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Science China(Technological Sciences) 2024年第6期67卷 1893-1906页

作者： AN Kai WANG ZhenGuo HUANG Wei Hypersonic Technology Laboratory National University of Defense TechnologyChangsha410073China

We propose an adaptive learning-based optimal control scheme for height-velocity control models considering model uncertainties and external disturbances of hypersonic winged-cone *** longitudinal nonlinear model is first established and transformed into the control-oriented error equations,and the control scheme is organized by a steady-compensation *** overcome and eliminate the impact of model uncertainties and external disturbances,an adaptive radial basis function neural network(RBFNN)is designed by a q-gradient *** the height-velocity error system with estimated uncertainties into account,the adaptive learning-based optimal tracking control(ALOTC)scheme is proposed by combining the critic-only adaptive dynamic programming(ADP)framework and parameter optimization of system settling ***,a novel weight update law is proposed to satisfy the online iteration requirements,and the algorithm convergence and closedloop stability are discussed by the Lyapunov ***,four simulation cases are provided to prove the effectiveness,accuracy,and robustness of the proposed scheme for the hypersonic longitudinal control system.

关键词： optimal tracking control adaptive dynamic programming RBFNN hypersonic vehicle

Adaptive Dynamic Programming-Based Attitude optimal tracking control for a Quadrotor with Unmeasured Velocities and Model Uncertainties

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Guidance, Navigation and control 2024年第2期4卷 25-46页

作者： Junrui Guo Xiaoyang Gao Tieshan Li School of Automation Engineering University of Electronic Science and Technology of China Chengdu Sichuan 611731P.R.China

This paper proposes an optimal output feedback tracking control scheme of the quadrotor unmanned aerial vehicle(UAV)attitude system with unmeasured angular velocities and model ***,neural network(NN)is used to approximate the model ***,an NN velocity observer is established to estimate the unmeasured angular ***,a quadrotor output feedback attitude optimal tracking controller is designed,which consists of an adaptive controller designed by backstepping method and an optimal compensation term designed by adaptive dynamic *** signals in the closed-loop system are proved to be ***,numerical simulation example shows that the quadrotor attitude tracking scheme is effective and feasible.

关键词： Quadrotor optimal tracking control neural network velocity observer model uncertainties adaptive dynamic programming

optimal tracking control for linear time-delay large-scale systems with persistent disturbances

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Journal of Systems Engineering and Electronics 2009年第5期20卷 1058-1064页

作者： Tang Ruichun Ma Huamin Guo Shuangle Ren Lijie Coll. of Information Science and Engineering Ocean Univ. of China Qingdao 266100 P. R. China Huawei Technologies Co. Ltd Shenzhen 518129 P. R. China Coll. of Mathematics and Computer Science Hengshui Univ. Hengshui 053000 P. R. China

An optimal tracking control （OTC） problem for linear time-delay large-scale systems affected by external persistent disturbances is investigated. Based on the internal model principle, a disturbance compensator is constructed. The system with persistent disturbances is transformed into an augmented system without persistent disturbances. The original OTC problem of linear time-delay system is transformed into a sequence of linear two- point boundary value （TPBV） problems by introducing a sensitivity parameter and expanding Maclaurin series around it. By solving an OTC law of the augmented system, the OTC law of the original system is obtained. A numerical simulation is provided to illustrate the effectiveness of the proposed method.

关键词： optimal tracking control sensitivity approach time-delay large-scale system persistent disturbance,

optimal tracking control for nonlinear large-scale systems with persistent disturbances

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控制理论与应用（英文版） 2010年第4期8卷 515-520页

作者： Ruichun TANG Xianmin LU Yili ZHAI Cunqun GONG College of Information Science and Engineering Ocean University of China Qingdao Shandong 266100 China Hisense TransTech Co. Ltd. Qingdao Shandong 266101 China Qing Dao Haier Electronic Ltd. Qingdao Shandong 266101 China

This paper studies the optimal control with zero steady-state error problem for nonlinear large-scale systems affected by external persistent *** nonlinear large-scale system is transformed into N nonlinear subsystems with interconnect *** on the internal model principle,a disturbance compensator is constructed such that the ith subsystem with external persistent disturbances is transformed into an augmented subsystem without *** to the sensitivity approach,the optimal tracking control law for the ith nonlinear subsystem can be *** optimal tracking control law for the nonlinear large-scale systems can be obtained.A numerical simulation shows that the method is effective.

关键词： Nonlinear systems Large-scale systems Persistent disturbances optimal tracking control Sensitivity approach

optimal tracking control for automatic transmission shift process

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Journal of Beijing Institute of Technology 2015年第4期24卷 458-465页

作者：万国强李克强裴玲黄英张付军 State Key Laboratory of Automotive Safety and Energy Tsinghua University Laboratory for Integrated Power System Technology Beijing Institute of Technology

In order to improve the shift quality, a linear quadratic optimal tracking control algorithm for automatic transmission shift process is proposed. The dynamic equations of the shift process are derived using a Lagrange method. And a powertrain model is built in the Matlab/Simulink and veri- fied by the measurements. Considering the shift jerk and friction loss during the shift process, the tracking trajectories of the turbine speed and output shaft speed are defined. Furthermore, the linear quadratic optimal tracking control performance index is proposed. Based on the Pontryagin＇ s mini- mum principle, the optimal control law of the shift process is presented. Finally, the simulation study of the 1 - 2 upshift process under different load conditions is carried out with the powertrain model. The simulation results demonstrate that the shift jerk and friction loss can be significantly re- duced by applying the proposed optimal tracking control method.

关键词： powertrain automatic transmission shift process optimal tracking control

optimal tracking control for Reconfigurable Manipulators Based on Critic-only Policy Iteration Algorithm

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Optimal Tracking Control for Reconfigurable Manipulators Bas...

Off-policy integral reinforcement learning optimal tracking control for continuous-time chaotic systems

第36届中国控制会议

作者： Hongbing Xia Bo Zhao Yuanchun Li Department of control Science and Engineering Changchun University of Technology The State Key Laboratory of Management and control for Complex Systems Institute of AutomationChinese Academy of Sciences

ISBN: (纸本)9781538629185

This paper tackles the optimal tracking control problem for reconfigurable manipulators based on critic-only policy iteration（Co PI） algorithm. By system transformation, the optimal tracking control problem is transformed into an optimal regulation problem. The optimal tracking controller is composed of the desired controller and the approximate optimal feedback one. The desired controller is developed to maintain the desired tracking performance at the steady-state, while the approximate optimal feedback controller is designed to stabilize the tracking error dynamics in an optimal manner. Then, a critic neural network is used to estimate the optimal performance index function, and the optimal feedback control is obtained by the Co PI algorithm. The convergence of the proposed method is analyzed and it is shown that the closed-loop system based on Co PI is uniformly ultimately bounded by using the Lyapunov approach. Finally, simulation studies are given to show the effectiveness of the developed method.

关键词： Adaptive dynamic programming Reconfigurable manipulators optimal tracking control Policy iteration Neural networks

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Chinese Physics B 2015年第9期24卷 147-152页

作者：魏庆来宋睿卓孙秋野肖文栋 The State Key Laboratory of Management and control for Complex Systems Institute of AutomationChinese Academy of Sciences School of Automation and Electrical Engineering University of Science and TechnologyBeijing School of Information Science and Engineering Northeastern University

This paper estimates an off-policy integral reinforcement learning（IRL） algorithm to obtain the optimal tracking control of unknown chaotic systems. Off-policy IRL can learn the solution of the HJB equation from the system data generated by an arbitrary control. Moreover, off-policy IRL can be regarded as a direct learning method, which avoids the identification of system dynamics. In this paper, the performance index function is first given based on the system tracking error and control error. For solving the Hamilton–Jacobi–Bellman（HJB） equation, an off-policy IRL algorithm is *** is proven that the iterative control makes the tracking error system asymptotically stable, and the iterative performance index function is convergent. Simulation study demonstrates the effectiveness of the developed tracking control method.

关键词： adaptive dynamic programming approximate dynamic programming chaotic system optimal tracking control

Approximation-error-ADP-based optimal tracking control for chaotic systems with convergence proof

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Chinese Physics B 2013年第9期22卷 305-311页

作者：宋睿卓肖文栋孙长银魏庆来 School of Automation and Electrical Engineering University of Science and Technology Beijing The State Key Laboratory of Management and control for Complex Systems Institute of AutomationChinese Academy of Sciences

In this paper, an optimal tracking control scheme is proposed for a class of discrete-time chaotic systems using the approximation-error-based adaptive dynamic programming （ADP） algorithm. Via the system transformation, the optimal tracking problem is transformed into an optimal regulation problem, and then the novel optimal tracking control method is proposed. It is shown that for the iterative ADP algorithm with finite approximation error, the iterative performance index functions can converge to a finite neighborhood of the greatest lower bound of all performance index functions under some convergence conditions. Two examples are given to demonstrate the validity of the proposed optimal tracking control scheme for chaotic systems.

关键词： chaotic systems approximation error adaptive dynamic programming optimal tracking control

Neural-network-based stochastic linear quadratic optimal tracking control scheme for unknown discrete-time systems using adaptive dynamic programming

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control Theory and Technology 2021年第3期19卷 315-327页

作者： Xin Chen Fang Wang School of Automation China University of GeosciencesWuhan430074HubeiChina Hubei Key Laboratory of Advanced control and Intelligent Automation for Complex Systems Wuhan430074HubeiChina

In this paper,a stochastic linear quadratic optimal tracking scheme is proposed for unknown linear discrete-time(DT)systems based on adaptive dynamic programming(ADP)***,an augmented system composed of the original system and the command generator is constructed and then an augmented stochastic algebraic equation is derived based on the augmented ***,to obtain the optimal control strategy,the stochastic case is converted into the deterministic one by system transformation,and then an ADP algorithm is proposed with convergence *** the purpose of realizing the ADP algorithm,three back propagation neural networks including model network,critic network and action network are devised to guarantee unknown system model,optimal value function and optimal control strategy,***,the obtained optimal control strategy is applied to the original stochastic system,and two simulations are provided to demonstrate the effectiveness of the proposed algorithm.

关键词： Stochastic system optimal tracking control Adaptive dynamic programming Neural networks

Adaptive optimal tracking control for Continuous-Time Systems Using Identifier-Critic Based Dynamic Programming

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Adaptive Optimal Tracking Control for Continuous-Time System...