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学者姓名：王鼎
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摘要 ：
In this article, in order to achieve optimal tracking control of unknown linear discrete sys-tems, a model-free scheme based on Q-learning is established online. First, we introduce an innovative performance index function, so as to eliminate the tracking error and avert the calculation for stable control policies of the reference trajectory. Taking value iteration and policy iteration into consideration, the corresponding model-based approaches are derived. Then, the Q-function is developed and the model-free algorithm utilizing Q-learning is given for the sake of dealing with the linear quadratic tracking (LQT) problem online with-out relying on system dynamics information. In addition, novel stability analysis based on Q-learning is provided for the discounted LQT control issue and the probing noise is demonstrated that it does not result in any excitation noise bias. Finally, by means of con-ducting numerical simulation, the proposed Q-learning algorithm is demonstrated to be effective and practicable.(c) 2023 Elsevier Inc. All rights reserved.
关键词 ：
Model -free control Model -free control Discounted linear quadratic tracking Discounted linear quadratic tracking Adaptive critic Adaptive critic Q-function Q-function Reinforcement learning Reinforcement learning
引用：
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| GB/T 7714 | Wang, Ding , Ren, Jin , Ha, Mingming . Discounted linear Q-learning control with novel tracking cost and its stability [J]. | INFORMATION SCIENCES , 2023 , 626 : 339-353 . |
| MLA | Wang, Ding 等. "Discounted linear Q-learning control with novel tracking cost and its stability" . | INFORMATION SCIENCES 626 (2023) : 339-353 . |
| APA | Wang, Ding , Ren, Jin , Ha, Mingming . Discounted linear Q-learning control with novel tracking cost and its stability . | INFORMATION SCIENCES , 2023 , 626 , 339-353 . |
| 导入链接 | NoteExpress RIS BibTex |
摘要 ：
本发明提供了一种针对双自旋稳定系统的加速集成值迭代控制方法。双自旋稳定系统是航天器的姿态控制中的重要实现方法之一。具有旋转激励的平移振荡器(RTAC)作为双自旋航天器的简化模型被广泛研究。然而RTAC系统内部存在非线性，不确定性及干扰，为了实现该系统的智能优化控制，本发明基于自适应评判框架，提出了一种集成的新型值迭代方案，引入松弛因子加速代价函数的迭代过程，且该算法生成的控制策略能够保证闭环系统的稳定性。同时，设计了自适应松弛函数来调节代价函数序列的收敛速度。通过实验结果验证了所提出的集成值迭代控制算法的快速收敛性，从而能够快速有效地获得最优控制策略，在保证系统稳定的同时提升控制效率。
引用：
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| GB/T 7714 | 王鼎 , 任进 . 一种针对双自旋稳定系统的加速集成值迭代控制方法 : CN202310712294.X[P]. | 2023-06-16 . |
| MLA | 王鼎 等. "一种针对双自旋稳定系统的加速集成值迭代控制方法" : CN202310712294.X. | 2023-06-16 . |
| APA | 王鼎 , 任进 . 一种针对双自旋稳定系统的加速集成值迭代控制方法 : CN202310712294.X. | 2023-06-16 . |
| 导入链接 | NoteExpress RIS BibTex |
摘要 ：
本发明涉及一种基于Q学习的污水处理硝态氮浓度控制方法。在污水处理系统中，使硝态氮浓度跟踪上期望轨迹是污水处理过程的一个重要控制目标。本发明针对硝态氮浓度的期望值跟踪问题，提出一种基于Q学习的轨迹跟踪控制方法，降低对系统模型信息要求，并用于实现污水处理过程中硝态氮浓度的跟踪控制设计。根据自适应动态规划算法，建立Q学习算法框架，训练神经网络来解决最优跟踪控制问题，并在BSM1(Benchmark Simulation Model No.1)仿真模型上进行方法验证。本发明能够保证硝态氮浓度更精准地跟踪上期望轨迹，从而实现污水处理过程的有效控制。
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| GB/T 7714 | 王鼎 , 王元 , 赵明明 . 一种基于Q学习的污水处理硝态氮浓度控制方法 : CN202310713223.1[P]. | 2023-06-15 . |
| MLA | 王鼎 等. "一种基于Q学习的污水处理硝态氮浓度控制方法" : CN202310713223.1. | 2023-06-15 . |
| APA | 王鼎 , 王元 , 赵明明 . 一种基于Q学习的污水处理硝态氮浓度控制方法 : CN202310713223.1. | 2023-06-15 . |
| 导入链接 | NoteExpress RIS BibTex |
摘要 ：
In this paper, the decentralised tracking control (DTC) problem is investigated for a class of continuous-time large-scale systems with external disturbance by utilising adaptive dynamic programming (ADP). Firstly, the DTC problem is solved by designing corresponding optimal controllers of the isolated subsystems, which are formulated with N augmented subsystems consisting of the tracking error and the reference trajectory. Then, considering the external disturbance, we can effectively construct the DTC scheme by means of adding suitable feedback gains to the optimal control strategies associated with each augmented tracking isolated subsystems (ATISs). Due to the approximate nature, a series of critic neural networks are constructed to solve the Hamilton-Jacobi-Isaacs equation, so as to derive the estimation of the Nash equilibrium solution containing the optimal control strategy and the worst disturbance law. Herein, a modified weight updating criterion is developed by employing a stabilising term. Consequently, we remove the requirement of initial admissible control in the proposed algorithm. After that, stability analysis of the ATIS is performed through the Lyapunov theory, in the sense that tracking states and weight approximation errors are uniformly ultimately bounded. Finally, an experimental simulation is demonstrated to ensure the validity of the proposed DTC scheme.
关键词 ：
optimal control optimal control Adaptive dynamic programming (ADP) Adaptive dynamic programming (ADP) interconnected systems interconnected systems disturbance rejection disturbance rejection decentralised tracking control (DTC) decentralised tracking control (DTC) neural networks neural networks
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| GB/T 7714 | Wang, Ding , Fan, Wenqian , Li, Menghua et al. Decentralised tracking control based on critic learning for nonlinear disturbed interconnected systems [J]. | INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE , 2023 , 54 (5) : 1150-1164 . |
| MLA | Wang, Ding et al. "Decentralised tracking control based on critic learning for nonlinear disturbed interconnected systems" . | INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE 54 . 5 (2023) : 1150-1164 . |
| APA | Wang, Ding , Fan, Wenqian , Li, Menghua , Qiao, Junfei . Decentralised tracking control based on critic learning for nonlinear disturbed interconnected systems . | INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE , 2023 , 54 (5) , 1150-1164 . |
| 导入链接 | NoteExpress RIS BibTex |
摘要 ：
The decomposition-based evolutionary algorithm (MOEA/D) has attained excellent performance in solving optimization problems involving multiple conflicting objectives. However, the Pareto-optimal front (POF) of many multiobjective optimization problems (MOPs) has irregular properties, which weakens the performance of MOEA/D. To address this issue, we devise a dynamic transfer reference point-oriented MOEA/D with local objective-space knowledge (DTR-MOEA/D). The design principle is based on three original and rigorous mechanisms. First, the individuals are projected onto a line segment (two-objective case) or a 3-D plane (three-objective case) after being normalized in the objective space. The line segment or the plane is divided into three different regions: 1) the central region; 2) the middle region; and 3) the edge region. Second, a dynamic transfer criterion of the reference point is developed based on the population density relationships in different regions. Third, a strategy of population diversity enhancement guided by local objective-space knowledge is adopted to improve the diversity of the population. Finally, the experimental results conducted on 16 benchmark MOPs and eight modified MOPs with irregular POF shapes verify that the proposed DTR-MOEA/D has attained a strong competitiveness compared with other representative algorithms.
关键词 ：
Shape Shape Pareto optimization Pareto optimization multiobjective optimization multiobjective optimization Optimization Optimization Decomposition Decomposition Statistics Statistics local objective space local objective space dynamic transfer reference point dynamic transfer reference point Convergence Convergence Sociology Sociology Optical fibers Optical fibers
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| GB/T 7714 | Xie, Yingbo , Yang, Shengxiang , Wang, Ding et al. Dynamic Transfer Reference Point-Oriented MOEA/D Involving Local Objective-Space Knowledge [J]. | IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION , 2022 , 26 (3) : 542-554 . |
| MLA | Xie, Yingbo et al. "Dynamic Transfer Reference Point-Oriented MOEA/D Involving Local Objective-Space Knowledge" . | IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION 26 . 3 (2022) : 542-554 . |
| APA | Xie, Yingbo , Yang, Shengxiang , Wang, Ding , Qiao, Junfei , Yin, Baocai . Dynamic Transfer Reference Point-Oriented MOEA/D Involving Local Objective-Space Knowledge . | IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION , 2022 , 26 (3) , 542-554 . |
| 导入链接 | NoteExpress RIS BibTex |
摘要 ：
In this paper, an adaptive critic method based on neural networks is established to solve the tracking con-trol problem for multi-person zero-sum games with constrained nonlinear dynamics. First, an augmented system is constructed with the tracking error system and the reference system, an appropriate function is introduced to handle the constrained problem, and a constrained tracking Hamilton-Jacobi-Isaacs (HJI) equation is derived for the augmented system. Then, a constrained tracking design with neural critic learning for multi-person zero-sum games is developed to approximately solve the tracking HJI equation with input constraints. A new updating rule is given and only one critic network is employed during neural critic learning. In addition, we prove that the tracking error in the augmented system is uniformly ulti-mately bounded by using Lyapunov's direct method. Finally, an example is given to verify the effectiveness of the proposed method. In this example, we make the number of control inputs less than the number of disturbance inputs. (C) 2022 Elsevier B.V. All rights reserved.
关键词 ：
Multi -person zero -sum games Multi -person zero -sum games Adaptive dynamic programming Adaptive dynamic programming Neural critic learning Neural critic learning Constrained tracking control Constrained tracking control
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| GB/T 7714 | Li, Menghua , Wang, Ding , Qiao, Junfei . Neural critic learning for tracking control design of constrained nonlinear multi-person zero-sum games [J]. | NEUROCOMPUTING , 2022 , 512 : 456-465 . |
| MLA | Li, Menghua et al. "Neural critic learning for tracking control design of constrained nonlinear multi-person zero-sum games" . | NEUROCOMPUTING 512 (2022) : 456-465 . |
| APA | Li, Menghua , Wang, Ding , Qiao, Junfei . Neural critic learning for tracking control design of constrained nonlinear multi-person zero-sum games . | NEUROCOMPUTING , 2022 , 512 , 456-465 . |
| 导入链接 | NoteExpress RIS BibTex |
摘要 ：
The idea of optimization can be regarded as an important basis of many disciplines and hence is extremely useful for a large number of research fields, particularly for artificial-intelligence-based advanced control design. Due to the difficulty of solving optimal control problems for general nonlinear systems, it is necessary to establish a kind of novel learning strategies with intelligent components. Besides, the rapid development of computer and networked techniques promotes the research on optimal control within discrete-time domain. In this paper, the bases, the derivation, and recent progresses of critic intelligence for discrete-time advanced optimal control design are presented with an emphasis on the iterative framework. Among them, the so-called critic intelligence methodology is highlighted, which integrates learning approximators and the reinforcement formulation.
关键词 ：
Advanced optimal control Advanced optimal control Intelligent critic Intelligent critic Dynamic systems Dynamic systems
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| GB/T 7714 | Wang, Ding , Ha, Mingming , Zhao, Mingming . The intelligent critic framework for advanced optimal control [J]. | ARTIFICIAL INTELLIGENCE REVIEW , 2022 , 55 (1) : 1-22 . |
| MLA | Wang, Ding et al. "The intelligent critic framework for advanced optimal control" . | ARTIFICIAL INTELLIGENCE REVIEW 55 . 1 (2022) : 1-22 . |
| APA | Wang, Ding , Ha, Mingming , Zhao, Mingming . The intelligent critic framework for advanced optimal control . | ARTIFICIAL INTELLIGENCE REVIEW , 2022 , 55 (1) , 1-22 . |
| 导入链接 | NoteExpress RIS BibTex |
摘要 ：
In this article, a novel value iteration scheme is developed with convergence and stability discussions. A relaxation factor is introduced to adjust the convergence rate of the value function sequence. The convergence conditions with respect to the relaxation factor are given. The stability of the closed-loop system using the control policies generated by the present VI algorithm is investigated. Moreover, an integrated VI approach is developed to accelerate and guarantee the convergence by combining the advantages of the present and traditional value iterations. Also, a relaxation function is designed to adaptively make the developed value iteration scheme possess fast convergence property. Finally, the theoretical results and the effectiveness of the present algorithm are validated by numerical examples.
关键词 ：
Numerical stability Numerical stability reinforcement learning (RL) reinforcement learning (RL) Stability criteria Stability criteria Adaptive dynamic programming (ADP) Adaptive dynamic programming (ADP) discrete-time nonlinear systems discrete-time nonlinear systems value iteration value iteration convergence rate convergence rate Heuristic algorithms Heuristic algorithms Approximation algorithms Approximation algorithms Optimal control Optimal control Convergence Convergence admissible control policy admissible control policy Iterative algorithms Iterative algorithms
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| GB/T 7714 | Ha, Mingming , Wang, Ding , Liu, Derong . A Novel Value Iteration Scheme With Adjustable Convergence Rate [J]. | IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS , 2022 , 34 (10) : 7430-7442 . |
| MLA | Ha, Mingming et al. "A Novel Value Iteration Scheme With Adjustable Convergence Rate" . | IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 34 . 10 (2022) : 7430-7442 . |
| APA | Ha, Mingming , Wang, Ding , Liu, Derong . A Novel Value Iteration Scheme With Adjustable Convergence Rate . | IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS , 2022 , 34 (10) , 7430-7442 . |
| 导入链接 | NoteExpress RIS BibTex |
摘要 ：
In this paper, an event-triggered neural critic learning algorithm is investigated to address constrained nonzero-sum game problems with discrete-time nonaffine dynamics. First, in order to ensure the saturation independence of two controllers in the nonzero-sum game problem, we adopt two different boundaries to constrain them respectively. Then, a novel triggering condition is designed to reduce the update times of the controllers, which achieves the purpose of less calculation. It is emphasised that the triggering condition is established based on the iteration of the time-triggered mechanism. Meanwhile, we prove that the real cost function possesses a predetermined upper bound, which realises the cost guarantee of the controlled system. In addition, we prove that the closed-loop system using the developed algorithm is asymptotically stable and that the system state and the sampling state are uniformly ultimately bounded during the process of training neural networks. Finally, two simulation examples are conducted to demonstrate the effectiveness of the proposed algorithm.
关键词 ：
Adaptive critic technique Adaptive critic technique optimal control optimal control neural networks neural networks nonaffine systems nonaffine systems event-triggered control event-triggered control constrained control constrained control nonzero-sum games nonzero-sum games
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| GB/T 7714 | Hu, Lingzhi , Wang, Ding , Ren, Jin et al. An event-triggered neural critic technique for nonzero-sum game design with control constraints [J]. | INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE , 2022 , 54 (2) : 237-250 . |
| MLA | Hu, Lingzhi et al. "An event-triggered neural critic technique for nonzero-sum game design with control constraints" . | INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE 54 . 2 (2022) : 237-250 . |
| APA | Hu, Lingzhi , Wang, Ding , Ren, Jin , Wang, Jiangyu , Qiao, Junfei . An event-triggered neural critic technique for nonzero-sum game design with control constraints . | INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE , 2022 , 54 (2) , 237-250 . |
| 导入链接 | NoteExpress RIS BibTex |
摘要 ：
The core task of tracking control is to make the controlled plant track a desired trajectory. The traditional performance index used in previous studies cannot eliminate completely the tracking error as the number of time steps increases. In this paper, a new cost function is introduced to develop the value-iteration-based adaptive critic framework to solve the tracking control problem. Unlike the regulator problem, the iterative value function of tracking control problem cannot be regarded as a Lyapunov function. A novel stability analysis method is developed to guarantee that the tracking error converges to zero. The discounted iterative scheme under the new cost function for the special case of linear systems is elaborated. Finally, the tracking performance of the present scheme is demonstrated by numerical results and compared with those of the traditional approaches.
关键词 ：
stability analysis stability analysis tracking control tracking control discrete-time nonlinear systems discrete-time nonlinear systems approximate dynamic programming approximate dynamic programming Adaptive critic design Adaptive critic design value iteration (VI) value iteration (VI) reinforcement learning reinforcement learning adaptive dynamic programming (ADP) adaptive dynamic programming (ADP)
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| GB/T 7714 | Ha, Mingming , Wang, Ding , Liu, Derong . Discounted Iterative Adaptive Critic Designs With Novel Stability Analysis for Tracking Control [J]. | IEEE-CAA JOURNAL OF AUTOMATICA SINICA , 2022 , 9 (7) : 1262-1272 . |
| MLA | Ha, Mingming et al. "Discounted Iterative Adaptive Critic Designs With Novel Stability Analysis for Tracking Control" . | IEEE-CAA JOURNAL OF AUTOMATICA SINICA 9 . 7 (2022) : 1262-1272 . |
| APA | Ha, Mingming , Wang, Ding , Liu, Derong . Discounted Iterative Adaptive Critic Designs With Novel Stability Analysis for Tracking Control . | IEEE-CAA JOURNAL OF AUTOMATICA SINICA , 2022 , 9 (7) , 1262-1272 . |
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