检索结果-内蒙古大学图书馆

Optimal dynamic output-feedback controller design for linear output regulation problems with its applications

SCIENCE CHINA-INFORMATION SCIENCES 2025年第8期68卷 1-15页

作者： Wang, Zhongyang Wang, Youqing Liang, Li Beijing Univ Chem Technol Coll Informat Sci & Technol Beijing 100029 Peoples R China

This paper designs an optimal dynamic output-feedback controller (ODOFC) for linear output regulation problems based on adaptive dynamic programming (ADP). First, the overall model of the controller and compensator is established using the internal model principle and the minimal polynomial of the exosystem. Second, a state reconstruction technique is employed to reconstruct all system states using measurable input and output information. Subsequently, the delayed form of the minimal polynomial of the exosystem is introduced, eliminating the need to collect the exosystem states. Without relying on system dynamics, a value iteration based off-policy ADP algorithm is proposed to learn ODOFC using online input and output information. Finally, the effectiveness of this method is verified through simulations of a DC motor speed control system and a double integral system, thereby demonstrating its practicality and robustness.

关键词： optimal dynamic output-feedback controller adaptive dynamic programming linear output regulation problems internal model principle value iteration

来源：评论

学校读者我要写书评

暂无评论

Model-Free Optimal Tracking Design With Evolving Control Strategies via Q-Learning

引用

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2024年第7期71卷 3373-3377页

作者： Wang, Ding Huang, Haiming Zhao, Mingming Beijing Univ Technol Fac Informat Technol Beijing Key Lab Computat Intelligence & Intelligen Beijing Lab Smart Environm Protect Beijing 100124 Peoples R China Beijing Univ Technol Beijing Inst Artificial Intelligence Beijing 100124 Peoples R China

This brief leverages a value-iteration-based Q-learning (VIQL) scheme to tackle optimal tracking problems for nonlinear nonaffine systems. The optimal policy is learned from measured data instead of a precise mathematical model. Furthermore, a novel criterion is proposed to determine the stability of the iterative policy based on measured data. The evolving control algorithm is developed to verify the proposed criterion by employing these stable policies for system control. The advantage of the early elimination of tracking errors is provided by this approach since various stable policies can be employed before obtaining the optimal strategy. Finally, the effectiveness of the developed algorithm is demonstrated by a simulation experiment.

关键词： adaptive dynamic programming intelligent control optimal tracking control system stability criterion value-iteration-based Q-learning

来源：评论

学校读者我要写书评

暂无评论

Iterative Q-Learning for Model-Free Optimal Control With Adjustable Convergence Rate

引用

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2024年第4期71卷 2224-2228页

作者： Wang, Ding Wang, Yuan Zhao, Mingming Qiao, Junfei Beijing Univ Technol Beijing Key Lab Computat Intelligence & Intelligen Beijing Lab Smart Environm Protect Fac Informat Technol Beijing 100124 Peoples R China Beijing Univ Technol Beijing Inst Artificial Intelligence Beijing 100124 Peoples R China

In this brief, a novel accelerated Q-learning algorithm is developed to address optimal control problems for discrete-time nonlinear systems. First, the accelerated Q-learning scheme is proposed by introducing the relaxation factor. Note that the relaxation factor leads to the adjustability of the convergence rate. Second, the convergence of the Q-function is analyzed with different relaxation factors. Third, the adjustable Q-learning scheme is developed with guaranteed convergence, which can adaptively change the value of the relaxation factor. Finally, the simulation results demonstrate the effectiveness of this proposed algorithm.

关键词： Convergence Q-learning Optimal control Iterative methods Adaptation models Heuristic algorithms Power system dynamics adaptive dynamic programming fast convergence rate nonlinear systems optimal control

来源：评论

学校读者我要写书评

暂无评论

Data-Driven Optimal Output Cluster Synchronization Control of Heterogeneous Multi-Agent Systems

引用

IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2024年第3期21卷 3910-3920页

作者： Li, Hongyang Wei, Qinglai Chinese Acad Sci Inst Automat State Key Lab Multimodal Artificial Intelligence S Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Macau Univ Sci & Technol Inst Syst Engn Macau Peoples R China

This paper presents a novel data-driven optimal output cluster synchronization control method for heterogeneous multi-agent systems with disturbances based on adaptive dynamic programming. Traditional cluster synchronization control methods require the information of system matrices, which limit the application scope in the reality. In order to solve this problem, a novel data-driven optimal control method is presented, where the input-state data is utilized without the information of system matrices of state equations, to realize the output cluster synchronization of multi-agent systems. The major contributions are displayed as follows: 1) a novel data-driven optimal output cluster synchronization control method is presented which requires the input-state data of multi-agent systems;2) a novel distributed adaptive observer is designed which can avoid the effects of negative edge weights between the clusters;3) the output cluster synchronization control problem is transformed into the output regulation problem, and adaptive dynamic programming method is presented which can realize the disturbance rejection. First, the output cluster synchronization control problem is formulated. Next, a novel optimal output cluster synchronization control method is presented based on distributed adaptive observer and adaptive dynamic programming. Numerical experiment shows the good performance of the presented method. Note to Practitioners-Most of the existing cluster synchronization control methods require the information of system matrices. However, it is hard to obtain the accurate system models in the reality, which limits the application scope of the existing methods. On the other hand, the disturbances in practice make the effective cluster synchronization control of multi-agent systems very challenging. Aiming at the above problems, this paper designs novel data-driven optimal control laws for heterogeneous multi-agent systems with disturbances to realize the output cluster s

关键词： Index Terms- Output cluster synchronization control data-driven control adaptive dynamic programming policy iteration heterogeneous multi-agent systems optimal control

来源：评论

学校读者我要写书评

暂无评论

Bias-policy iteration based optimal control for unknown continuous-time linear periodic systems

引用

SYSTEMS & CONTROL LETTERS 2024年 189卷

作者： Li, Xiang Jiang, Huaiyuan Zhou, Bin Harbin Inst Technol Ctr Control Theory & Guidance Technol Harbin 150001 Peoples R China

In this paper, the optimal control problem for unknown continuous -time linear periodic (CTLP) systems is investigated. A model -based bias -policy iteration algorithm for CTLP systems with its convergence proof is established firstly. Based on that, the data -driven implementation is proposed to approximate the optimal controller without the knowledge of system dynamics. Compared with the existing methods, the advantages of the proposed method are that, the initial stabilizing controller requirement is relaxed, and the approximate optimal controller can be obtained without solving nonlinear differential equations. The numerical simulation verifies the effectiveness of the proposed method.

关键词： adaptive dynamic programming Continuous-time Linear periodic systems Optimal control Data-driven control

来源：评论

学校读者我要写书评

暂无评论

Time-varying gain extended state observer-based adaptive optimal control for disturbed unmanned helicopter

引用

ISA TRANSACTIONS 2024年 148卷 1-11页

作者： Yan, Kun Chen, Hongtian Chen, Chaobo Gao, Song Sun, Jingliang Xian Technol Univ Coll Elect Informat Engn Xian 710021 Peoples R China Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China Beijing Inst Technol Sch Aerosp Engn Beijing 100081 Peoples R China

In this paper, the robust adaptive optimal tracking control problem is addressed for the disturbed unmanned helicopter based on the time -varying gain extended state observer (TVGESO) and adaptive dynamic programming (ADP) methods. Firstly, a novel TVGESO is developed to tackle the unknown disturbance, which can overcome the drawback of initial peaking phenomenon in the traditional linear ESO method. Meanwhile, compared with the nonlinear ESO, the proposed TVGESO possesses easier and rigorous stability analysis process. Subsequently, the optimal tracking control issue for the original unmanned helicopter system is transformed into an optimization stabilization problem. By means of the ADP and neural network techniques, the feedforward controller and optimal feedback controller are skillfully designed. Compared with the conventional backstepping approach, the designed anti -disturbance optimal controller can make the unmanned helicopter accomplish the tracking task with less energy. Finally, simulation comparisons demonstrate the validity of the developed control scheme.

关键词： Unmanned helicopter Time-varying gain extended state observer Optimal tracking control adaptive dynamic programming Neural network

来源：评论

学校读者我要写书评

暂无评论

Fuzzy Optimal Control for a Class of Discrete-Time Switched Nonlinear Systems

引用

IEEE TRANSACTIONS ON FUZZY SYSTEMS 2024年第4期32卷 2297-2306页

作者： Xiang, Zhengrong Li, Pingchuan Chadli, Mohammed Zou, Wencheng Nanjing Univ Sci & Technol Sch Automat Nanjing 210094 Peoples R China Univ Evry Univ Paris Saclay IBISC F-91020 Evry France

This article investigates the optimal tracking problem for discrete-time autonomous nonlinear switched systems with the switching cost. To avoid excessive switching frequency, the switching cost between modes is considered in the performance index, which means that the optimal switching policy is not only related to the tracking error but also the mode applied at the previous instant. The objective is to make the system state track the reference signal while minimizing the defined performance function. A model-free Q-learning algorithm that learns the optimal switching policy from real system data is developed. Furthermore, it is proved by mathematical induction that the iterative Q-functions generated by the proposed Q-learning algorithm will converge to the optimum. To implement the Q-learning algorithm, fuzzy logic systems (FLSs) are applied to approximate the iterative Q-functions. A novel structure of FLSs is designed to ensure the validity of Q-function approximation. Finally, simulation results demonstrate the effectiveness and advantages of the algorithm.

关键词： Switches Switched systems Performance analysis Heuristic algorithms Costs Schedules Mathematical models adaptive dynamic programming fuzzy logic systems (FLSs) optimal switching optimal tracking switching cost

来源：评论

学校读者我要写书评

暂无评论

Optimal control of unknown nonlinear system under event-triggered mechanism and identifier-critic-actor architecture

引用

INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL 2024年第1期34卷 530-550页

作者： Liu, Ning Zhang, Kun Xie, Xiangpeng Nanjing Univ Posts & Telecommun Coll Automat Nanjing Peoples R China Nanjing Univ Posts & Telecommun Coll Artificial Intelligence Nanjing Peoples R China Beihang Univ Sch Astronaut Beijing Peoples R China Nanjing Univ Posts & Telecommun Inst Adv Technol Nanjing Peoples R China Nanjing Univ Posts & Telecommun Inst Adv Technol Nanjing 210023 Peoples R China

This paper proposes an event-triggered adaptive control algorithm for general continuous-time systems with unknown system models. Unlike existing articles, the developed method does not require prior determination of the knowledge of system dynamics, and effectively reduces the update frequency of key signals through the introduction of event-trigger mechanism. Three neural networks (NNs) are designed in the identifier-critic-actor (ICA) architecture to learn the optimal control solution online. The unknown system is approximated by the identifier NN, the critic NN is designed to approach the optimal cost function, and the actor NN is designed to approach the optimal controller. Besides, under event-triggered control, the parameters of critic NN and actor NN as well as control signals are updated only at the trigger time determined by the event-trigger condition, which reduces effectively the computing burden and communication cost. The stability of event-trigger control and the convergence of parameters of three NNs are verified via Lyapunov method. Finally, two examples are presented to demonstrate the viability of the proposed algorithm.

关键词： adaptive dynamic programming event-triggered model-free optimal control

来源：评论

学校读者我要写书评

暂无评论

Three-dimensional optimal trajectory tracking control of underactuated AUVs with uncertain dynamics and input saturation

引用

OCEAN ENGINEERING 2024年 298卷

作者： Gong, Huibin Er, Meng Joo Liu, Yi Ma, Chuang Dalian Maritime Univ Inst Artificial Intelligence & Marine Robot Coll Marine Elect Engn Dalian 116026 Peoples R China

In practice, the energy consumption of underactuated autonomous underwater vehicles (AUVs) is an essential factor to consider. Also, uncertain dynamics, actuator saturation, and unknown environmental disturbances affect control performance. To this end, a three-dimensional optimal trajectory tracking control scheme for underactuated AUVs with environmental disturbances, uncertain dynamics, and input saturation is proposed. First, a continuous differentiable asymmetric saturation model is designed to handle input saturation. Then, the underactuated problem is solved by redefining system outputs. An adaptive neural network observer is developed to estimate disturbances and uncertain dynamic parts. Next, an adaptive backstepping controller is developed via adaptive control and backstepping techniques to obtain a new affine nonlinear system while reducing the effects of input saturation and estimation errors. An optimal controller that can optimize energy consumption and tracking errors is designed via adaptive dynamic programming. Finally, actual control inputs are obtained by combining observer estimates, adaptive backstepping control inputs, approximate optimal control inputs, and the saturation model. Theoretical analysis shows that all signals of the AUV control system are uniformly ultimately bounded, and tracking errors can converge to an arbitrarily small compact set of the origin. Simulation results prove the effectiveness and superiority of the proposed scheme.

关键词： adaptive dynamic programming Input saturation Optimal tracking control Underactuated autonomous underwater vehicles Uncertain dynamics

来源：评论

学校读者我要写书评

暂无评论

New Results in Cooperative adaptive Optimal Output Regulation

引用

Journal of Systems Science & Complexity 2024年第1期37卷 253-272页

作者： DONG Yuchen GAO Weinan JIANG Zhong-Ping State Key Laboratory of Synthetical Automation for Process Industries Northeastern UniversityShenyang 110819China Department of Electrical and Computer Engineering Tandon School of EngineeringNew York UniversityBrooklynNY 11201USA

This paper investigates the cooperative adaptive optimal output regulation problem of continuous-time linear multi-agent *** the multi-agent system dynamics are uncertain,solving regulator equations and the corresponding algebraic Riccati equations is challenging,especially for high-order *** this paper,a novel method is proposed to approximate the solution of regulator equations,i.e.,gradient descent *** is worth noting that this method obtains gradients through online data rather than model information.A data-driven distributed adaptive suboptimal controller is developed by adaptive dynamic programming,so that each follower can achieve asymptotic tracking and disturbance ***,the effectiveness of the proposed control method is validated by simulations.

关键词： adaptive dynamic programming cooperative output regulation gradient descent method multi-agent systems.

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：