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Reinforcement learning for optimal tracking of large-scale systems with multitime scales

Science China(Information Sciences) 2023年第7期66卷 5-29页

作者： Jinna LI Hao NIE Tianyou CHAI Frank L.LEWIS School of Information and Control Engineering Liaoning Petrochemical University State Key Laboratory of Synthetical Automation for Process Industries Northeastern University UTA Research Institute University of Texas at Arlington

This paper aims to solve an optimal tracking control(OTC) problem of large-scale systems with multitime scales and coupled subsystems using singular perturbation(SP) theory and reinforcement learning(RL) techniques. A considerable contribution of this paper is the development of a data-driven SP-based RL method for the OTC of unknown large-scale systems with multitime scales. To achieve this, a multitime scale tracking problem was decomposed into a linear quadratic tracker problem for slow subsystems and a dynamical game problem for fast subsystems using the SP theory. Then, the distributed composite feedback controllers were found using a distributed off-policy integral RL algorithm that uses only measured data from the system in real time. Thus, the operational index can follow its prescribed target value via an approximately optimal approach. Theoretical analysis and proof are presented to demonstrate that the sum of the performances of reduced-order subsystems is approximately equal to the performance of the original large-scale system. Finally, numerical and practical examples are provided to validate the effectiveness of the proposed method.

关键词： reinforcement learning singular perturbation multitime scales data-driven control

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Rolling Bearing Fault Diagnosis Based on MTF Encoding and CBAM-LCNN Mechanism

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Computers, Materials & Continua 2025年第3期82卷 4863-4880页

作者： Wei Liu Sen Liu Yinchao He Jiaojiao Wang Yu Gu School of Mechanical and Electrical Engineering Zhoukou Normal UniversityZhoukou466001China School of Information and Control Engineering Jilin Institute of Chemical TechnologyJilin132022China School of Automation Guangdong University of Petrochemical TechnologyMaoming525000China

To address the issues of slow diagnostic speed,low accuracy,and poor generalization performance in traditional rolling bearing fault diagnosis methods,we propose a rolling bearing fault diagnosis method based on Markov Transition Field(MTF)image encoding combined with a lightweight convolutional neural network that integrates a Convolutional Block Attention Module(CBAM-LCNN).Specifically,we first use the Markov Transition Field to convert the original one-dimensional vibration signals of rolling bearings into two-dimensional ***,we construct a lightweight convolutional neural network incorporating the convolutional attention module(CBAM-LCNN).Finally,the two-dimensional images obtained from MTF mapping are fed into the CBAM-LCNN network for image feature extraction and fault *** validate the effectiveness of the proposed method on the bearing fault datasets from Guangdong University of Petrochemical Technology’s multi-stage centrifugal fan and Case Western Reserve *** results show that,compared to other advanced baseline methods,the proposed rolling bearing fault diagnosis method offers faster diagnostic speed and higher diagnostic *** addition,we conducted experiments on the Xi’an Jiaotong University rolling bearing dataset,achieving excellent results in bearing fault *** results validate the strong generalization performance of the proposed *** method presented in this paper not only effectively diagnoses faults in rolling bearings but also serves as a reference for fault diagnosis in other equipment.

关键词： Rolling bearing fault diagnosis markov transition field lightweight convolutional neural network convolutional block attention module

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Discretization-Chattering-Free Implementation of Arbitrary-Order Sliding Mode controllers 63

Discretization-Chattering-Free Implementation of Arbitrary-O...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Andritsch, Benedikt Watermann, Lars Koch, Stefan Reichhartinger, Markus Reger, Johann Horn, Martin Institute of Automation and Control Graz University of Technology Graz Austria Technische Universität Ilmenau Control Engineering Group Ilmenau Germany

ISBN: (纸本)9798350316339

In this paper an implementation of sliding mode control for disturbed integrator chains that does not suffer from the discretization chattering effect is presented. The method is based on an Euler forward discretization of the sliding mode controller. In a vicinity of the origin, that properly scales with the discretization time, the controller is altered to eliminate discretization chattering which can also improve the control accuracy. Finite-time stability of the origin is proven in the absence of a disturbance. In the disturbed case boundedness of the control error is shown. The control actuation is shown to be locally bounded. Exemplary applications to first- and second-order sliding mode control show the effectiveness of the method. © 2024 IEEE.

关键词： Sliding mode control

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Human Cognitive Learning in Shared control via Differential Game With Bounded Rationality and Incomplete Information

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第10期5卷 5141-5152页

作者： Wu, Huai-Ning Jiang, Xiao-Yan Wang, Mi Beihang University Science and Technology on Aircraft Control Laboratory School of Automation Science and Electrical Engineering Beijing100191 China Hangzhou International Innovation Institute of Beihang University Hangzhou311115 China Beihang University School of Automation Science and Electrical Engineering Beijing100191 China

Since human beings are of limited reasoning ability as well as the machines do not usually know human intentions, how to learn human cognitive levels in shared control to enhance the machines’ intelligence is a challenging issue. In this study, this issue is addressed in the context of human–machine shared control for a class of human-in-the-loop (HiTL) systems based on a differential game with bounded rationality and incomplete information. Initially, we formulate the human–machine shared control problem as a two-player nonzero-sum linear quadratic dynamic game (LQDG), where the weighting matrix of the cost function representing the human intention is unknown for the machine. To model the human bounded rationality, the level-k (LK) approach is employed to set up the LK control policies of two players performing the corresponding steps of strategic thinking. To infer the human intention, an online adaptive inverse optimal control (IOC) algorithm is then developed by using the system state data, so that the control policies of different cognitive levels can be computed. In addition, a reinforcement learning method is proposed for the machine to identify the distribution of the human cognitive levels while providing a proactive collaborative control to assist the human in a probabilistic switching way. Finally, simulation results on a cooperative shared control driver assistance system (DAS) illustrate the efficacy of the proposed approach. © 2024 IEEE.

关键词： Game theory

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Reachable set estimation for spacecraft relative motion based on bang-bang principle

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Chinese Journal of Aeronautics 2023年第2期36卷 229-240页

作者： Lizhen SHAO Haibin MIAO Renhong HU Hongjin LIU Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education School of Automation and Electrical EngineeringUniversity of Science and Technology BeijingBeijing 100083China Shunde Graduate School of University of Science and Technology Beijing 100083China School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen 528399China Beijing Institute of Control Engineering Beijing 100190China Beijing Sunwise Space Technology Ltd. Beijing 100190China

For spacecraft formation flight,the information of relative motion reachable set is very important,which can be used to predict the operating boundary of adjacent spacecraft and thus to ensure the safety of spacecraft *** this paper,we aim at developing a numerical method to approximate the reachable set for spacecraft relative *** particular,we focus on the quality of the approximation and the computational *** on the bang-bang control principle,a polyhedral approximation algorithm is proposed to compute the reachable set of a relative motion spacecraft *** inner approximation and an outer approximation of the reachable set for the system can be *** prove that the approximation quality measured in Hausdorff distance can be *** method is easy to implement and has low computational ***,the effectiveness of the algorithm is demonstrated by experimental simulation.

关键词： Polyhedral approximation Reachable set Spacecraft control Spacecraft relative motion The bang-bang control principle

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Silicon Optical Filter With Widely Tunable Bandwidth Driving by Intelligent Algorithms

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Journal of Lightwave Technology 2025年第11期43卷 5358-5365页

作者： Duan, Jiazhu Liu, Cangli Zhang, Dayong Zhao, Xiangjie Liu, Li China Academy of Engineering Physics Institute of Fluid Physics Mianyang621900 China China Academy of Engineering Physics Mianyang621900 China China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China

Capitalizing two silicon rings assisted a Mach-Zehnder interferometer (MZI) structure, we propose and demonstrate picometer narrowband optical filters featuring widely tunable bandwidths, high extinction ratios and low in-band ripples. By tuning the bandwidth of any ring or the resonance offset between the two rings, the filter bandwidth could be flexibly manipulated. Notably, by controlling the phase of the two rings and the MZI structures, the extinction ratios and shape factors of the filter could be commendably improved. It is worth mentioning that a genetic algorithm is employed to efficiently manipulate the various heaters on the optical filter, enabling the attainment of desired target filtering waveforms. Experimental results demonstrate the filter capability to widely adjust its 3dB-bandwidth while maintaining high extinction ratios, low in-band ripples and favorable shape factors. To the best of our knowledge, it is a record bandwidth tuning range among the algorithm-driven pm-narrowband optical filters. With the dominant advantages and high performance, the proposed optical filters are competent to dynamically process the on-chip narrowband signals. © 1983-2012 IEEE.

关键词： Mach-Zehnder interferometers

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Simulation Method for Reliability Prediction of Switching Power Supply injected with PoF Model 6

Simulation Method for Reliability Prediction of Switching Po...

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6th International Conference on System Reliability and Safety engineering, SRSE 2024

作者： Xiao, Kaiwen Chen, Cen Liu, Weiming Wang, Shujuan Gao, Xiaoying Zhai, Guofu Harbin Institute of Technology Department of Electrical Engineering & Automation Harbin China Beijing Aerospace Automatic Control Institute Beijing China

ISBN: (纸本)9798350356083

Switching power supplies are widely used in aerospace, new energy and many other fields. During long-term operation, various electronic components in these supplies experience performance degradation due to continuous electrical and thermal stress, leading to changes in output characteristics. This is the fundamental reason affecting the reliability of switching power supplies. However, the current combination of physics of failure (PoF) models and simulation technique is imperfect, and most methods cannot achieve batch injection of multiple device failures. This paper proposes a reliability prediction simulation method for switching power supplies based on PoF model injection. By focusing on a switching circuit, the approach involves digital twin modeling and validation, failure mechanism and sensitivity analysis, key failure components degradation modeling, and batch degradation simulation. This method achieves continuous degradation data of multiple components based on the PoF model through batch injection, improving the efficiency and accuracy of reliability prediction for switching power supplies. © 2024 IEEE.

关键词： Sensitivity analysis

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Knowledge-based Retrieval Methods for Enhancing Aerospace Model Software Documentation 24

Knowledge-based Retrieval Methods for Enhancing Aerospace Mo...

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3rd International Conference on Artificial Intelligence and Intelligent Information Processing, AIIIP 2024

作者： Duan, Jinjian Wei, Deming Wang, Meiqing Chen, Gaohui Zhang, Yang Gao, Yanhua School of Mechanical Engineering and Automation Beihang University Beijing China Beijing Institute of Control and Electronic Technology Beijing China

ISBN: (纸本)9798400707308

Addressing the critical challenges of poor structure, weak relevance, and limited reusability in aerospace model software development documents, we propose a knowledge-based retrieval method. This method constructs a knowledge base by analyzing key document features, including storage methods, file formats, content structure, inter-document associations, and naming conventions. The system implements structured document management and associates documents based on software configuration information. By partitioning the retrieval domain, constructing semantic vectors, and applying multi-dimensional weight configurations, the method enables efficient retrieval in domains characterized by dense information and frequent term repetition. An aerospace model software document retrieval system has been developed and preliminarily implemented in an aerospace enterprise, demonstrating its effectiveness in improving retrieval efficiency and enhancing the reuse of development knowledge. © 2024 Copyright held by the owner/author(s).

关键词： Content based retrieval

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Relaxed Stability Criteria for Time-Delay Systems:A Novel Quadratic Function Convex Approximation Approach

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 996-1006页

作者： Shenquan Wang Wenchengyu Ji Yulian Jiang Yanzheng Zhu Jian Sun College of Electrical and Electronic Engineering Changchun University of TechnologyChangchun 130012China the College of Electrical Engineering and Automation Shandong University of Science and TechnologyQingdao 266590China Key Laboratory of Complex Systems Intelligent Control and Decision Beijing Institute of TechnologyBeijing 100081China

This paper develops a quadratic function convex approximation approach to deal with the negative definite problem of the quadratic function induced by stability analysis of linear systems with time-varying *** introducing two adjustable parameters and two free variables,a novel convex function greater than or equal to the quadratic function is constructed,regardless of the sign of the coefficient in the quadratic *** developed lemma can also be degenerated into the existing quadratic function negative-determination(QFND)lemma and relaxed QFND lemma respectively,by setting two adjustable parameters and two free variables as some particular ***,for a linear system with time-varying delays,a relaxed stability criterion is established via our developed lemma,together with the quivalent reciprocal combination technique and the Bessel-Legendre *** a result,the conservatism can be reduced via the proposed approach in the context of constructing Lyapunov-Krasovskii functionals for the stability analysis of linear time-varying delay ***,the superiority of our results is illustrated through three numerical examples.

关键词： Equivalent reciprocal combination technique quadratic function convex approximation approach stability timevarying delay

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Fixed-time sliding mode control of QUAV attitude system based on disturbance observer

Fixed-time sliding mode control of QUAV attitude system base...

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2024 China automation Congress, CAC 2024

作者： Gao, Yunjie Zhou, Yingjiang Jiang, Guoping Lu, Ming Fan, Zhihao School of Automation and Artificial Intelligence Nanjing University of Posts and Telecommunications China Beijing Institute of Control Engineering China

ISBN: (纸本)9798350368604

In this paper, the fixed-time stability of the attitude system of a quadrotor unmanned aerial vehicle (QUAV) under external time-varying disturbance is investigated. A novel disturbance observer with state dependent variables as exponents is designed to estimate time-varying perturbations. Subsequently, a fixed-time controller is engineered to achieve fixed-time convergence of the QUAV’s attitude system. The efficacy of the proposed algorithm is validated through numerical simulation. © 2024 IEEE.

关键词： Sliding mode control

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