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state estimation for delayed switched positive systems: delayed radius approach

Science China(Information Sciences) 2024年第8期67卷 190-205页

作者： Weizhong CHEN Zhongyang FEI Xudong ZHAO Zheng-Guang WU School of Electronics and Information Xi'an Polytechnic University Research Institute of Intelligent Control and Systems Harbin Institute of Technology Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology School of Control Science and Engineering Dalian University of Technology State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and ControlZhejiang University

In this paper, an interval estimation scheme is developed for delayed switched positive systems（DSPS） with mode-dependent average dwell time switching. A lossless zonotopic estimation approach is proposed for the delayed intersection zonotope with the positive generator matrix. First, considering the existence of asynchronism between the system mode and the correction matrix mode, the mismatched intersection zonotope is constructed for DSPS to verify the consistency between the system model and ***, by utilizing the introduced radius definitions, the ?∞performance is addressed to optimize the size of delayed intersection zonotopes. Subsequently, we present a joint-design approach of switching signals and the mode-dependent correction matrix by constructing positive generator matrix-based delayed radius functions. Furthermore, guaranteed nonnegative state bounds are derived for the considered DSPS based on the proposed lossless zonotopic estimation criteria. Finally, detailed simulations are conducted to validate the feasibility and superiority of the developed methods.

关键词： delayed switched positive systems interval estimation asynchronous correction matrix zonotopes mode-dependent average dwell time

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Command filter-based I&I adaptive control for MIMO uncertain systems with input saturation and disturbances

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Science China(Information Sciences) 2023年第12期66卷 64-79页

作者： Qi HAN Zhitao LIU Hongye SU Xiangbin LIU State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and ControlZhejiang University School of Electronic Information Engineering Beijing Jiaotong University

This paper develops a control strategy based on immersion and invariance(I&I) adaptive methodology for a class of multi-input multi-output(MIMO) systems in the presence of parametric uncertainty, input saturation, and external disturbance. To avoid the analytic calculation in the backstepping process, a highgain auxiliary system is constructed to compensate for the effect of command filter error. The first-order command filters are also employed in the construction procedure of the I&I adaptive law to simplify its design and remove the structural conditions on the regressors. A filter-based disturbance observer is developed to counteract the effect of the external disturbance produced by a partially known exogenous *** overcome the input saturation nonlinearity, a smooth function is introduced to approximate the input saturation with an extended state and a bounding estimation law. Stringent analysis guarantees the stability of closed-loop system. Finally, simulated examples confirm the effectiveness of the suggested method.

关键词： adaptive control command filtered backstepping disturbance observer immersion and invariance MIMO systems

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Spherical robot: A novel robot for exploration in harsh unknown environments

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IET cyber-systems and Robotics 2023年第4期5卷 1-15页

作者： Wei Ren You Wang Haoxiang Liu Song Jin Yixu Wang Yifan Liu Ziang Zhang Tao Hu Guang Li State Key Laboratory of Industrial Control Technology Institute of Cyber Systems and ControlZhejiang UniversityHangzhouChina

The authors propose a complete software and hardware framework for a novel spherical robot to cope with exploration in harsh and unknown *** proposed robot is driven by a heavy pendulum covered by a fully enclosed spherical shell,which is strongly protected,amphibious,anti-overturn and has a *** for location and perception,planning and motion control are comprehensively *** the one hand,the authors fully consider the kinematic model of a spherical robot,propose a positioning algorithm that fuses data from inertial measurement units,motor encoder and Global Navigation Satellite System,improve global path planning algorithm based on Hybrid A*and design an instruction planning controller based on model predictive control(MPC).On the other hand,the dynamic model is built,linear MPC and robust servo linear quadratic regulator algorithm is improved,and a speed controller and a direction controller are *** addition,based on the pose and motion charac-teristics of a spherical robot,a visual obstacle perception algorithm and an electronic image stabilisation algorithm are ***,the authors build physical systems to verify the effectiveness of the above algorithms through experiments.

关键词： mobile robots robot control robot perception robot planning

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Cooperative decision-making algorithm with efficient convergence for UCAV formation in beyond-visual-range air combat based on multi-agent reinforcement learning

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Chinese Journal of Aeronautics 2024年第8期37卷 311-328页

作者： Yaoming ZHOU Fan YANG Chaoyue ZHANG Shida LI Yongchao WANG School of Aeronautic Science and Engineering Beihang UniversityBeijing 100191China Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and ControlZhejiang UniversityHangzhou 310027China

Highly intelligent Unmanned Combat Aerial Vehicle(UCAV)formation is expected to bring out strengths in Beyond-Visual-Range(BVR)air *** Multi-Agent Reinforcement Learning(MARL)shows outstanding performance in cooperative decision-making,it is challenging for existing MARL algorithms to quickly converge to an optimal strategy for UCAV formation in BVR air combat where confrontation is complicated and reward is extremely sparse and *** to solve this problem,this paper proposes an Advantage Highlight Multi-Agent Proximal Policy Optimization(AHMAPPO)***,at every step,the AHMAPPO records the degree to which the best formation exceeds the average of formations in parallel environments and carries out additional advantage sampling according to ***,the sampling result is introduced into the updating process of the actor network to improve its optimization ***,the simulation results reveal that compared with some state-of-the-art MARL algorithms,the AHMAPPO can obtain a more excellent strategy utilizing fewer sample episodes in the UCAV formation BVR air combat simulation environment built in this paper,which can reflect the critical features of BVR air *** AHMAPPO can significantly increase the convergence efficiency of the strategy for UCAV formation in BVR air combat,with a maximum increase of 81.5%relative to other algorithms.

关键词： Unmanned combat aerial vehicle(UCAV)formation Decision-making Beyond-visual-range(BVR)air combat Advantage highlight Multi-agent reinforcement learning(MARL)

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Multi-objective optimization for 10-kW rated power dynamic wireless charging systems of electric vehicles

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Science China(Information Sciences) 2022年第10期65卷 178-195页

作者： Ze ZHOU Zhitao LIU Hongye SU Liyan ZHANG State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University School of Automation Wuhan University of Technology

In this paper, we propose a method to optimize the output power, efficiency, and cost of the dynamic wireless charging(DWC) system of electric vehicles by using the transmitting coil spacing as the decision variable. In a set of transmitting equipment, we adopt a structure with two transmitting networks in parallel and derive loss models. The expressions of the output power and efficiency of the DWC system are obtained by data fitting. In addition, combined with the proposed cost function, we construct a multiobjective optimization problem on output power, efficiency, and cost. Due to the complexity of the objective function, it is difficult to solve the problem by the analytic method, and thus we propose a constrained adaptive particle swarm optimization(CAPSO) algorithm with high accuracy to solve the problem. Finally,the simulation results verify the feasibility of the proposed model. The advantages of the proposed CAPSO algorithm and the optimization results under different weight combinations are presented.

关键词： dynamic wireless charging electric vehicles multi-objective optimization constrained adaptive particle swarm optimization

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An Effective Adaptive Large Neighborhood Search Algorithm for Multi-AGV Dispatching Problem in Matrix Manufacturing systems 21

An Effective Adaptive Large Neighborhood Search Algorithm fo...

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21st International Conference on Networking, Sensing and control, ICNSC 2024

作者： Li, Boyu Wu, Weimin Institute of Cyber-Systems and Control Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou China

ISBN: (纸本)9798350365221

With the increasing prevalence of automated guided vehicles (AGV s) in industry, the AG V dispatching has emerged as a research hotspot. Recently, matrix manufacturing systems (MMS) have been favored for their suitability in mass-customized production. However, fluctuating and diverse transport demands in MMS pose challenges for effective AGV scheduling. This paper investigates a multi-AGV dispatching problem (AGVDP) in MMS, involving time-constrained pick-up and delivery tasks. A mixed-integer linear programming model is developed to minimize total transportation costs, including travel distance, early arrival time, and utilized AGV s. To achieve this, an effective adaptive large neighborhood search algorithm (ALNS) is proposed. In ALNS, a scope-based nearest neighbor heuristic is introduced for initial construction. Diverse problem-specific operators are designed to generate large neighborhoods. To enhance ALNS's robustness to instance variations, an adaptive simulated annealing acceptance criterion is proposed. Computational experiments using a well-established benchmark validate the superiority of the proposed ALNS. © 2024 IEEE.

关键词： Simulated annealing

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Research on Optimization Seeking Method of Transmission Efficiency of Orbital Inspection Robot Based on DWPT System

Research on Optimization Seeking Method of Transmission Effi...

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2024 IEEE Transportation Electrification Conference and Expo, Asia-Pacific, ITEC Asia-Pacific 2024

作者： Chen, Youcheng Liu, Zhitao Xue, Xuchi Su, Hongye Zhejiang University State Key Laboratory Of Industrial Control Technology Institute Of Cyber-Systems And Control Hangzhou China

ISBN: (纸本)9798331529277

In wireless power transmission system, due to the changes of coupling coefficient, load impedance and other factors, it destroys the system constant voltage, constant power output and transmission efficiency optimal working condition. Therefore, this paper proposes an optimization seeking method for the maximum transmission efficiency of the DWPT system of an orbital inspection robot with constant voltage and constant power output. Firstly, the LCC-S topology mathematical model with additional PI control circuit and the convex optimization model of transmission efficiency are established, and the gradient descent algorithm is used to iteratively search for the maximum value of transmission efficiency when the orbital coupling coefficient changes. Then, based on the mutual inductance model between coils, the coupling coefficients are converted into coil inductance parameters L1 and L2, and the coil self-inductance is utilized for matching regulation to keep the transmission efficiency at the optimal value. Finally, in order to further optimize and predict the transmission efficiency, the fitting effects of the four fitting curves of the transmission efficiency are observed by the coefficient of determination and the residual paradigm, and the optimal fitting curves are used to calculate the maximum and average transmission efficiency, which reduces the system transmission loss and improves the charging efficiency. © 2024 IEEE.

关键词： Convex optimization

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Optimal Traffic-Power Flow of Transportation-Microgrid Coupled System Based on Spatiotemporal Coupling

Optimal Traffic-Power Flow of Transportation-Microgrid Coupl...

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2024 China Automation Congress, CAC 2024

作者： Li, Bin Li, Jia Li, Qincheng Liu, Zhitao Su, Hongye The State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou310027 China

ISBN: (纸本)9798350368604

The growing adoption of electric vehicles and dynamic wireless charging has strengthened the spatiotemporal interconnection between the transportation network (TN) and the microgrid (MG). This paper presents an optimal traffic-power flow (OTPF) model for the transportation-microgrid coupled system (TMCS) to enhance the coordination of its operations. The OTPF model is transformed into bi-level programming, with the optimal power flow model of MGs at the upper level and the dynamic traffic assignment model of the TN at the lower level. The upper level is a mixed-integer second-order cone programming, while the lower level is formulated as a dynamic user equilibrium. A fixed-point algorithm is developed to tackle this bi-level programming. Case studies show that the OTPF model of the TMCS can be efficiently solved to capture the spatiotemporal variations of traffic flow and power flow. © 2024 IEEE.

关键词： Second-order cone programming

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Research on Multi-Task Scheduling in Smart Warehouse systems Based on Dual-Task Chains 21

Research on Multi-Task Scheduling in Smart Warehouse Systems...

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21st International Conference on Networking, Sensing and control, ICNSC 2024

作者： Zhang, Chenwei Wu, Weimin Institute of Cyber-Systems and Control Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou310027 China

ISBN: (纸本)9798350365221

With the advancement of warehousing technology, the allocation of multiple tasks in multi-AGV systems has become an important factor in order to decrease task completion time in the warehouse. This paper develops a multi-task scheduling algorithm that employs a dual-task chain approach to maximize task execution benefits. For the multi-task allocation problem, this paper proposes a dual-task chain-based task allocation algorithm (DTTA), which uses the dual-task chain strategy as a mechanism for selecting multiple tasks, taking into consideration derived tasks to enhance solution quality. Simulation experiments show that the proposed algorithm and model perform better than other methods. © 2024 IEEE.

关键词： Scheduling algorithms

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Optimal Prices for Coordinated Operation of Coupled Transportation and Power systems

Optimal Prices for Coordinated Operation of Coupled Transpor...

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2024 China Automation Congress, CAC 2024

作者： Li, Jia Li, Bin Li, Qincheng Liu, Zhitao Su, Hongye State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou310027 China

ISBN: (纸本)9798350368604

The growing adoption of electric vehicles (EVs) necessitates an in-depth analysis of the effects of centralized charging on both traffic congestion and power distribution networks (PDNs). This study presents a coupled model of transportation and power systems that incorporates EV travel behavior and charging costs, emphasizing their interaction between the urban transportation network and the PDN via dynamic wireless energy transmission technology. The equilibrium of the coupled system was then determined through an iterative algorithm aimed at minimizing the total social cost. Example results validate the model’s accuracy and effectiveness. Furthermore, the study demonstrates that the proposed approach can significantly alleviate traffic congestion while simultaneously satisfying the charging needs of EVs and maintaining the stability of the power distribution network. © 2024 IEEE.

关键词： Power distribution networks

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