonlinear systems with unknown strong interconnections,unknown time-varying parameters,and disturbances.First,by employing the intrinsic properties of Gaussian functions for the interconnection terms for the first time,all extra signals in the framework of decentralized control are filtered out,thereby removing all additional assumptions imposed on the interconnec-tions,such as upper bounding functions and matching conditions.Second,by introducing two integral bounded functions,asymptotic tracking control is realized.Moreover,the nonlinear filters with the compensation terms are introduced to circumvent the issue of“explosion of complexity”.It is shown that all the closed-loop signals are bounded and the tracking errors converge to zero asymptotically.In the end,a simulation example is carried out to demonstrate the effectiveness of the proposed approach.展开更多
This paper discusses consensus problems for high-dimensional networked multi-agent systems with fixed topology. The communication topology of multi-agent systems is represented by a digraph. A new consensus protocol i...This paper discusses consensus problems for high-dimensional networked multi-agent systems with fixed topology. The communication topology of multi-agent systems is represented by a digraph. A new consensus protocol is proposed, and consensus convergence of multigent systems is analyzed based on the Lyapunov stability theory. The consensus problem can be formulated into solving a feasible problem with bilinear matrix inequality （BMI） constrains. Furthermore, the consensus protocol is extended to achieving tracking and formation control. By introducing the formation structure set, each agent can gain its individual desired trajectory. Finally, numerical simulations are provided to show the effectiveness of our strategies. The results show that agents from arbitrary initial states can asymptotically reach a consensus. In addition, agents with high-dimensional can track any target trajectory, and maintain desired formation during movement by selecting appropriate structure set.展开更多
In this paper,an asymmetric bipartite consensus problem for the nonlinear multi-agent systems with cooperative and antagonistic interactions is studied under the event-triggered mechanism.For the agents described by a...In this paper,an asymmetric bipartite consensus problem for the nonlinear multi-agent systems with cooperative and antagonistic interactions is studied under the event-triggered mechanism.For the agents described by a structurally balanced signed digraph,the asymmetric bipartite consensus objective is firstly defined,assigning the agents'output to different signs and module values.Considering with the completely unknown dynamics of the agents,a novel event-triggered model-free adaptive bipartite control protocol is designed based on the agents'triggered outputs and an equivalent compact form data model.By utilizing the Lyapunov analysis method,the threshold of the triggering condition is obtained.Subsequently,the asymptotic convergence of the tracking error is deduced and a sufficient condition is obtained based on the contraction mapping principle.Finally,the simulation example further demonstrates the effectiveness of the protocol.展开更多
This paper proposes an L_(1)adaptive fault tolerant control method for trajectory tracking of tail-sitter aircraft in the state of motor loss fault.The tail-sitter model considers the uncertainties produced by the fea...This paper proposes an L_(1)adaptive fault tolerant control method for trajectory tracking of tail-sitter aircraft in the state of motor loss fault.The tail-sitter model considers the uncertainties produced by the features of nonlinearities and couplings which cause difficulties in control.An L_(1)adaptive controller is designed to reduce the position and attitude error when actuators have faults.A reference trajectory containing large maneuver flight transitions is designed,which makes it even harder for the L_(1)controller to track accurately.Compensators are designed to assist L_(1)adaptive controller tracking of the reference trajectory.The stability of the L_(1)adaptive controller including compensators is proved.Finally,the simulation results are used to analyse the effectiveness of the proposed controller.Compared to the H∞controller,the L_(1)adaptive controller with compensators has better performance in position control and attitude control under fault tolerance state even when the aircraft conducts large maneuver.Besides,as the L_(1)adaptive control method separates feedback control and adaptive law design,the response speed of the whole system is improved.展开更多
In order to solve the problems of dynamic modeling and complicated parameters identification of trajectory tracking control of the quadrotor,a data driven model-free adaptive control method based on the improved slidi...In order to solve the problems of dynamic modeling and complicated parameters identification of trajectory tracking control of the quadrotor,a data driven model-free adaptive control method based on the improved sliding mode control(ISMC)algorithm is designed,which does not depend on the precise dynamic model of the quadrotor.The design of the general sliding mode control(SMC)algorithm depends on the mathematical model of the quadrotor and has chattering problems.In this paper,according to the dynamic characteristics of the quadrotor,an adaptive update law is introduced and a saturation function is used to improve the SMC.The proposed control strategy has an inner and an outer loop control structures.The outer loop position control provides the required reference attitude angle for the inner loop.The inner loop attitude control ensures rapid convergence of the attitude angle.The effectiveness and feasibility of the algorithm are verified by mathematical simulation.The mathematical simulation results show that the designed model-free adaptive control method of the quadrotor is effective,and it can effectively realize the trajectory tracking control of the quadrotor.The design of the controller does not depend on the kinematic and dynamic models of the unmanned aerial vehicle(UAV),and has high control accuracy,stability,and robustness.展开更多
基金the China Scholarship Council(202106690037)the Natural Science Foundation of Anhui Province(19080885QE194)。
文摘The trajectory tracking control performance of nonholonomic wheeled mobile robots(NWMRs)is subject to nonholonomic constraints,system uncertainties,and external disturbances.This paper proposes a barrier function-based adaptive sliding mode control(BFASMC)method to provide high-precision,fast-response performance and robustness for NWMRs.Compared with the conventional adaptive sliding mode control,the proposed control strategy can guarantee that the sliding mode variables converge to a predefined neighborhood of origin with a predefined reaching time independent of the prior knowledge of the uncertainties and disturbances bounds.Another advantage of the proposed algorithm is that the control gains can be adaptively adjusted to follow the disturbances amplitudes thanks to the barrier function.The benefit is that the overestimation of control gain can be eliminated,resulting in chattering reduction.Moreover,a modified barrier function-like control gain is employed to prevent the input saturation problem due to the physical limit of the actuator.The stability analysis and comparative experiments demonstrate that the proposed BFASMC can ensure the prespecified convergence performance of the NWMR system output variables and strong robustness against uncertainties/disturbances.
文摘This paper investigates the trajectory following problem of exoskeleton robots with numerous constraints. However, as a typical nonlinear system with variability and parameter uncertainty, it is difficult to accurately achieve the trajectory tracking control for exoskeletons. In this paper, we present a robust control of trajectory tracking control based on servo constraints. Firstly, we consider the uncertainties (e.g., modelling errors, initial condition deviations, structural vibrations, and other unknown external disturbances) in the exoskeleton system, which are time-varying and bounded. Secondly, we establish the dynamic model and formulate a close-loop connection between the dynamic model and the real world. Then, the trajectory tracking issue is regarded as a servo constraint problem, and an adaptive robust control with leakage-type adaptive law is proposed with the guaranteed Lyapunov stability. Finally, we conduct numerical simulations to verify the performance of the proposed controller.
基金The National Natural Science Foundation of China(No.61273119,61374038,61473079)
文摘In order to design a suitable controller which can achieve accurate trajectory tracking and a good control performance, and guarantee the stability and robustness of a robot system due to external disturbances error and internal parameter variations, an adaptive switching control strategy is proposed. The proposed scheme is designed under the condition of bounded distances and consists of an adaptive switching law and a PD controller. Based on the Lyapunov stability theory, it is proved that the proposed scheme can guarantee the tracking performance of the robotic manipulator and is adapted to varying unknown loads. Simulations are carded out on a two-link robotic manipulator, which illustrate the feasibility and validity of the proposed control scheme and the robustness for variational payloads.
基金Project (No.50775200) supported by the National Natural Science Foundation of China
文摘This paper presents a pressure observer based adaptive robust controller (POARC) for posture trajectory tracking of a parallel manipulator driven by three pneumatic muscles without pressure sensors. Due to model errors of the static forces and friction forces of pneumatic muscles, simplified average flow rate characteristics of valves, unknown disturbances of entire system, and unmeasured pressures, there exist rather severe parametric uncertainties, nonlinear uncertainties and dynamic uncertainties in modeling of the parallel manipulator. A nonlinear pressure observer is constructed to estimate unknown pressures on the basis of a single-input-single-output (SISO) decoupling model that is simplified from the actual multiple-input-multiple-output (MIMO) coupling model of the parallel manipulator. Then, an adaptive robust controller integrated with the pressure observer is developed to accomplish high precision posture trajectory tracking of the parallel manipulator. The experimental results indicate that the system with the proposed POARC not only achieves good control accuracy and smooth movement but also maintains robustness to disturbances.
基金Supported by National Natural Science Foundation of China(Grant Nos.50775200,50905156)
文摘Friction compensation is particularly important for motion trajectory tracking control of pneumatic cylinders at low speed movement. However, most of the existing model-based friction compensation schemes use simple classical models, which are not enough to address applications with high-accuracy position requirements. Furthermore, the friction force in the cylinder is time-varying, and there exist rather severe unmodelled dynamics and unknown disturbances in the pneumatic system. To deal with these problems effectively, an adaptive robust controller with LuGre model-based dynamic friction compensation is constructed. The proposed controller employs on-line recursive least squares estimation（RLSE） to reduce the extent of parametric uncertainties, and utilizes the sliding mode control method to attenuate the effects of parameter estimation errors, unmodelled dynamics and disturbances. In addition, in order to realize LuGre model-based friction compensation, the modified dual-observer structure for estimating immeasurable friction internal state is developed. Therefore, a prescribed motion tracking transient performance and final tracking accuracy can be guaranteed. Since the system model uncertainties are unmatched, the recursive backstepping design technology is applied. In order to solve the conflicts between the sliding mode control design and the adaptive control design, the projection mapping is used to condition the RLSE algorithm so that the parameter estimates are kept within a known bounded convex set. Finally, the proposed controller is tested for tracking sinusoidal trajectories and smooth square trajectory under different loads and sudden disturbance. The testing results demonstrate that the achievable performance of the proposed controller is excellent and is much better than most other studies in literature. Especially when a 0.5 Hz sinusoidal trajectory is tracked, the maximum tracking error is 0.96 mm and the average tracking error is 0.45 mm. This paper constructs an adaptive robust controller which can compensate the friction force in the cylinder.
基金Supported by the National High Technology Research and Development Programme of China (No. 2006AA04Z245)the Program for Changjiang Scholars and Innovative Research Team in University ( No. IRT0423)the Fund for Foreign Scholars in University Research and Teaching Programs (No. B07018)
文摘Wheeled mobile robot is one of the well-known nonholonomic systems. A two-wheeled sell-balance robot is taken as the research objective. This paper carried out a detailed force analysis of the robot and established a non-linear dynamics model. An adaptive tracking controller for the kinematic model of a nonhotonomic mobile robot with unknown parameters is also proposed. Using control Lyapunov function （CLF）, the controller＇s global asymptotic stability has been proven. The adaptive trajectory tracking controller decreases the disturbance in the course of tracking control and enhances the real-time control characteristics. The simulation result indicated that the wheeled mobile robot tracking can be effectively controlled.
基金supported by National Basic Research and Development Program of China (973 Program, Grant No. 2006CB705402)
文摘In order to solve the problem of trajectory tracking for a class of novel serial-parallel hybrid humanoid arm（HHA）, which has parameters uncertainty, frictions, disturbance, abrasion and pulse forces derived from motors, a multistep dynamics modeling strategy is proposed and a robust controller based on neural network（NN）-adaptive algorithm is designed. At the first step of dynamics modeling, the dynamics model of the reduced HHA is established by Lagrange method. At the second step of dynamics modeling, the parameter uncertain part resulting mainly from the idealization of the HHA is learned by adaptive algorithm. In the trajectory tracking controller, the radial basis function（RBF） NN, whose optimal weights are learned online by adaptive algorithm, is used to learn the upper limit function of the total uncertainties including frictions, disturbances, abrasion and pulse forces. To a great extent, the conservatism of this robust trajectory tracking controller is reduced, and by this controller the HHA can impersonate mostly human actions. The proof and simulation results testify the validity of the adaptive strategy for parameter learning and the neural network-adaptive strategy for the trajectory tracking control.
基金Foundation items:National Science and Technology Major Project(No.2011ZX05021-001)China Postdoctoral Science Foundation(No.2019M663865)。
文摘This paper presents a two-wheeled differential spherical mobile robot in view of the problems that the motion of spherical robot is difficult to control and the sensor is limited by the spherical shell.The robot is simple in structure,flexible in motion and easy to control.The kinematics and dynamics model of spherical mobile robot is established according to the structure of spherical mobile robot.On the basis of the adaptive neural sliding mode control,the trajectory tracking controller of the system is designed.During the simulation of the s-trajectory and circular trajectory tracking control of the spherical mobile robot,it is concluded that the spherical mobile robot is flexible in motion and easy to control.In addition,the simulation results show that the adaptive neural sliding mode control can effectively track the trajectory of the spherical robot.The adaptive control eliminates the influence of unknown parameters and disturbances,and avoids the jitter of left and right wheels during the torque output.
基金support of the National Natural Science Foundation of China(No.12032012)the Priority Academic Program Development of Jiangsu Higher Education Institutions,China。
文摘To achieve high-precision trajectory following during helicopter maneuver tasks and reduce the disruptive influences of unknown variabilities,this study introduces a cascaded-loop helicopter trajectory tracking controller,whose parameters are set using an Ant Colony OptimizationSlime Mould Algorithm(ACO-SMA).Initially,a nonlinear flight dynamics model of the helicopter is constructed.Observer gain functions and nonlinear feedback from a vibrational suppression function to improve the tracking performance of the controller,addressing issues in disturbance estimation and compensation of the Active Disturbance Rejection Control(ADRC).Simultaneously,a cascaded loop system,comprising an internal attitude loop and an external position loop,is created,and the ant colony-slime mold hybrid algorithm optimizes the system parameters of the trajectory tracking controller.Finally,helicopter trajectory tracking simulation experiments are conducted,including spiral ascending and“8”shape climbing maneuvers.The findings indicate that the ADRC employed for helicopter trajectory tracking exhibits outstanding performance in rejecting disturbances caused by gusts and accurately tracking trajectories.The trajectory tracking controller,whose parameters are optimized by the ACO-SMA,shows higher tracking precision compared to the conventional PID and ADRC,thereby substantially improving the precision of maneuver tasks.
基金supported by National Natural Science Foundation of China(No.60974139)Fundamental Research Funds for the Central Universities(No.72103676)
文摘In this paper, an iterative learning control strategy is presented for a class of nonlinear time-varying systems, the timevarying parameters are expanded into Fourier series with bounded remainder term. The backstepping design technique is used to deal with system dynamics with non-global Lipschitz nonlinearities and the approach proposed in this paper solves the non-uniform trajectory tracking problem. Based on the Lyapunov-like synthesis, the proposed method shows that all signals in the closed-loop system remain bounded over a pre-specified time interval [0, T ]. And perfect non-uniform trajectory tracking of the system output is completed. A typical series is introduced in order to deal with the unknown bound of remainder term. Finally, a simulation example shows the feasibility and effectiveness of the approach.
基金supported in part by the National Natural Science Foundation of China under Grant Nos.62273297,62103353,61825304,and 6182500417in part by the Innovative Research Groups of the Natural Science Foundation of Hebei Province under Grant No.E2020203174+2 种基金in part by Hebei Innovation Capability Improvement Plan Project under Grant No.22567619Hin part by Youth Top Talent Project of Hebei Province under Grant No.HY2024050021in part by Post-graduate Innovation Fund Project of Hebei Province under Grant No.CXZZSS2023042。
文摘This paper focuses on the trajectory tracking control problem of unmanned underwater vehicles(UUVs)with unknown dead-zone inputs.The primary objective is to design an adaptive trajectory tracking error constraint controller using the fully actuated systems(FAs)approach to enable UUVs to asymptotically track target signals.Firstly,a novel error constraint fully actuated systems(ECFAs)approach is proposed by incorporating the tracking error dependent normalized function and barrier function along with time-varying scaling.Secondly,in order to deal with the model uncertainties of the UUVs,adaptive radial basis function neural networks(RBFNNs)is combined with the ECFAs approach.Then,a positive time-varying integral function is introduced to completely eliminate the effect of the residual effect caused by unknown dead-zone inputs,and it is proved that the trajectory tracking error converges to zero asymptotically based on the Lyapunov functions.Finally,the simulation results demonstrate the effectiveness of the designed adaptive controller.
基金supported in part by the National Key R&D Program of China under Grant 2021YFB2011300the National Natural Science Foundation of China under Grant 52075262。
文摘This paper mainly focuses on the development of a learning-based controller for a class of uncertain mechanical systems modeled by the Euler-Lagrange formulation.The considered system can depict the behavior of a large class of engineering systems,such as vehicular systems,robot manipulators and satellites.All these systems are often characterized by highly nonlinear characteristics,heavy modeling uncertainties and unknown perturbations,therefore,accurate-model-based nonlinear control approaches become unavailable.Motivated by the challenge,a reinforcement learning(RL)adaptive control methodology based on the actor-critic framework is investigated to compensate the uncertain mechanical dynamics.The approximation inaccuracies caused by RL and the exogenous unknown disturbances are circumvented via a continuous robust integral of the sign of the error(RISE)control approach.Different from a classical RISE control law,a tanh(·)function is utilized instead of a sign(·)function to acquire a more smooth control signal.The developed controller requires very little prior knowledge of the dynamic model,is robust to unknown dynamics and exogenous disturbances,and can achieve asymptotic output tracking.Eventually,co-simulations through ADAMS and MATLAB/Simulink on a three degrees-of-freedom(3-DOF)manipulator and experiments on a real-time electromechanical servo system are performed to verify the performance of the proposed approach.
文摘In this paper, the problem of adaptive tracking control for a class of nonlinear large scale systems with unknown parameters entering linearly is discussed. Based on the theory of input output linearization of nonlinear systems, direct adaptive control schemes are presented to achieve bounded tracking. The proposed control schemes are robust with respect to the uncertainties in interconnection structure as well as subsystem dynamics. A numerical example is given to illustrate the efficiency of this method.
基金Project(61273138)supported by the National Natural Science Foundation of ChinaProject(14JCZDJC39300)supported by the Key Fund of Tianjin,China
文摘One of the primary difficulties in using powered parafoil(PPF) systems is the lack of effective trajectory tracking controllers since the trajectory tracking control is the essential operation for PPF to accomplish autonomous tasks. The characteristic model(CM) based all-coefficient adaptive control(ACAC) designed for PPF systems in horizontal and vertical trajectory control is proposed. The method is easy to use and convenient to adjust and test. Just a few parameters are adapted during the control process. In application, vertical and horizontal CMs are designed and ACAC controllers are constructed to control vertical altitude and horizontal trajectory of PPF based on the proposed CMs, respectively. Result analysis of different simulations shows that the applied ACAC control method is effective for trajectory tracking of the PPF systems and the approach guarantees the transient performance of the PPF systems with better disturbance rejection ability.
基金This work was supported in part by the National Natural Science Foundation of China(61873151,62073201)in part by the Shandong Provincial Natural Science Foundation of China(ZR2019MF009)+2 种基金the Taishan Scholar Project of Shandong Province of China(tsqn201909078)the Major Scientific and Technological Innovation Project of Shandong Province,China(2019JAZZ020812)in part by the Major Program of Shandong Province Natural Science Foundation,China(ZR2018ZB0419).
文摘An adaptive decentralized asymptotic tracking control scheme is developed in this paper for a class of large-scale nonlinear systems with unknown strong interconnections,unknown time-varying parameters,and disturbances.First,by employing the intrinsic properties of Gaussian functions for the interconnection terms for the first time,all extra signals in the framework of decentralized control are filtered out,thereby removing all additional assumptions imposed on the interconnec-tions,such as upper bounding functions and matching conditions.Second,by introducing two integral bounded functions,asymptotic tracking control is realized.Moreover,the nonlinear filters with the compensation terms are introduced to circumvent the issue of“explosion of complexity”.It is shown that all the closed-loop signals are bounded and the tracking errors converge to zero asymptotically.In the end,a simulation example is carried out to demonstrate the effectiveness of the proposed approach.
基金Supported by the National Natural Science Foundation of China （No. 61075065,60774045, U1134108） and the Ph. D Programs Foundation of Ministry of Education of China （ No. 20110162110041 ）.
文摘This paper discusses consensus problems for high-dimensional networked multi-agent systems with fixed topology. The communication topology of multi-agent systems is represented by a digraph. A new consensus protocol is proposed, and consensus convergence of multigent systems is analyzed based on the Lyapunov stability theory. The consensus problem can be formulated into solving a feasible problem with bilinear matrix inequality （BMI） constrains. Furthermore, the consensus protocol is extended to achieving tracking and formation control. By introducing the formation structure set, each agent can gain its individual desired trajectory. Finally, numerical simulations are provided to show the effectiveness of our strategies. The results show that agents from arbitrary initial states can asymptotically reach a consensus. In addition, agents with high-dimensional can track any target trajectory, and maintain desired formation during movement by selecting appropriate structure set.
基金supported in part by the National Natural Science Foundation of China(U1804147,61833001,61873139,61573129)the Innovative Scientists and Technicians Team of Henan Polytechnic University(T2019-2)the Innovative Scientists and Technicians Team of Henan Provincial High Education(20IRTSTHN019)。
文摘In this paper,an asymmetric bipartite consensus problem for the nonlinear multi-agent systems with cooperative and antagonistic interactions is studied under the event-triggered mechanism.For the agents described by a structurally balanced signed digraph,the asymmetric bipartite consensus objective is firstly defined,assigning the agents'output to different signs and module values.Considering with the completely unknown dynamics of the agents,a novel event-triggered model-free adaptive bipartite control protocol is designed based on the agents'triggered outputs and an equivalent compact form data model.By utilizing the Lyapunov analysis method,the threshold of the triggering condition is obtained.Subsequently,the asymptotic convergence of the tracking error is deduced and a sufficient condition is obtained based on the contraction mapping principle.Finally,the simulation example further demonstrates the effectiveness of the protocol.
基金supported by the National Natural Science Foundation of China(61873012)。
文摘This paper proposes an L_(1)adaptive fault tolerant control method for trajectory tracking of tail-sitter aircraft in the state of motor loss fault.The tail-sitter model considers the uncertainties produced by the features of nonlinearities and couplings which cause difficulties in control.An L_(1)adaptive controller is designed to reduce the position and attitude error when actuators have faults.A reference trajectory containing large maneuver flight transitions is designed,which makes it even harder for the L_(1)controller to track accurately.Compensators are designed to assist L_(1)adaptive controller tracking of the reference trajectory.The stability of the L_(1)adaptive controller including compensators is proved.Finally,the simulation results are used to analyse the effectiveness of the proposed controller.Compared to the H∞controller,the L_(1)adaptive controller with compensators has better performance in position control and attitude control under fault tolerance state even when the aircraft conducts large maneuver.Besides,as the L_(1)adaptive control method separates feedback control and adaptive law design,the response speed of the whole system is improved.
文摘In order to solve the problems of dynamic modeling and complicated parameters identification of trajectory tracking control of the quadrotor,a data driven model-free adaptive control method based on the improved sliding mode control(ISMC)algorithm is designed,which does not depend on the precise dynamic model of the quadrotor.The design of the general sliding mode control(SMC)algorithm depends on the mathematical model of the quadrotor and has chattering problems.In this paper,according to the dynamic characteristics of the quadrotor,an adaptive update law is introduced and a saturation function is used to improve the SMC.The proposed control strategy has an inner and an outer loop control structures.The outer loop position control provides the required reference attitude angle for the inner loop.The inner loop attitude control ensures rapid convergence of the attitude angle.The effectiveness and feasibility of the algorithm are verified by mathematical simulation.The mathematical simulation results show that the designed model-free adaptive control method of the quadrotor is effective,and it can effectively realize the trajectory tracking control of the quadrotor.The design of the controller does not depend on the kinematic and dynamic models of the unmanned aerial vehicle(UAV),and has high control accuracy,stability,and robustness.
