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24th International Conference on Neural Information Processing (ICONIP)

作者： Zhu, Liao Song, Ruizhuo Xie, Yulong Li, Junsong Univ Sci & Technol Beijing Sch Automat & Elect Engn Beijing 100083 Peoples R China

ISBN: (纸本)9783319700878;9783319700861

In this paper, a control method for continuous time Direct Current (DC) servo motor, is presented based on adaptive dynamic programming. The core of this paper is the application of adaptive dynamic programming (ADP) to control the DC servo motor system. The program includes three main steps: (i) The mathematical model of DC servo motor system is established, and the feasibility of solving the problem with ADP is analyzed;(ii) On the basis of introducing the theory of ADP, we propose a solution to the problem;(iii) The simulation of the DC servo motor system is carried out. The contribution of this paper is that ADP, which is one of the most important methods in the field of optimal control, is used to solve the traditional problem. Finally, simulation study is conducted to verify the effectiveness of the presented algorithm.

关键词： Optimization adaptive dynamic programming Policy iteration

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adaptive dynamic programming and Blockchain Technique-Based Smart Home Energy Management 3

Adaptive Dynamic Programming and Blockchain Technique-Based ...

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

作者： Zeng, Chujian Zhao, Bo Liu, Derong Guangdong Univ Technol Sch Automat Guangzhou 510006 Peoples R China Beijing Normal Univ Sch Syst Sci Beijing 100875 Peoples R China Southern Univ Sci & Technol Sch Syst Design & Intelligent Mfg Shenzhen 518055 Peoples R China

ISBN: (纸本)9798350373707;9798350373691

This paper focuses on developing an optimal energy storage strategy for smart home energy management using adaptive dynamic programming (ADP) and blockchain technique. The ADP-based self-learning algorithm is developed to generate an iterative control sequence for the battery as the electricity storage equipment. The algorithm takes real-time electricity prices, load demand, and battery power efficiency into account to establish an optimal performance index function. The goal is to minimize total electricity costs while maximizing the battery's lifespan. Additionally, the blockchain technique is employed to ensure transparent, tamper-proof and secure transaction data. A numerical simulation is provided to demonstrate the effectiveness of the proposed algorithm.

关键词： adaptive dynamic programming energy management optimal control smart home blockchain

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adaptive dynamic programming-based optimal tracking control for nonlinear systems using general value iteration

Adaptive dynamic programming-based optimal tracking control ...

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IEEE Symposium on adaptive dynamic programming and Reinforcement Learning (ADPRL)

作者： Lin, Xiaofeng Ding, Qiang Kong, Weikai Song, Chunning Huang, Qingbao Guangxi Univ Sch Elect Engn Nanning Peoples R China

ISBN: (纸本)9781479945528

For the optimal tracking control problem of affine nonlinear systems, a general value iteration algorithm based on adaptive dynamic programming is proposed in this paper. By system transformation, the optimal tracking problem is converted into the optimal regulating problem for the tracking error dynamics. Then, general value iteration algorithm is developed to obtain the optimal control with convergence analysis. Considering the advantages of echo state network, we use three echo state networks with levenberg-Marquardt (LM) adjusting algorithm to approximate the system, the cost function and the control law. A simulation example is given to demonstrate the effectiveness of the presented scheme.

关键词： adaptive dynamic programming value iteration tracking control echo state network

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adaptive dynamic programming Based Decentralized Tracking Control for Unknown Large-scale Systems 36

Adaptive Dynamic Programming Based Decentralized Tracking Co...

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第36届中国控制会议

作者： Bo Zhao Derong Liu Yuanchun Li Qinglai Wei Ruizhuo Song The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences School of Automation Guangdong University of Technology Department of Control Science and Engineering Changchun University of Technology School of Automation and Electrical Engineering University of Science and Technology Beijing

ISBN: (纸本)9781538629185

This paper investigates decentralized tracking control（DTC） problem for unknown large-scale systems via adaptive dynamic *** DTC consists of local desired control and local tracking error *** replacing the actual states of coupled subsystems in interconnection terms with their desired states,the norm-boundedness assumption can be *** on local neural network（NN） observers,unknown subsystems can be *** helps to obtain the local desired control with corresponding desired *** establishing a proper local cost function,the local tracking error control is derived via local critic NN and the identified input gain *** the entire error caused by replacement,identification and critic NN approximation,an adaptive robust term is added to construct the robust local cost function that reflects the entire error,regulation and control ***,the asymptotic stability can be guaranteed for the closed-loop tracking system via Lyapunov stability *** demonstrate the effectiveness of the proposed DTC,simulation on a hard spring connected parallel inverted pendulum system is given.

关键词： adaptive dynamic programming Unknown large-scale systems Decentralized tracking control Neural networks Observer

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adaptive dynamic programming Method for Optimal Battery Management of Battery Electric Vehicle 9

Adaptive Dynamic Programming Method for Optimal Battery Mana...

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9th IEEE Data Driven Control and Learning Systems Conference (DDCLS)

作者： Xue, Jiguang Yan, Chunsheng Wang, Dan Wang, Jun Wu, Jun Liao, Zehua State Grid Liaoning Elect Power Co Ltd Elect Power Res Inst Shenyang 110006 Peoples R China LiaoNing Elect Power Dev Stock Co LTD Shenyang 110006 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

ISBN: (纸本)9781728159225

One of the main influencing factors of battery electric vehicle (BEV) application is the high-cost of the battery. We consider to apply the battery of BEV to smart residential environments when the BEV is idle, so that we can lower the utility cost. Therefore, an adaptive dynamic programming (ADP) method is designed to solve the optimal battery management, which avoids the dimension disaster of the complex nonlinear BEV system. First, the operation modes of the battery are analyzed, and the problem statement is carried out. Then, the corresponding self-learning optimization algorithm is developed based on ADP. Finally, numerical results by experiment simulations are used to verify the ADP algorithm.

关键词： Battery electric vehicle optimal control adaptive dynamic programming battery management

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adaptive dynamic programming Approach for Micro-grid Optimal Energy Transmission Scheduling 39

Adaptive Dynamic Programming Approach for Micro-grid Optimal...

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39th Chinese Control Conference (CCC)

作者： Li, Jinglin Chen, Shuai Jiang, Chengpeng Liu, Fen Xiao, Wendong Univ Sci & Technol Beijing Sch Automat & Elect Engn Beijing 100083 Peoples R China Beijing Engn Res Ctr Ind Spectrum Imaging Beijing 100083 Peoples R China State Grid Blockchain Technol Beijing Co Ltd Beijing 100083 Peoples R China

ISBN: (纸本)9789881563903

Micro-grid energy scheduling optimization is a complex nonlinear optimization problem. During the studies, the micro-grid is the low-voltage system whose resistance of the transmission line plays an important role in the system. Difference in traditional micro-grid control scheme, a new control scheme is proposed which the power flow of each transmission line is taken as decision variables, that is to say, the power flow of each line is controlled in order to get the optimal operating cost of micro-grid. Based on the above, in this paper we focus on the micro-grid optimal energy transmission scheduling. It is formulated as a nonlinear quadratic programming problem with quadratic constraints, due to infinite micro-grid operating cycle, it is also an infinite steps optimization problem. Traditional optimal scheduling algorithm is difficult to deal with. Therefore, we propose an adaptive dynamic programing (ADP) algorithm which is effective to solve the infinite steps optimization problem. ADP could avoid meeting the curse of dimensionality caused by the micro-grid optimization, and also has the neural networks which are updated by themselves during applications. By theoretical proof, we obtain an optimal control accuracy and operation efficiency. Finally, numerical simulation results show that the adaptive dynamic programming algorithm has less operating cost and better control scheme compared with the simulated annealing algorithm.

关键词： micro-grid optimal energy transmission scheduling adaptive dynamic programming

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adaptive dynamic programming-based Decentralized Sliding Mode Optimal Control for Modular and Reconfigurable Robots

Adaptive Dynamic Programming-based Decentralized Sliding Mod...

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IEEE Symposium Series on Computational Intelligence (SSCI)

作者： An, Tianjiao Men, Xiaodong Zhang, Xinyao Li, Yuanchun Dong, Bo Changchun Univ Technol Dept Control Sci & Engn Changchun Peoples R China Northeastern Univ Res Ctr Mech Kinet & Reliabil Qinhuangdao Hebei Peoples R China

ISBN: (纸本)9781728124858

A model-free decentralized sliding mode control (SMC) is proposed via adaptive dynamic programming (ADP) algorithm to solve the problem of optimal tracking control of modular and reconfigurable robots (MRRs) in this paper. The dynamic formulation of MRR is expressed by a synthesis of joint subsystems with interconnected dynamic couplings (IDCs). Based on SMC technique, the optimal control of robotic system is transformed into an optimal compensation problem of unknown dynamics of each subsystem and a neural network (NN) identifier is set up to approximate IDC dynamics. Based on ADP and policy iteration (PI) method, the Hamilton-Jacobi-Bellman (HJB) equation can be addressed by using the critic NN and the optimal control policy can be obtained. The closed-loop robotic system is proved to be asymptotic stable by using the Lyapunov theory. Finally, simulation results are provided to demonstrate the effectiveness of the method.

关键词： Optimal control Decentralized control adaptive dynamic programming Modular and reconfigurable robot

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adaptive dynamic programming-based State Quantized Networked Control System without Value and/or Policy Iterations

Adaptive Dynamic Programming-based State Quantized Networked...

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International Joint Conference on Neural Networks (IJCNN)

作者： Zhao, Qiming Xu, Hao Jagannathan, S. Missouri Univ S&T Dept Elect & Comp Engn Rolla MO 65409 USA

ISBN: (纸本)9781467314909

In this paper, the Bellman equation is used to solve the stochastic optimal control of unknown linear discrete-time system with communication imperfections including random delays, packet losses and quantization. A dynamic quantizer for the sensor measurements is proposed which essentially provides system states to the controller. To eliminate the effect of the quantization error, the dynamics of the quantization error bound and an update law for tuning its range are derived. Subsequently, by using adaptive dynamic programming technique, the infinite horizon optimal regulation of the uncertain NCS is solved in a forward-in-time manner without using value and/or policy iterations by using Q-function and reinforcement learning. The asymptotic stability of the closed-loop system is verified by standard Lyapunov stability theory. Finally, the effectiveness of the proposed method is verified by simulation results.

关键词： Networked Control System Quantization adaptive dynamic programming Optimal Control

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adaptive dynamic programming without Persistence Excitation for Tracking in A Special Class of Linear Systems with Input Constraints 33

Adaptive Dynamic Programming without Persistence Excitation ...

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33rd Chinese Control and Decision Conference (CCDC)

作者： Qin, Chunbin Wang, Jinguang Zhu, Heyang Zhang, Jishi Zhang, Dehua Henan Univ Sch Artificial Intelligence Kaifeng 475000 Peoples R China Henan Univ Sch Software Kaifeng 475000 Peoples R China

ISBN: (纸本)9781665440899

In this paper, an approximate optimal control method with input constraints based on adaptive dynamic programming (ADP) is proposed for a class of special linear systems. The method is based on an actor/critic framework. The critic approximator is used to approximate the optimal cost function, and the actor approximator is used to approximate the bounded control input. In view of the fact that the algorithm requires a persistence of excitation (PE) condition, we use the previous data and the current data to alleviate this requirement. When Lyapunov method is used to prove stability, the error between the optimal control and the bounded control is considered. It is prove that the closed-loop system can be guaranteed to be uniformly ultimately bounded (UUB). On this basis, a robustness term is added to compensate the effect of the approximation error. A simulation example shows the effectiveness.

关键词： adaptive dynamic programming Bounded input control Persistence of excitation Reinforcement learning

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adaptive fault-tolerant control for non-minimum phase hypersonic vehicles based on adaptive dynamic programming

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Chinese Journal of Aeronautics 2024年第3期37卷 290-311页

作者： Le WANG Ruiyun QI Bin JIANG State Key Laboratory of Mechanics and Control for Aerospace Structures Nanjing University of Aeronautics and AstronauticsNanjing 210016China College of Automation Engineering Nanjing University of Aeronautics and AstronauticsNanjing 211106China

In this paper,a novel adaptive Fault-Tolerant Control(FTC)strategy is proposed for non-minimum phase Hypersonic Vehicles(HSVs)that are affected by actuator faults and parameter *** strategy is based on the output redefinition method and adaptive dynamic programming(ADP).The intelligent FTC scheme consists of two main parts:a basic fault-tolerant and stable controller and an ADP-based supplementary *** the basic FTC part,an output redefinition approach is designed to make zero-dynamics stable with respect to the new ***,Ideal Internal dynamic(IID)is obtained using an optimal bounded inversion approach,and a tracking controller is designed for the new output to realize output tracking of the nonminimum phase HSV *** the ADP-based compensation control part,an ActionDependent Heuristic dynamic programming(ADHDP)adopting an actor-critic learning structure is utilized to further optimize the tracking performance of the HSV control ***,simulation results are provided to verify the effectiveness and efficiency of the proposed FTC algorithm.

关键词： Hypersonic vehicle Fault-tolerant control Non-minimum phase system adaptive control Nonlinear control adaptive dynamic programming

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