检索结果-内蒙古大学图书馆

第33届中国过程控制会议

作者： Mingming Liang Derong Liu School of Automation Guangdong University of Technology

This paper focuses on designing the optimal impulsive controller of continuous-time nonlinear systems.A generalevent-based dynamics(GD) is constructed to describe the state transition characteristics across the impulsive actions for the continuous-time nonlinear ***,based on the GD,a new impulsive controller design scheme and an impulsive adaptive dynamic programming(IADP) algorithm are proposed,which possess strong generality and ***,by introducing a novel policy updating mechanism an efficient IADP(EIADP) algorithm is established to make it more flexible to fit into the memory-limited computing devices,thus improving the realization efficiency of the ADP-based *** developed methods are proved to converge to the optimal impulsive performance index functions and obtain the optimal impulsive controllers for the continuous-time nonlinear ***,a numerical study is provided to verify the effectiveness of the proposed IADP and EIADP algorithms.

关键词： adaptive dynamic programming continuous nonlinear system policy iteration impulsive control optimal control

来源：评论

学校读者我要写书评

暂无评论

Multi-source microwave heating temperature uniformity study based on adaptive dynamic programming

引用

HIGH TEMPERATURE MATERIALS AND PROCESSES 2023年第1期42卷

作者： Yang, Biao Peng, Feiyun Zhang, Ziqi Wu, Zhaogang Huang, Hongbin Shi, Yuyi Han, Zemin Kunming Univ Sci & Technol Fac Informat Engn & Automat Kunming 650500 Peoples R China Kunming Univ Sci & Technol Yunnan Key Lab Artificial Intelligence Kunming 650500 Peoples R China Kunming Univ Sci & Technol Key Lab Unconvent Met Minist Educ Kunming 650093 Peoples R China

In view of the multi-physical field coupling and time-varying characteristics of the microwave heating medium process, how to dynamically plan the state characteristics of multiple microwave sources and optimize the material temperature uniformity becomes the focus of this article. To this end, first, algebraic graph theory is used to construct the multiple microwave sources as a multi-agent system, and a perfect communication topology is established to ensure the transfer and sharing of information. Second, according to the real-time temperature distribution of the material, an event-triggered adaptive dynamic planning algorithm is used to co-operate with the power input of the multiple microwave sources to ensure that no new hot spots are generated during the optimization of the temperature distribution using the self-organizing properties of the medium. Finally, a numerical calculation model for optimizing a mixture of integer and continuous variables is solved using the finite-element method. The experimental and numerical results show that this article improves the temperature uniformity by 32.4-73.5% and the heating efficiency by 14.3-39.4% compared to the generic heating model, and the feasibility of the method is verified by the different shapes of the heated material.

关键词： microwave heating multiple microwave sources intelligent agent systems event triggering adaptive dynamic programming

来源：评论

学校读者我要写书评

暂无评论

Optimal trajectory-tracking guidance for reusable launch vehicle based on adaptive dynamic programming

引用

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2023年第PartA期117卷

作者： Wang, Xueyun Li, Yifan Quan, Zhiyuan Wu, Jiabao Beihang Univ Sch Instrument Sci & Optoelect Engn Beijing 100191 Peoples R China China Changfeng Mech & Elect Technol Acad Beijing 100074 Peoples R China

An optimal trajectory-tracking guidance method for Reusable Launch Vehicle (RLV) based on neural adaptive dynamic programming (ADP) is proposed. Firstly, a reentry reference trajectory and the corresponding steady-state control are generated based on the Gauss Pseudo-spectral Method (GPM) with saturation constraints on the amplitude, rate and acceleration of flow angles. A single-critic ADP controller is designed for optimal feedback control, which is combined with the steady-state control to realize the trajectory-tracking guidance. An innovative weight iteration algorithm for the critic neural network is proposed to reduce training computation and improve guidance accuracy. Simulation results show that with initial state errors and system uncertainty, the terminal position error is within 2.1 km in a reentry flight whose range covers more than 5500 km. Involved with the innovative weight iteration method, the training computation is reduced by 95% compared with the traditional gradient descent method and the guidance performance is also improved.

关键词： adaptive dynamic programming Reusable launch vehicle Approximate optimal control Trajectory-tracking guidance Neural weight iteration

来源：评论

学校读者我要写书评

暂无评论

adaptive dynamic programming and deep reinforcement learning for the control of an unmanned surface vehicle: Experimental results

引用

CONTROL ENGINEERING PRACTICE 2021年 111卷 104807-104807页

作者： Gonzalez-Garcia, Alejandro Barragan-Alcantar, David Collado-Gonzalez, Ivana Garrido, Leonardo Tecnol Monterrey Sch Sci & Engn Av Eugenio Garza Sada 2501 Sur Monterrey 64849 Nuevo Leon Mexico

This paper presents a low-level controller for an unmanned surface vehicle based on adaptive dynamic programming and deep reinforcement learning. This approach uses a single deep neural network capable of self-learning a policy, and driving the surge speed and yaw dynamics of a vessel. A simulation of the vehicle mathematical model was used to train the neural network with the model-based backpropagation through time algorithm, capable of dealing with continuous action-spaces. The path-following control scenario is additionally addressed by combining the proposed low-level controller and a line-of-sight based guidance law with time-varying look-ahead distance. Simulation and real-world experimental results are presented to validate the control capabilities of the proposed approach and contribute to the diversity of validated applications of adaptive dynamic programming based control strategies. Results show the controller is capable of self-learning the policy to drive the surge speed and yaw dynamics, and has an improved performance in comparison to a standard controller.

关键词： Unmanned surface vehicle (USV) adaptive dynamic programming Backpropagation through time Deep reinforcement learning Marine robotics

来源：评论

学校读者我要写书评

暂无评论

dynamic event-triggered control for discrete-time nonlinear Markov jump systems using policy iteration-based adaptive dynamic programming

引用

NONLINEAR ANALYSIS-HYBRID SYSTEMS 2023年 49卷

作者： Tang, Fanghua Wang, Huanqing Chang, Xiao-Heng Zhang, Liang Alharbi, Khalid H. Bohai Univ Coll Control Sci & Engn Jinzhou 121013 Liaoning Peoples R China Bohai Univ Coll Math Sci Jinzhou 121013 Liaoning Peoples R China King Abdulaziz Univ Fac Engn Dept Elect & Comp Engn Commun Syst & Networks Res Grp Jeddah Saudi Arabia

This paper investigates a dynamic event-triggered optimal control problem of discrete-time (DT) nonlinear Markov jump systems (MJSs) via exploring policy iteration (PI) adaptive dynamic programming (ADP) algorithms. The performance index function (PIF) defined in each subsystem is updated by utilizing an online PI algorithm, and the corresponding control policy is derived via solving the optimal PIF. Then, we adopt neural network (NN) techniques, including an actor network and a critic network, to estimate the iterative PIF and control policy. Moreover, the designed dynamic event-triggered mechanism (DETM) is employed to avoid wasting additional resources when the estimated iterative control policy is updated. Finally, based on the Lyapunov difference method, it is proved that the system stability and the convergence of all signals can be guaranteed under the developed control scheme. A simulation example for DT nonlinear MJSs with two system modes is presented to demonstrate the feasibility of the control design scheme.& COPY;2023 Elsevier Ltd. All rights reserved.

关键词： Markov jump systems Neural network dynamic event-triggered mechanism Policy iteration adaptive dynamic programming

来源：评论

学校读者我要写书评

暂无评论

Pinning consensus control for switched multi-agent systems: A switched adaptive dynamic programming method

引用

NONLINEAR ANALYSIS-HYBRID SYSTEMS 2023年 48卷

作者： Qi, Yiwen Geng, Honglin Fuzhou Univ Coll Elect Engn & Automat Fuzhou 350108 Peoples R China Shenyang Aerosp Univ Sch Automat Shenyang 110136 Peoples R China

Stability is fundamental to ensure the operation of control system, but optimality is the ultimate goal to achieve the maximum performance. This paper investigates an event -triggered pinning optimal consensus control for switched multi-agent system (SMAS) via a switched adaptive dynamic programming (ADP) method. The technical contribution mainly lies in two aspects. On the one hand, in order to optimize the control performance and ensure the consensus, the switched local value function (SLVF) and the minimum -error switching law are constructed. Based on SLVF, an algorithm of switched ADP policy iteration is proposed, and its convergence and optimality are proved. On the other hand, considering that it is impractical to install a controller for each agent in reality, a pinning strategy is developed to guide the setting of the ADP controller, which can reduce the waste of control resources. A new condition is constructed to determine the minimum number of controlled vertices of the SMAS. Lastly, a numerical example is given to verify the effectiveness of the proposed method.(c) 2022 Elsevier Ltd. All rights reserved.

关键词： Switched multi-agent system Pinning control adaptive dynamic programming Control constraint

来源：评论

学校读者我要写书评

暂无评论

Event-triggered optimal decentralized control for stochastic interconnected nonlinear systems via adaptive dynamic programming

引用

NEUROCOMPUTING 2023年第1期539卷

作者： Zhao, Yanwei Niu, Ben Zong, Guangdeng Xu, Ning Ahmad, Adil M. Bohai Univ Coll Control Sci & Engn Jinzhou 121013 Peoples R China Shandong Normal Univ Sch Informat Sci & Engn Jinan 250014 Peoples R China Tiangong Univ Sch Control Sci & Engn Tianjin 300387 Peoples R China Bohai Univ Coll Informat Sci & Technol Jinzhou 121013 Peoples R China King Abdulaziz Univ Fac Comp & Informat Technol Dept Informat Technol Commun Syst & Networks Res Grp Jeddah Saudi Arabia

This paper presents an event-triggered adaptive dynamic programming (ETADP) algorithm to study the optimal decentralized control issue of interconnected nonlinear systems subject to stochastic dynamics. By developing a performance index function for augmented auxiliary subsystem, the primordial control issue is converted into deriving an array of optimal control policies sampling in an aperiodic pattern. Then, an ETADP algorithm is introduced under an identifier-actor-critic network framework, where the identifier aims to determine the stochastic dynamic, the critic aims to assess the system performance and the actor aims to implement the control action. A remarkable feature is that the actor-critic updating laws are constructed through the negative gradient method of a positive function, which is designed in the light of the partial derivative of a Hamilton-Jacobi-Bellman equation. Under the provided weight tun-ing rule, the traditional ADP algorithm can be significantly simplified. The stability of the close-loop sys-tem is verified through direct Lyapunov theory, and a numerical simulation is given to confirm the effectiveness of the optimal control scheme.(c) 2023 Elsevier B.V. All rights reserved.

关键词： Stochastic interconnected systems Event -triggered control adaptive dynamic programming Identifier -actor -critic networks Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

adaptive dynamic programming-Based Sliding Mode Optimal Position-Force Control for Reconfigurable Manipulators with Uncertain Disturbance 32

Adaptive Dynamic Programming-Based Sliding Mode Optimal Posi...

引用

32nd Chinese Control And Decision Conference (CCDC)

作者： Zhu, Xinye Ma, Bing Dong, Bo Liu, Keping Li, Yuanchun Changchun Univ Technol Dept Control Sci & Engn Changchun 130012 Peoples R China

ISBN: (纸本)9781728158556

In this paper, a sliding mode optimal position-force control method is proposed for constrained reconfigurable manipulators with disturbance based on adaptive dynamic programming (ADP) method and policy iteration (PI) algorithm. The sliding mode control is developed to compensate the model uncertainties, and the improved performance index function includes the sliding mode function and disturbance function. Then, the position-force control problem of the reconfigurable manipulator system under disturbance is transformed into an optimal control issue. The solution of Hamiltonian-Jacobi-Bellman (HJB) equation can be solved by using ADP and PI methods, and then the approximated sliding mode optimal control policy can be derived by constructing the critic neural network (NN). The closed-loop robotic system is proved to be asymptotic stability by using Lyapunov theory. Finally, simulations are provided to demonstrate the effectiveness of the proposed method.

关键词： Reconfigurable manipulators adaptive dynamic programming Sliding mode optimal position-force control Policy iteration algorithm Critic neural network

来源：评论

学校读者我要写书评

暂无评论

Fault-tolerant control based on adaptive dynamic programming for reentry vehicles subjected to state-dependent actuator fault

引用

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2023年第PartC期123卷

作者： Hu, Guanjie Guo, Jianguo Cieslak, Jerome Ding, Yixin Guo, Zongyi Henry, David Northwestern Polytech Univ Inst Precis Guidance & Control Xian Peoples R China Univ Bordeaux CNRS Bordeaux INP IMSUMR 5218 F-33400 Talence France

The paper addresses the problem of fault tolerant control (FTC) for reentry vehicles (RV) subject to actuator fault and perturbation. In contrast to the majority of papers assuming bounded and exogenous actuator fault effect, the adaptive dynamic programming (ADP) control algorithm has been considered here to tackle with the dependence of closed-loop states induced by the setup of an active FTC strategy. By this way, the FTC problem formulation takes theoretically into account the fact that an actuator fault can destabilize a closed -loop. First, the FTC problem in attitude tracking is transformed into an error-optimal control problem. Next, a cost function based on zero-sum game theory is considered to achieve tracking under the joint influence of state-dependent actuator faults and perturbations. Lyapunov theory has been next used to prove the stability of FTC architecture and the network weight convergence. Benefits of proposed ADP-FTC algorithm is finally highlighted on a numerical benchmark of RV.

关键词： Fault tolerant control Reentry vehicles adaptive dynamic programming Attitude tracking Lyapunov stability

来源：评论

学校读者我要写书评

暂无评论

Fuzzy approximation-based optimal consensus control for nonlinear multiagent systems via adaptive dynamic programming

引用

NEUROCOMPUTING 2023年第1期553卷

作者： Zhao, Heng Wang, Huanqing Xu, Ning Zhao, Xudong Sharaf, Sanaa Bohai Univ Coll Control Sci & Engn Jinzhou 121013 Liaoning Peoples R China Bohai Univ Coll Math Sci Jinzhou 121013 Liaoning Peoples R China Bohai Univ Coll Informat Sci & Technol Jinzhou 121013 Liaoning Peoples R China King Abdulaziz Univ Fac Comp & Informat Technol Dept Comp Sci Jeddah 21589 Saudi Arabia

This paper investigates the fuzzy approximation-based optimal consensus control problem for nonlinear multi agent systems with unknown perturbations. By constructing local error dynamics, the considered optimal consensus problem is reformulated as finding Nash-equilibrium solutions to zero-sum games. Then, by using sliding mode control technology and the concept of hierarchical design, a series of control signals are sequentially designed to regulate the consensus error and minimize the local value function. In addition, an identifier critic architecture is developed by using generalized fuzzy hyperbolic models, where the identifier is employed to relax the requirement for complete system dynamics information, and the hierarchical sliding mode surface based critic network is applied to approximate optimal control inputs. Finally, A simulation example is presented to illustrate the validity of the proposed approach.

关键词： Nonlinear multiagent system Hierarchical sliding-mode control Fuzzy approximation H & INFIN optimal consensus control adaptive dynamic programming

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：