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Policy Optimization adaptive dynamic programming for Optimal Control of Input-Affine Discrete-Time Nonlinear Systems

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IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2023年第7期53卷 4339-4350页

作者： Lin, Mingduo Zhao, Bo Beijing Normal Univ Sch Syst Sci Beijing 100875 Peoples R China Chongqing Univ Posts & Telecommun Key Lab Ind Internet Things & Networked Control Minist Educ Chongqing 400065 Peoples R China

In this article, a policy optimization adaptive dynamic programming (POADP) method is developed for optimal control of discrete-time unknown nonlinear systems, where the iterative control policy is parameterized to optimize the iterative Q-function directly. The relaxed condition for the learning rate is given to guarantee the convergence of the present algorithm. Furthermore, the Polyak-Lojasiewicz inequality is introduced to analyze the optimality, i.e., the iterative Q-function converges to the optimum within a given computational threshold under a finite iteration, and the rate of convergence (i.e., the required minimum number of iterations) for the developed POADP method is also illustrated. To ease real implementations, the iterative Q-function and the iterative control policy are approximated by employing an actor-critic structure. Then, an experiment-based method is developed to obtain the initial weights of actor-critic structure. Finally, numerical simulation results of two examples are provided to validate the effectiveness of the POADP algorithm.

关键词： Optimal control Convergence Optimization dynamic programming Nonlinear systems Performance analysis Iterative algorithms adaptive dynamic programming data based optimal control policy optimization (PO) reinforcement learning (RL)

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A brief survey on nonlinear control using adaptive dynamic programming under engineering-oriented complexities

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INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE 2023年第8期54卷 1855-1872页

作者： Zhang, Yuhan Zou, Lei Liu, Yang Ding, Derui Hu, Jun Shandong Univ Sci & Technol Coll Elect Engn & Automat Qingdao Peoples R China Donghua Univ Coll Informat Sci & Technol Shanghai 201620 Peoples R China Minist Educ Engn Res Ctr Digitalized Text & Fash Technol Shanghai 201620 Peoples R China Loughborough Univ Dept Aeronaut & Automot Engn Loughborough England Univ Shanghai Sci & Technol Dept Control Sci & Engn Shanghai Peoples R China Harbin Univ Sci & Technol Dept Math Harbin Peoples R China Harbin Univ Sci & Technol Key Lab Adv Mfg & Intelligent Technol Minist Educ Harbin Peoples R China

Nonlinear dynamics is frequently encountered in practical applications. adaptive dynamic programming (ADP), which is implemented via actor/critic neural networks with excellent approximation capabilities, is appropriate to be used in finding the solution for the control problem in the presence of known/unknown nonlinear dynamics. The objective of this paper is to introduce state-of-the-art ADP-based algorithms and survey the recent advances in the ADP-based control strategies for nonlinear systems with various engineering-oriented complexities. Firstly, the main motivation of the ADP-based algorithms is thoroughly discussed, and the way of implementing the ADP-based algorithms is highlighted. Then, the latest research results concerning ADP-based control policy design for nonlinear systems are reviewed in detail, Finally, we conclude the survey by outlining the challenges and possible research topics in the future.

关键词： Nonlinear dynamics adaptive dynamic programming nonlinear control neural networks engineering-oriented complexities

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A Nonlinear Critical Surface With Input Constraints on Costate-adaptive dynamic programming

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2023年第11期70卷 4088-4092页

作者： Zhao, Guijie Sun, Jiayue Yan, Ying Zhang, Huaguang Northeastern Univ Sch Informat Sci & Engn Shenyang 110189 Liaoning Peoples R China Northeastern Univ State Key Laboratoryof Synthet Automat Proc Ind Shenyang 110189 Liaoning Peoples R China

In this brief, a costate-adaptive dynamic programming algorithm is presented to solve a class of nonlinear critical surface problems with input constraints. Different from the traditional-dual heuristic dynamic programming, costate-ADP does not rely on the exact system model, and can incubate the model-neural network through data catalysis, avoiding the super-dimensional calculation in the iterative process. Furthermore, the critical nonlinear surface with input constraints is transformed into the optimal action sequence for solving the non-quadratic HJB equation with discount factor. The costate function replaces the integral term in the repeated iterations. The algorithm is proved to be effective in determining the security properties of a class of structures.

关键词： adaptive dynamic programming critical surface dual heuristic dynamic programming costate function non-quadratic

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Robust Sliding Mode adaptive dynamic programming Control for Partially Unknown Second-order Nonlinear Systems 43

Robust Sliding Mode Adaptive Dynamic Programming Control for...

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43rd Chinese Control Conference (CCC)

作者： Huang, Tao Lu, Hongqian Yang, Yefeng Huang, Xianlin Harbin Inst Technol Ctr Control Theory & Guidance Technol Harbin 150001 Peoples R China Hong Kong Polytech Univ Dept Aeronaut & Aviat Engn Hong Kong 100872 Peoples R China

ISBN: (纸本)9798350366907;9789887581581

This paper introduces a novel robust cost function for the ADP algorithm to suppress the impact of the disturbance for partially unknown second-order nonlinear systems. The sliding mode control is employed to design the cost function, which thereby enhances the performance of the closed-loop system. Furthermore, an offline disturbance compensator is proposed to further improve the robustness of the system. Subsequently, the trajectory of the entire closed-loop system is proved to be uniformly ultimate bounded (UUB) in a Lyapunov sense. Sufficient simulations are conducted to verify the effectiveness and superiority of the proposed method.

关键词： Sliding mode control adaptive dynamic programming Robust cost function Disturbance compensator

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Bias-Policy Iteration Based adaptive dynamic programming for Linear Fully Actuated Systems 3

Bias-Policy Iteration Based Adaptive Dynamic Programming for...

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3rd Conference on Fully Actuated System Theory and Applications (FASTA)

作者： Jiang, Huaiyuan Yang, Xuefei Xu, Chuanchuan Zhang, Kangkang Harbin Inst Technol Ctr Control Theory & Guidance Technol POB 416 Harbin 150001 Peoples R China Nanjing Res Inst Elect Engn Nanjing 210000 Peoples R China Univ Hong Kong Dept Mech Engn Hong Kong Peoples R China

ISBN: (纸本)9798350373707;9798350373691

In this paper, the bias-policy iteration based optimal control of fully actuated systems is further reconsidered. With the help of the fully actuated property, a more neat bias-PI method for the fully actuated cases is established with the convergence proof. The data-driven implementation for the proposed algorithm is introduced accordingly. A numerical example verifies the effectiveness of the proposed results.

关键词： Fully actuated systems adaptive dynamic programming Data driven control Bias-policy iteration

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Data-Driven CACC of Vehicular Platoons Based on adaptive dynamic programming with Initial Excitation 39

Data-Driven CACC of Vehicular Platoons Based on Adaptive Dyn...

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39th Youth Academic Annual Conference of Chinese-Association-of-Automation (YAC)

作者： Yang, Xin Liu, Zhongchang Zhao, Wenyan Dalian Maritime Univ Coll Marine Elect Engn Dalian Peoples R China

ISBN: (纸本)9798350390780;9798350379228

This paper studies the cooperative adaptive cruise control (CACC) problem for a platoon of vehicles with unknown system parameters. Data-based adaptive dynamic programming (ADP) method is adopted to solve the control gains of the vehicles from algebraic Ricatti equations by using online data. The ADP takes a two-layer filter structure, which only requires the initial excitation (IE) condition instead of the restricted persistent excitation (PE) condition when solving the iterative equation. Moreover, data-storage for integral computation is obviated compared with existing data-driven approaches. The simulation results show the effectiveness of the proposed method.

关键词： adaptive dynamic programming cooperative adaptive cruise control (CACC) filter-based design

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adaptive dynamic programming enhanced admittance control for robots with environment interaction and actuator saturation

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INTERNATIONAL JOURNAL OF INTELLIGENT ROBOTICS AND APPLICATIONS 2021年第1期5卷 89-100页

作者： Zhan, Hong Huang, Dianye Yang, Chenguang South China Univ Technol Key Lab Autonomous Syst & Networked Control Minist Educ Guangzhou 510640 Peoples R China Tech Univ Munich Dept Informat D-85748 Munich Germany Univ West England Bristol Robot Lab Bristol BS16 1QY Avon England

This paper focuses on the optimal tracking control problem for robot systems with environment interaction and actuator saturation. A control scheme combined with admittance adaptation and adaptive dynamic programming (ADP) is developed. The unknown environment is modelled as a linear system and admittance controller is derived to achieve compliant behaviour of the robot. In the ADP framework, the cost function is defined with non-quadratic form and the critic network is designed with radial basis function neural network which introduces to obtain an approximate optimal control of the Hamilton-Jacobi-Bellman equation, which guarantees the optimal trajectory tracking. The system stability is analysed by Lyapunov theorem and simulations demonstrate the effectiveness of the proposed strategy.

关键词： adaptive dynamic programming Admittance control Robot-environment interaction Actuator saturation Optimal control Neural network

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adaptive dynamic programming for Control: A Survey and Recent Advances

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IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2021年第1期51卷 142-160页

作者： Liu, Derong Xue, Shan Zhao, Bo Luo, Biao Wei, Qinglai Guangdong Univ Technol Sch Automat Guangzhou 510006 Peoples R China South China Univ Technol Sch Comp Sci & Engn Guangzhou 510006 Peoples R China Beijing Normal Univ Sch Syst Sci Beijing 100875 Peoples R China Cent South Univ Sch Automat Changsha 410083 Peoples R China Peng Cheng Lab Shenzhen 518000 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China

This article reviews the recent development of adaptive dynamic programming (ADP) with applications in control. First, its applications in optimal regulation are introduced, and some skilled and efficient algorithms are presented. Next, the use of ADP to solve game problems, mainly nonzero-sum game problems, is elaborated. It is followed by applications in large-scale systems. Note that although the functions presented in this article are based on continuous-time systems, various applications of ADP in discrete-time systems are also analyzed. Moreover, in each section, not only some existing techniques are discussed, but also possible directions for future work are pointed out. Finally, some overall prospects for the future are given, followed by conclusions of this article. Through a comprehensive and complete investigation of its applications in many existing fields, this article fully demonstrates that the ADP intelligent control method is promising in today's artificial intelligence era. Furthermore, it also plays a significant role in promoting economic and social development.

关键词： adaptive critic designs (ACDs) adaptive dynamic programming approximate dynamic programming intelligent control learning control neural dynamic programming neuro-dynamic programming optimal control reinforcement learning (RL)

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adaptive dynamic programming based composite control for profile tracking with multiple constraints

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NEUROCOMPUTING 2023年第1期557卷

作者： Tang, Rui Luo, Biao Liao, Yuxin Cent South Univ Sch Automat Changsha 410083 Peoples R China

A composite control method based on adaptive dynamic programming (ADP) is developed to solve the profile tracking problem of the hypersonic gliding vehicle (HGV) with multiple constraints (flight and input constraints). First, based on the framework of the standard profile guidance method, a standard drag acceleration-velocity profile is planned as the tracking target, which satisfies the flight constraints. Second, a composite controller based on ADP and dynamic surface control (DSC) is proposed to track the planned profile and satisfy both the terminal conditions and the input constraint. An ADP method is developed to realize the optimal control through a critic neural network (NN) approximation for the solution of Hamilton- Jacobi-Bellman (HJB) equation. By using DSC method, the steady control is realized. Finally, the states of the closed-loop system and the weight estimation error are proved to be uniformly ultimately bounded, and the effectiveness of the proposed composite control method is verified via simulations.

关键词： Hypersonic gliding vehicle Standard profile adaptive dynamic programming Composite control Multiple constraints

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Decentralized Fault Tolerant Control of Modular Manipulators System Based on adaptive dynamic programming

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INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS 2022年第10期20卷 3252-3263页

作者： Zhou, Fan Nie, Fujie An, Tianjiao Ma, Bing Li, Yuanchun Changchun Univ Technol Dept Control Sci & Engn Changchun 130012 Peoples R China

This paper presented an original decentralized fault tolerant control approach for modular manipulators which based on adaptive dynamic programming (ADP) algorithm. First, the dynamic model of modular manipulators is established via joint torque feedback technique. Then, the fault tolerant controller is designed which composes of model-based compensation controller, observer-based fault tolerant controller and ADP-based optimal controller. According to ADP algorithm, the Hamiltonian-Jacobi-Bellman (HJB) equation can be tackled by critic neural network (NN). The closed-loop modular manipulators system is guaranteed asymptotic stable based on Lyapunov theory. Experiments are performed to verify the proposed method, and the results have guaranteed its effectiveness.

关键词： adaptive dynamic programming decentralized control fault tolerant control modular manipulators

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