This paper deals with a nonlinear control strategy of induction motor that combines an input-output linearization control technique and a nonlinear observer design. It is well known that induction motors are the most ...This paper deals with a nonlinear control strategy of induction motor that combines an input-output linearization control technique and a nonlinear observer design. It is well known that induction motors are the most widely used motors in electrical appliances, industrial control and automation. However, it is also known that induction motor control is a complex task that is due to its nonlinear characteristics. Two main features of the proposed approach are worth to be mentioned. Firstly, a nonlinear control is carried out using a nonlinear feedback linearization technique involving non available state variable measurements of the induction motor system. Secondly, a nonlinear observer is designed to estimate these pertinent but unmeasurable state variables of the machine. The circle-criterion approach is performed to compute the observer gain matrices as a solution of LMI （linear matrix inequalities） that ensure the stability conditions, in the sense of Lyapunov, of the estimated state error dynamics of the designed observer. Simulation results are presented to validate the effectiveness of the proposed approach.展开更多
Cable robots are structurally the same as parallel robots but with the basic difference that cables can only pull the platform and cannot push it. This feature makes control of cable robots a lot more challenging comp...Cable robots are structurally the same as parallel robots but with the basic difference that cables can only pull the platform and cannot push it. This feature makes control of cable robots a lot more challenging compared to parallel robots. This paper introduces a controller for cable robots under force constraint. The controller is based on input-output linearization and linear model predictive control. Performance of input-output linearizing (IOL) controllers suffers due to constraints on input and output variables. This problem is successfully tackled by augmenting IOL controllers with linear model predictive controller (LMPC). The effecttiveness of the proposed method is illustrated by numerical simulation.展开更多
In this paper, the nonlinear control of chaotic oscillations was investigated by using the input output linearization control method. The chaotic attitude of a kind of spacecraft was discussed. It is demonstrated that...In this paper, the nonlinear control of chaotic oscillations was investigated by using the input output linearization control method. The chaotic attitude of a kind of spacecraft was discussed. It is demonstrated that the input output linearization control law is the nonlinear version of the parametric open plus closed loop control law.展开更多
Piezoelectric stages use piezoelectric actuators and flexure hinges as driving and amplifying mechanisms,respectively.These systems have high positioning accuracy and high-frequency responses,and they are widely used ...Piezoelectric stages use piezoelectric actuators and flexure hinges as driving and amplifying mechanisms,respectively.These systems have high positioning accuracy and high-frequency responses,and they are widely used in various precision/ultra-precision positioning fields.However,the main challenge with these devices is the inherent hysteresis nonlinearity of piezoelectric actuators,which seriously affects the tracking accuracy of a piezoelectric stage.Inspired by this challenge,in this work,we developed a Hammerstein model to describe the hysteresis nonlinearity of a piezoelectric stage.In particular,in our proposed scheme,a feedback-linearization algorithm is used to eliminate the static hysteresis nonlinearity.In addition,a composite controller based on equivalent-disturbance compensation was designed to counteract model uncertainties and external disturbances.An analysis of the stability of a closed-loop system based on this feedback-linearization algorithm and composite controller was performed,and this was followed by extensive comparative experiments using a piezoelectric stage developed in the laboratory.The experimental results confirmed that the feedback-linearization algorithm and the composite controller offer improved linearization and trajectory-tracking performance.展开更多
An efficient approach is proposed for the equivalent linearization of frame structures with plastic hinges under nonstationary seismic excitations.The concentrated plastic hinges,described by the Bouc-Wen model,are as...An efficient approach is proposed for the equivalent linearization of frame structures with plastic hinges under nonstationary seismic excitations.The concentrated plastic hinges,described by the Bouc-Wen model,are assumed to occur at the two ends of a linear-elastic beam element.The auxiliary differential equations governing the plastic rotational displacements and their corresponding hysteretic displacements are replaced with linearized differential equations.Then,the two sets of equations of motion for the original nonlinear system can be reduced to an expanded-order equivalent linearized equation of motion for equivalent linear systems.To solve the equation of motion for equivalent linear systems,the nonstationary random vibration analysis is carried out based on the explicit time-domain method with high efficiency.Finally,the proposed treatment method for initial values of equivalent parameters is investigated in conjunction with parallel computing technology,which provides a new way of obtaining the equivalent linear systems at different time instants.Based on the explicit time-domain method,the key responses of interest of the converged equivalent linear system can be calculated through dimension reduction analysis with high efficiency.Numerical examples indicate that the proposed approach has high computational efficiency,and shows good applicability to weak nonlinear and medium-intensity nonlinear systems.展开更多
We show that an intrinsically nonlinear oscillator can always be transformed into a linear or harmonic oscillator by addition of a constant force, which shifts the equilibrium position of the oscillator.
We consider the partially linear multiplicative model with monotonic constraint for the analysis of positive response data. We propose a constrained least product relative error (LPRE) estimation procedure for the mod...We consider the partially linear multiplicative model with monotonic constraint for the analysis of positive response data. We propose a constrained least product relative error (LPRE) estimation procedure for the model by means of B-spline basis expansion. We have also established asymptotic properties of the proposed estimators under regularity conditions. We finally provide numerical simulations and a real data application to assess the finite sample performance of the developed methodology.展开更多
In this paper,we introduce TianXing,a transformer-based data-driven model designed with physical augmentation for skillful and efficient global weather forecasting.Previous data-driven transformer models such as Pangu...In this paper,we introduce TianXing,a transformer-based data-driven model designed with physical augmentation for skillful and efficient global weather forecasting.Previous data-driven transformer models such as Pangu-Weather,FengWu,and FuXi have emerged as promising alternatives for numerical weather prediction in weather forecasting.However,these models have been characterized by their substantial computational resource consumption during training and limited incorporation of explicit physical guidance in their modeling frameworks.In contrast,TianXing applies a linear complexity mechanism that ensures proportional scalability with input data size while significantly diminishing GPU resource demands,with only a marginal compromise in accuracy.Furthermore,TianXing proposes an explicit attention decay mechanism in the linear attention derived from physical insights to enhance its forecasting skill.The mechanism can reweight attention based on Earth's spherical distances and learned sparse multivariate coupling relationships,promptingTianXing to prioritize dynamically relevant neighboring features.Finally,to enhance its performance in mediumrange forecasting,TianXing employs a stacked autoregressive forecast algorithm.Validation of the model's architecture is conducted using ERA5 reanalysis data at a 5.625°latitude-longitude resolution,while a high-resolution dataset at 0.25°is utilized for training the actual forecasting model.Notably,the TianXing exhibits excellent performance,particularly in the Z500(geopotential height)and T850(temperature)fields,surpassing previous data-driven models and operational fullresolution models such as NCEP GFS and ECMWF IFS,as evidenced by latitude-weighted RMSE and ACC metrics.Moreover,the TianXing has demonstrated remarkable capabilities in predicting extreme weather events,such as typhoons.展开更多
Ammonium level in body fluids serves as one of the critical biomarkers for healthcare,especially those relative to liver diseases.The continuous and real-time monitoring in both invasive and noninvasive manners is hig...Ammonium level in body fluids serves as one of the critical biomarkers for healthcare,especially those relative to liver diseases.The continuous and real-time monitoring in both invasive and noninvasive manners is highly desired,while the ammonium concentrations vary largely in different body fluids.Besides,the sensing reliability based on ion-selective biosensors can be significantly interfered by potassium ions.To tackle these challenges,a flexible and biocompatible sensing patch for wireless ammonium level sensing was reported with an ultrawide linear range for universal body fluids including blood,tears,saliva,sweat and urine.The as-prepared biocompatible sensors deliver a reliable sensitivity of 58.7 mV decade-1 in the range of 1-100 mM and a desirable selectivity coefficient of 0.11 in the interference of potassium ions,attributed to the cross-calibration within the sensors array.The sensor’s biocompatibility was validated by the cell growth on the sensor surface(>80%),hemolysis rates(<5%),negligible cellular inflammatory responses and weight changes of the mice with implanted sensors.Such biocompatible sensors with ultrawide linear range and desirable selectivity open up new possibility of highly compatible biomarker analysis via different body fluids in versatile approaches.展开更多
This study develops a signal-based trading strategy for the SPDR S&P 500 ETF Trust(SPY)using a multiple linear regression framework to analyze interrelationships between SPY and global equity indices across U.S.,E...This study develops a signal-based trading strategy for the SPDR S&P 500 ETF Trust(SPY)using a multiple linear regression framework to analyze interrelationships between SPY and global equity indices across U.S.,European,Asian,and Australian markets.By synthesizing historical pricing data from these major benchmarks,the model generates systematic trading signals through predicted price trajectories.In controlled training scenarios,the strategy achieved superior risk-adjusted returns compared to passive buy-and-hold approaches,demonstrating the value of cross-market signal integration.While the framework shows promise for algorithmic trading systems,the study acknowledges limitations in generalizing historical patterns to evolving market conditions.The findings highlight opportunities to enhance predictive accuracy through machine learning architectures capable of processing nonlinear market dynamics.These insights advance quantitative trading research by establishing methodologies for cross-market signal synthesis and proposing pathways to develop adaptive models for volatile capital markets.展开更多
Due to the heterogeneity of rock masses and the variability of in situ stress,the traditional linear inversion method is insufficiently accurate to achieve high accuracy of the in situ stress field.To address this cha...Due to the heterogeneity of rock masses and the variability of in situ stress,the traditional linear inversion method is insufficiently accurate to achieve high accuracy of the in situ stress field.To address this challenge,nonlinear stress boundaries for a numerical model are determined through regression analysis of a series of nonlinear coefficient matrices,which are derived from the bubbling method.Considering the randomness and flexibility of the bubbling method,a parametric study is conducted to determine recommended ranges for these parameters,including the standard deviation(σb)of bubble radii,the non-uniform coefficient matrix number(λ)for nonlinear stress boundaries,and the number(m)and positions of in situ stress measurement points.A model case study provides a reference for the selection of these parameters.Additionally,when the nonlinear in situ stress inversion method is employed,stress distortion inevitably occurs near model boundaries,aligning with the Saint Venant's principle.Two strategies are proposed accordingly:employing a systematic reduction of nonlinear coefficients to achieve high inversion accuracy while minimizing significant stress distortion,and excluding regions with severe stress distortion near the model edges while utilizing the central part of the model for subsequent simulations.These two strategies have been successfully implemented in the nonlinear in situ stress inversion of the Xincheng Gold Mine and have achieved higher inversion accuracy than the linear method.Specifically,the linear and nonlinear inversion methods yield root mean square errors(RMSE)of 4.15 and 3.2,and inversion relative errors(δAve)of 22.08%and 17.55%,respectively.Therefore,the nonlinear inversion method outperforms the traditional multiple linear regression method,even in the presence of a systematic reduction in the nonlinear stress boundaries.展开更多
Aim To present a simple and effective method for the design of nonlinear and time varying control system. Methods A new concept of dynamic equilibrium of a system and its stability were presented first. It was poin...Aim To present a simple and effective method for the design of nonlinear and time varying control system. Methods A new concept of dynamic equilibrium of a system and its stability were presented first. It was pointed out that what is controlled directly by the input of a control system is the system's dynamic equilibrium rather than the states. Based on it, a new feedback linearization method for nonlinear system based on the Lyapunov direct method was given. Simulation studies were also carried out. Results The example and simulation show that by use of the method, the controller design becomes very simple and the control effect is quite satisfying. Conclusion The new method unifies the stabilizing problem(regulating problem) with the tracking problem. It is a very simple and effective method for the design of nonlinear and time varying control system.展开更多
A class of nonlinear and continuous type Leontief model and its corresponding conditional input-output equation are introduced, and two basic problems under the so called positive or negative boundary assumption are p...A class of nonlinear and continuous type Leontief model and its corresponding conditional input-output equation are introduced, and two basic problems under the so called positive or negative boundary assumption are presented. By approaches of nonlinear analysis some solvability results of this equation and continuous perturbation properties of the relative solution sets are obtained, and some economic significance are illustrated by the remark.展开更多
In order to design a nonlinear controller for small-scale autonomous helicopters, the dynamic characteristics of a model helicopter are investigated, and an integrated nonlinear model of a small-scale helicopter for h...In order to design a nonlinear controller for small-scale autonomous helicopters, the dynamic characteristics of a model helicopter are investigated, and an integrated nonlinear model of a small-scale helicopter for hovering control is presented. It is proved that the nonlinear system of the small-scale helicopter can be transformed to a linear system using the dynamic feedback linearization technique. Finally, simulations are carried out to validate the nonlinear controller.展开更多
This paper is focused on developing a tracking controller for a hypersonic cruise vehicle using tangent linearization approach.The design of flight control systems for air-breathing hypersonic vehicles is a highly cha...This paper is focused on developing a tracking controller for a hypersonic cruise vehicle using tangent linearization approach.The design of flight control systems for air-breathing hypersonic vehicles is a highly challenging task due to the unique characteristics of the vehicle dynamics.Motivated by recent results on tangent linearization control,the tracking control problem for the hypersonic cruise vehicle is reduced to that of a feedback stabilizing controller design for a linear time-varying system which can be accomplished by a standard design method of frozen-time control.Through a proper model transformation,it can be proven that the tracking error of the designed closed-loop system decays exponentially.Simulation studies are conducted for trimmed cruise conditions of 110000 ft and Mach 15 where the responses of the vehicle to step changes in altitude and velocity are evaluated.The effectiveness of the controller is demonstrated by simulation results.展开更多
The impact angle control over guidance(IACG) law against stationary targets is proposed by using feedback linearization control(FLC) and finite time control(FTC). First, this paper transforms the kinematics equation o...The impact angle control over guidance(IACG) law against stationary targets is proposed by using feedback linearization control(FLC) and finite time control(FTC). First, this paper transforms the kinematics equation of guidance systems into the feedbackable linearization model, in which the guidance law is obtained without considering the impact angle via FLC. For the purpose of the line of sight(LOS) angle and its rate converging to the desired values, the second-order LOS angle is considered as a double-integral system. Then, this paper utilizes FTC to design a controller which can guarantee the states of the double-integral system converging to the desired values. Numerical simulation illustrates the performance of the IACG, in contrast to the existing guidance law.展开更多
Feedforward multi layer neural networks have very strong mapping capability that is based on the non linearity of the activation function, however, the non linearity of the activation function can cause the multiple ...Feedforward multi layer neural networks have very strong mapping capability that is based on the non linearity of the activation function, however, the non linearity of the activation function can cause the multiple local minima on the learning error surfaces, which affect the learning rate and solving optimal weights. This paper proposes a learning method linearizing non linearity of the activation function and discusses its merits and demerits theoretically.展开更多
An enhanced trajectory linearization control （TLC） structure based on radial basis function neural network （RBFNN） and its application on an aerospace vehicle （ASV） flight control system are presensted. The infl...An enhanced trajectory linearization control （TLC） structure based on radial basis function neural network （RBFNN） and its application on an aerospace vehicle （ASV） flight control system are presensted. The influence of unknown disturbances and uncertainties is reduced by RBFNN thanks to its approaching ability, and a robustifying itera is used to overcome the approximate error of RBFNN. The parameters adaptive adjusting laws are designed on the Lyapunov theory. The uniform ultimate boundedness of all signals of the composite closed-loop system is proved based on Lyapunov theory. Finally, the flight control system of an ASV is designed based on the proposed method. Simulation results demonstrate the effectiveness and robustness of the designed approach.展开更多
A robust adaptive trajectory linearization control （RATLC） algorithm for a class of nonlinear systems with uncertainty and disturbance based on the T-S fuzzy system is presented. The unknown disturbance and uncertai...A robust adaptive trajectory linearization control （RATLC） algorithm for a class of nonlinear systems with uncertainty and disturbance based on the T-S fuzzy system is presented. The unknown disturbance and uncertainty are estimated by the T-S fuzzy system, and a robust adaptive control law is designed by the Lyapunov theory. Irrespective of whether the dimensions of the system and the rules of the fuzzy system are large or small, there is only one parameter adjusting on line. Uniformly ultimately boundedness of all signals of the composite closed-loop system are proved by theory analysis. Finally, a numerical example is studied based on the proposed method. The simulation results demonstrate the effectiveness and robustness of the control scheme.展开更多
In 1960s, Hartman and Grobman pointed out that if all eigenvalues of a matrix A have no zero real part and f(x) is small Lipchitzian, then x′=Ax+f(x) can be locally linearized on a neighborhood of the origin. Later, ...In 1960s, Hartman and Grobman pointed out that if all eigenvalues of a matrix A have no zero real part and f(x) is small Lipchitzian, then x′=Ax+f(x) can be locally linearized on a neighborhood of the origin. Later, the above result was generalized to global under the condition that f(x) is a bounded function. In this paper, we delete the condition that f(x) is a bounded function, and prove that if f(x) has suitable structure, then x′=Ax+f(x) can be linearized.展开更多
文摘This paper deals with a nonlinear control strategy of induction motor that combines an input-output linearization control technique and a nonlinear observer design. It is well known that induction motors are the most widely used motors in electrical appliances, industrial control and automation. However, it is also known that induction motor control is a complex task that is due to its nonlinear characteristics. Two main features of the proposed approach are worth to be mentioned. Firstly, a nonlinear control is carried out using a nonlinear feedback linearization technique involving non available state variable measurements of the induction motor system. Secondly, a nonlinear observer is designed to estimate these pertinent but unmeasurable state variables of the machine. The circle-criterion approach is performed to compute the observer gain matrices as a solution of LMI （linear matrix inequalities） that ensure the stability conditions, in the sense of Lyapunov, of the estimated state error dynamics of the designed observer. Simulation results are presented to validate the effectiveness of the proposed approach.
文摘Cable robots are structurally the same as parallel robots but with the basic difference that cables can only pull the platform and cannot push it. This feature makes control of cable robots a lot more challenging compared to parallel robots. This paper introduces a controller for cable robots under force constraint. The controller is based on input-output linearization and linear model predictive control. Performance of input-output linearizing (IOL) controllers suffers due to constraints on input and output variables. This problem is successfully tackled by augmenting IOL controllers with linear model predictive controller (LMPC). The effecttiveness of the proposed method is illustrated by numerical simulation.
基金Supported by the National Natural Science Foundation of China!( 19782 0 0 3 ) theChina Postdoctoral Science Foundation and
文摘In this paper, the nonlinear control of chaotic oscillations was investigated by using the input output linearization control method. The chaotic attitude of a kind of spacecraft was discussed. It is demonstrated that the input output linearization control law is the nonlinear version of the parametric open plus closed loop control law.
基金supported by the National Key R&D Program of China (Grant No.2022YFB3206700)the Independent Research Project of the State Key Laboratory of Mechanical Transmission (Grant No.SKLMT-ZZKT-2022M06)the Innovation Group Science Fund of Chongqing Natural Science Foundation (Grant No.cstc2019jcyj-cxttX0003).
文摘Piezoelectric stages use piezoelectric actuators and flexure hinges as driving and amplifying mechanisms,respectively.These systems have high positioning accuracy and high-frequency responses,and they are widely used in various precision/ultra-precision positioning fields.However,the main challenge with these devices is the inherent hysteresis nonlinearity of piezoelectric actuators,which seriously affects the tracking accuracy of a piezoelectric stage.Inspired by this challenge,in this work,we developed a Hammerstein model to describe the hysteresis nonlinearity of a piezoelectric stage.In particular,in our proposed scheme,a feedback-linearization algorithm is used to eliminate the static hysteresis nonlinearity.In addition,a composite controller based on equivalent-disturbance compensation was designed to counteract model uncertainties and external disturbances.An analysis of the stability of a closed-loop system based on this feedback-linearization algorithm and composite controller was performed,and this was followed by extensive comparative experiments using a piezoelectric stage developed in the laboratory.The experimental results confirmed that the feedback-linearization algorithm and the composite controller offer improved linearization and trajectory-tracking performance.
基金Fundamental Research Funds for the Central Universities under Grant No.2682022CX072the Research and Development Plan in Key Areas of Guangdong Province under Grant No.2020B0202010008。
文摘An efficient approach is proposed for the equivalent linearization of frame structures with plastic hinges under nonstationary seismic excitations.The concentrated plastic hinges,described by the Bouc-Wen model,are assumed to occur at the two ends of a linear-elastic beam element.The auxiliary differential equations governing the plastic rotational displacements and their corresponding hysteretic displacements are replaced with linearized differential equations.Then,the two sets of equations of motion for the original nonlinear system can be reduced to an expanded-order equivalent linearized equation of motion for equivalent linear systems.To solve the equation of motion for equivalent linear systems,the nonstationary random vibration analysis is carried out based on the explicit time-domain method with high efficiency.Finally,the proposed treatment method for initial values of equivalent parameters is investigated in conjunction with parallel computing technology,which provides a new way of obtaining the equivalent linear systems at different time instants.Based on the explicit time-domain method,the key responses of interest of the converged equivalent linear system can be calculated through dimension reduction analysis with high efficiency.Numerical examples indicate that the proposed approach has high computational efficiency,and shows good applicability to weak nonlinear and medium-intensity nonlinear systems.
文摘We show that an intrinsically nonlinear oscillator can always be transformed into a linear or harmonic oscillator by addition of a constant force, which shifts the equilibrium position of the oscillator.
文摘We consider the partially linear multiplicative model with monotonic constraint for the analysis of positive response data. We propose a constrained least product relative error (LPRE) estimation procedure for the model by means of B-spline basis expansion. We have also established asymptotic properties of the proposed estimators under regularity conditions. We finally provide numerical simulations and a real data application to assess the finite sample performance of the developed methodology.
基金supported in part by the Meteorological Joint Funds of the National Natural Science Foundation of China under Grant U2142211in part by the National Natural Science Foundation of China under Grant 42075141,42341202+2 种基金in part by the National Key Research and Development Program of China under Grant 2020YFA0608000in part by the Shanghai Municipal Science and Technology Major Project(2021SHZDZX0100)the Fundamental Research Funds for the Central Universities。
文摘In this paper,we introduce TianXing,a transformer-based data-driven model designed with physical augmentation for skillful and efficient global weather forecasting.Previous data-driven transformer models such as Pangu-Weather,FengWu,and FuXi have emerged as promising alternatives for numerical weather prediction in weather forecasting.However,these models have been characterized by their substantial computational resource consumption during training and limited incorporation of explicit physical guidance in their modeling frameworks.In contrast,TianXing applies a linear complexity mechanism that ensures proportional scalability with input data size while significantly diminishing GPU resource demands,with only a marginal compromise in accuracy.Furthermore,TianXing proposes an explicit attention decay mechanism in the linear attention derived from physical insights to enhance its forecasting skill.The mechanism can reweight attention based on Earth's spherical distances and learned sparse multivariate coupling relationships,promptingTianXing to prioritize dynamically relevant neighboring features.Finally,to enhance its performance in mediumrange forecasting,TianXing employs a stacked autoregressive forecast algorithm.Validation of the model's architecture is conducted using ERA5 reanalysis data at a 5.625°latitude-longitude resolution,while a high-resolution dataset at 0.25°is utilized for training the actual forecasting model.Notably,the TianXing exhibits excellent performance,particularly in the Z500(geopotential height)and T850(temperature)fields,surpassing previous data-driven models and operational fullresolution models such as NCEP GFS and ECMWF IFS,as evidenced by latitude-weighted RMSE and ACC metrics.Moreover,the TianXing has demonstrated remarkable capabilities in predicting extreme weather events,such as typhoons.
基金supported by the National Natural Science Foundation of China(62201243)Natural Science Foundation of Guangdong Province(2022A1515011928)+2 种基金Shenzhen Science and Technology Program(Grant No.RCYX20231211090432060,JSGGZD20220822095600001)Postgraduate Scientific Research Innovation Project of Hunan Province(CX20231306)the technical support from the Southern University of Science and Technology Core Research Facilities(SUSTech CRF)。
文摘Ammonium level in body fluids serves as one of the critical biomarkers for healthcare,especially those relative to liver diseases.The continuous and real-time monitoring in both invasive and noninvasive manners is highly desired,while the ammonium concentrations vary largely in different body fluids.Besides,the sensing reliability based on ion-selective biosensors can be significantly interfered by potassium ions.To tackle these challenges,a flexible and biocompatible sensing patch for wireless ammonium level sensing was reported with an ultrawide linear range for universal body fluids including blood,tears,saliva,sweat and urine.The as-prepared biocompatible sensors deliver a reliable sensitivity of 58.7 mV decade-1 in the range of 1-100 mM and a desirable selectivity coefficient of 0.11 in the interference of potassium ions,attributed to the cross-calibration within the sensors array.The sensor’s biocompatibility was validated by the cell growth on the sensor surface(>80%),hemolysis rates(<5%),negligible cellular inflammatory responses and weight changes of the mice with implanted sensors.Such biocompatible sensors with ultrawide linear range and desirable selectivity open up new possibility of highly compatible biomarker analysis via different body fluids in versatile approaches.
文摘This study develops a signal-based trading strategy for the SPDR S&P 500 ETF Trust(SPY)using a multiple linear regression framework to analyze interrelationships between SPY and global equity indices across U.S.,European,Asian,and Australian markets.By synthesizing historical pricing data from these major benchmarks,the model generates systematic trading signals through predicted price trajectories.In controlled training scenarios,the strategy achieved superior risk-adjusted returns compared to passive buy-and-hold approaches,demonstrating the value of cross-market signal integration.While the framework shows promise for algorithmic trading systems,the study acknowledges limitations in generalizing historical patterns to evolving market conditions.The findings highlight opportunities to enhance predictive accuracy through machine learning architectures capable of processing nonlinear market dynamics.These insights advance quantitative trading research by establishing methodologies for cross-market signal synthesis and proposing pathways to develop adaptive models for volatile capital markets.
基金funded by the National Key R&D Program of China(Grant No.2022YFC2903904)the National Natural Science Foundation of China(Grant Nos.51904057 and U1906208).
文摘Due to the heterogeneity of rock masses and the variability of in situ stress,the traditional linear inversion method is insufficiently accurate to achieve high accuracy of the in situ stress field.To address this challenge,nonlinear stress boundaries for a numerical model are determined through regression analysis of a series of nonlinear coefficient matrices,which are derived from the bubbling method.Considering the randomness and flexibility of the bubbling method,a parametric study is conducted to determine recommended ranges for these parameters,including the standard deviation(σb)of bubble radii,the non-uniform coefficient matrix number(λ)for nonlinear stress boundaries,and the number(m)and positions of in situ stress measurement points.A model case study provides a reference for the selection of these parameters.Additionally,when the nonlinear in situ stress inversion method is employed,stress distortion inevitably occurs near model boundaries,aligning with the Saint Venant's principle.Two strategies are proposed accordingly:employing a systematic reduction of nonlinear coefficients to achieve high inversion accuracy while minimizing significant stress distortion,and excluding regions with severe stress distortion near the model edges while utilizing the central part of the model for subsequent simulations.These two strategies have been successfully implemented in the nonlinear in situ stress inversion of the Xincheng Gold Mine and have achieved higher inversion accuracy than the linear method.Specifically,the linear and nonlinear inversion methods yield root mean square errors(RMSE)of 4.15 and 3.2,and inversion relative errors(δAve)of 22.08%and 17.55%,respectively.Therefore,the nonlinear inversion method outperforms the traditional multiple linear regression method,even in the presence of a systematic reduction in the nonlinear stress boundaries.
文摘Aim To present a simple and effective method for the design of nonlinear and time varying control system. Methods A new concept of dynamic equilibrium of a system and its stability were presented first. It was pointed out that what is controlled directly by the input of a control system is the system's dynamic equilibrium rather than the states. Based on it, a new feedback linearization method for nonlinear system based on the Lyapunov direct method was given. Simulation studies were also carried out. Results The example and simulation show that by use of the method, the controller design becomes very simple and the control effect is quite satisfying. Conclusion The new method unifies the stabilizing problem(regulating problem) with the tracking problem. It is a very simple and effective method for the design of nonlinear and time varying control system.
文摘A class of nonlinear and continuous type Leontief model and its corresponding conditional input-output equation are introduced, and two basic problems under the so called positive or negative boundary assumption are presented. By approaches of nonlinear analysis some solvability results of this equation and continuous perturbation properties of the relative solution sets are obtained, and some economic significance are illustrated by the remark.
基金supported by the National Natural Science Foundation of China (No.60975023)
文摘In order to design a nonlinear controller for small-scale autonomous helicopters, the dynamic characteristics of a model helicopter are investigated, and an integrated nonlinear model of a small-scale helicopter for hovering control is presented. It is proved that the nonlinear system of the small-scale helicopter can be transformed to a linear system using the dynamic feedback linearization technique. Finally, simulations are carried out to validate the nonlinear controller.
基金supported by the National Natural Science Foundation of China (6071000260904007)+1 种基金the Program for Changjiang Scholars and Innovative Research Team in Universitythe State Key Laboratory of Robotics and System (SKLRS200801AO3)
文摘This paper is focused on developing a tracking controller for a hypersonic cruise vehicle using tangent linearization approach.The design of flight control systems for air-breathing hypersonic vehicles is a highly challenging task due to the unique characteristics of the vehicle dynamics.Motivated by recent results on tangent linearization control,the tracking control problem for the hypersonic cruise vehicle is reduced to that of a feedback stabilizing controller design for a linear time-varying system which can be accomplished by a standard design method of frozen-time control.Through a proper model transformation,it can be proven that the tracking error of the designed closed-loop system decays exponentially.Simulation studies are conducted for trimmed cruise conditions of 110000 ft and Mach 15 where the responses of the vehicle to step changes in altitude and velocity are evaluated.The effectiveness of the controller is demonstrated by simulation results.
基金supported by the National Natural Science Foundation of China(51679201)
文摘The impact angle control over guidance(IACG) law against stationary targets is proposed by using feedback linearization control(FLC) and finite time control(FTC). First, this paper transforms the kinematics equation of guidance systems into the feedbackable linearization model, in which the guidance law is obtained without considering the impact angle via FLC. For the purpose of the line of sight(LOS) angle and its rate converging to the desired values, the second-order LOS angle is considered as a double-integral system. Then, this paper utilizes FTC to design a controller which can guarantee the states of the double-integral system converging to the desired values. Numerical simulation illustrates the performance of the IACG, in contrast to the existing guidance law.
文摘Feedforward multi layer neural networks have very strong mapping capability that is based on the non linearity of the activation function, however, the non linearity of the activation function can cause the multiple local minima on the learning error surfaces, which affect the learning rate and solving optimal weights. This paper proposes a learning method linearizing non linearity of the activation function and discusses its merits and demerits theoretically.
基金the National Natural Science Foundation of China (90405011).
文摘An enhanced trajectory linearization control （TLC） structure based on radial basis function neural network （RBFNN） and its application on an aerospace vehicle （ASV） flight control system are presensted. The influence of unknown disturbances and uncertainties is reduced by RBFNN thanks to its approaching ability, and a robustifying itera is used to overcome the approximate error of RBFNN. The parameters adaptive adjusting laws are designed on the Lyapunov theory. The uniform ultimate boundedness of all signals of the composite closed-loop system is proved based on Lyapunov theory. Finally, the flight control system of an ASV is designed based on the proposed method. Simulation results demonstrate the effectiveness and robustness of the designed approach.
基金the National Natural Science Foundation of China (90716028 and 90405011).
文摘A robust adaptive trajectory linearization control （RATLC） algorithm for a class of nonlinear systems with uncertainty and disturbance based on the T-S fuzzy system is presented. The unknown disturbance and uncertainty are estimated by the T-S fuzzy system, and a robust adaptive control law is designed by the Lyapunov theory. Irrespective of whether the dimensions of the system and the rules of the fuzzy system are large or small, there is only one parameter adjusting on line. Uniformly ultimately boundedness of all signals of the composite closed-loop system are proved by theory analysis. Finally, a numerical example is studied based on the proposed method. The simulation results demonstrate the effectiveness and robustness of the control scheme.
基金NSFC!( 1 9671 0 1 7) and NSF!( A970 1 2 ) of Fujian.
文摘In 1960s, Hartman and Grobman pointed out that if all eigenvalues of a matrix A have no zero real part and f(x) is small Lipchitzian, then x′=Ax+f(x) can be locally linearized on a neighborhood of the origin. Later, the above result was generalized to global under the condition that f(x) is a bounded function. In this paper, we delete the condition that f(x) is a bounded function, and prove that if f(x) has suitable structure, then x′=Ax+f(x) can be linearized.
