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A novel motion coordination method for variable-sized multi-mobile robots

Frontiers of Information technology & Electronic Engineering 2023年第4期24卷 521-535页

作者： Zichao XING Xingkai WANG Shuo WANG Weimin WU Ruifen HU State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and ControlZhejiang UniversityHangzhou 310027China

Multi-mobile robot systems(MMRSs)are widely used for transportation in industrial scenes such as manufacturing and *** an MMRS,motion coordination is important as collisions and deadlocks may lead to losses or system ***,in some scenarios,robot sizes are different when loaded and unloaded,which means that the robots are variable-sized,making motion coordination more *** methods based on zone control need to first divide the environment into disjoint zones,and then allocate the zones statically or dynamically for motion *** zone-control-based methods are not accurate enough for variable-sized multi-mobile robots and reduce the efficiency of the *** paper describes a motion coordination method based on glued nodes,which can dynamically avoid collisions and deadlocks according to the roadmap structure and the real-time paths of *** features make this method directly applicable to various scenarios,instead of dividing a roadmap into disjoint *** proposed method has been applied to many industrial projects,and this study is based on some manufacturing projects for *** analysis and experimental results show that the proposed algorithm is effective and efficient.

关键词： Multi-mobile robot system Collision avoidance Deadlock avoidance Glued nodes Motion coordination

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A Novel Trajectory Planning Method Based on Trust Region Policy Optimization

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-15页

作者： Ye, Bao-Lin Zhang, Jiajie Li, Lingxi Wu, Weimin Jiaxing Key Laboratory of Smart Transportations the School of Information Science and Engineering Jiaxing University China Elmore Family School of Electrical and Computer Engineering Purdue University Indianapolis USA State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China

Trajectory planning method is a research hotspot in autonomous driving. Existing reinforcement learning-based trajectory planning methods suffer from unstable performance due to the strong randomness of network weight parameter updates during the training process. Therefore, this paper proposes a novel trajectory planning method based on deep reinforcement learning trust region policy optimization (TRPO). Firstly, in order to enhance the robustness of the trajectory planning method based on deep reinforcement learning TRPO, a TRPO-LSTM based decision model was proposed. More specifically, a long short term memory (LSTM) based state feature extraction network was designed and embeded into a TRPO-based decision model to enhance the ability of TRPO to extract information from the environmental state space. Secondly, in order to make the planned trajectory adaptive to the dynamic changes of traffic environment, we presented a novel TRPO-LSTM trajectory fitting algorithm. To the best of our knowledge, this is the first work aiming at applying the TRPO-LSTM based decision model in the trajectory fitting process to search the optimal longitudinal trajectory speed. Finally, the proposed trajectory planning method was implemented and simulated on the CARLA simulator. The experimental results show that, compared with existing trajectory planning methods based on deep reinforcement learning algorithms, our proposed method achieves a cumulative reward improvement of over 28.9% in the scenario of four lane highway, and has better robustness. Meanwhile, the proposed method can achieve a lower collision rate of 0.93% while improving the average speed and comfort of vehicle driving. IEEE

关键词： Heuristic algorithms

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Distributed event-triggered adaptive control for second-order nonlinear uncertain multi-agent systems

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Chinese Journal of Aeronautics 2021年第10期34卷 237-247页

作者： Ming XIAO Zhitao LIU Hongye SU The State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and ControlZhejiang UniversityHangzhou 310027China

In this paper,the event-triggered consensus control problem for nonlinear uncertain multi-agent systems subject to unknown parameters and external disturbances is *** dynamics of subsystems are second-order with similar structures,and the nodes are connected by undirected *** event-triggered mechanisms are not only utilized in the transmission of information from the controllers to the actuators,and from the sensors to the controllers within each agent,but also in the communication between *** on the adaptive backstepping method,extra estimators are introduced to handle the unknown parameters,and the measurement errors that occur during the event-triggered communication are well handled by designing compensating terms for the control *** presented distributed event-triggered adaptive control laws can guarantee the boundness of the consensus tracking errors and the Zeno behavior is ***,the update frequency of the controllers and the load of communication burden are vastly *** obtained control protocol is further applied to a multi-input multi-output second-order nonlinear multi-agent system,and the simulation results show the effectiveness and advantages of our proposed method.

关键词： Adaptive distributed control structure Event-triggered control Multi-agent systems Second-order nonlinear models

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Review of Clustering technology and Its Application in Coordinating Vehicle Subsystems

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Automotive Innovation 2023年第1期6卷 89-115页

作者： Caizhi Zhang Weifeng Huang Tong Niu Zhitao Liu Guofa Li Dongpu Cao Chongqing Automotive Collaborative Innovation Centre The State Key Laboratory of Mechanical TransmissionsChongqing UniversityChongqing 400044China State Key Laboratory of Industrial Control Technology Institute of Cyber‑Systems and ControlZhejiang UniversityHangzhou 310027China School of Vehicle and Mobility Tsinghua UniversityBeijingChina

Clustering is an unsupervised learning technology,and it groups information(observations or datasets)according to similarity *** clustering algorithms is a hot topic in recent years,and this area develops rapidly with the increasing complexity of data and the volume of *** this paper,the concept of clustering is introduced,and the clustering technologies are analyzed from traditional and modern ***,this paper summarizes the principles,advantages,and disadvantages of 20 traditional clustering algorithms and 4 modern ***,the core elements of clustering are presented,such as similarity measures and evaluation *** that data processing is often applied in vehicle engineering,finally,some specific applications of clustering algorithms in vehicles are listed and the future development of clustering in the era of big data is *** purpose of this review is to make a comprehensive survey that helps readers learn various clustering algorithms and choose the appropriate methods to use,especially in vehicles.

关键词： Unsupervised learning Clustering Similarity measures Vehicle

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Obstacle Avoidance for Unicycle-Modelled Mobile Robots with Time-Varying control Barrier Functions 49

Obstacle Avoidance for Unicycle-Modelled Mobile Robots with ...

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49th Annual Conference of the IEEE industrial Electronics Society, IECON 2023

作者： Huang, Jihao Liu, Zhitao Zeng, Jun Chi, Xuemin Su, Hongye Institute of Cyber-Systems and Control Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou China Cruise Llc United States

ISBN: (纸本)9798350331820

In this paper, we propose a safety-critical controller based on time-varying control barrier functions (CBFs) for a robot with an unicycle model in the continuous-time domain to achieve navigation and dynamic collision avoidance. Unlike previous works, our proposed approach can control both linear and angular velocity to avoid collision with obstacles, overcoming the limitation of confined control performance due to the lack of control variable. To ensure that the robot reaches its destination, we also design a control Lyapunov function (CLF). Our safety-critical controller is formulated as a quadratic program (QP) optimization problem that incorporates CLF and CBFs as constraints, enabling real-time application for navigation and dynamic collision avoidance. Numerical simulations are conducted to verify the effectiveness of our proposed approach. © 2023 IEEE.

关键词： Lyapunov functions

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Interval Weight state Update Approach with Deep Reinforcement Learning for Dynamic Load Change Tasks in Air Separation Processes 13

Interval Weight State Update Approach with Deep Reinforcemen...

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13th IEEE Data Driven control and Learning systems Conference, DDCLS 2024

作者： Qiu, Ruiyu Yang, Guanghui Xu, Zuhua Shao, Zhijiang College of Control Science and Engineering Zhejiang University State Key Lab of Industrial Control Technology Hangzhou310027 China HuZhou Research Institute of Industrial Control Technology China

ISBN: (纸本)9798350361674

The air separation unit (ASU) is important for producing high-purity oxygen, nitrogen, and argon, and dynamic load change operation helps meet the needs of downstream industries. The ASU has an extremely long delay, and the requirements for this operation are strict, and model predictive control (MPC) is usually used for this task. However, the burden of online MPC computation is a key issue in improving production and economic efficiency. In this paper, a framework based on Reinforcement Learning (RL) is proposed to solve the long-delayed task in ASU. The state and reward function are specially designed for this task. First, training increases the sampling time of the original model to create a low resolution environment, which makes training more efficient. As a sacrifice, the control precision is reduced in the original high resolution environment. Then, an algorithm called Interval Weighted state Update (IWSU) is proposed to restore the agent and keeps the action accuracy in the original environment. The dynamic load change task works as the case in this paper. The performance of RL is compared with that of MPC, and results show that RL is almost exactly the same as MPC in key flow indicators, and can well meet the remaining content and purity range requirements. IWSU shows good performance compared with directly applying the agent to the original high resolution environment. © 2024 IEEE.

关键词： Deep reinforcement learning

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Data-driven consensus control of fully distributed event-triggered multi-agent systems

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Science China(Information Sciences) 2023年第5期66卷 147-161页

作者： Yifei LI Xin WANG Jian SUN Gang WANG Jie CHEN School of Automation Beijing Institute of Technology The State Key Lab of Autonomous Intelligent Unmanned Systems Beijing Institute of Technology Beijing Institute of Technology Chongqing Innovation Center Department of Control Science and Engineering Tongji University

This study investigates the consensus control issue in discrete-time linear multi-agent systems(MASs) using data-driven control under undirected communication networks. To alleviate the communication burden, an adaptive event-triggered control strategy involving only local information is proposed and a model-based stability condition is derived that guarantees the asymptotic consensus of MASs. Furthermore,a data-based consensus condition for unknown MASs is established by combining a data-based system representation with the model-based stability condition, using only pre-collected noisy input-state data instead of the accurate system information a priori. Specifically, both model-based and data-driven event-triggered controllers can be utilized without requiring any global information. The validity and correctness of the controllers and associated theoretical results are demonstrated via numerical simulations.

关键词： distributed control event-triggered control data-driven control discrete-time MASs

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Invariant EKF based state Estimator for Quadruped Robots 42

Invariant EKF based State Estimator for Quadruped Robots

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42nd Chinese control Conference, CCC 2023

作者： Zhang, Zhuqing Li, Zhang Chen, Yong Wang, Dongqi Yu, Jiyu Xiong, Rong Wang, Yue Zhejiang University State Key Laboratory of Industrial Control Technology and Institute of Cyber-Systems and Control Hangzhou310027 China Research Institute of Nuclear Power Operation Wuhan China

ISBN: (纸本)9789887581543

Quadruped robots have gained much attention in recent years due to their potential ability to handle various kinds of terrain. To control the quadruped robots to perform tasks, high frequency (up to 400Hz) state estimation is demanded. In this paper, we introduce an accurate and efficient state estimator by incorporating IMU measurements and quadruped robot joint encoder measurements. To be specific, we utilize the IMU measurements to propagate the state, while the joint encoder measurements are used to derive the foot position of the robot to update the state. The whole process is based on an invariant EKF, which is proved in this paper to be able to preserve the correct observability of the system. Moreover, based on the estimated state, the inclination of the terrain with respect to the horizontal plane can be calculated, which is useful for downstream control. Experiments are conducted to validate the effectiveness of our proposed state estimator. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： state estimation

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state estimation for delayed switched positive systems: delayed radius approach

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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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Detection of Stealthy False Data Injection Attacks Against cyber-Physical systems:A Stochastic Coding Scheme

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Journal of systems Science & Complexity 2022年第5期35卷 1668-1684页

作者： GUO Haibin PANG Zhonghua SUN Jian LI Jun State Key Lab of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China Beijing Institute of Technology Chongging Innovation Center Chongqing 401120China Key Laboratory of Fieldbus Technology and Automation of Beijing North China University of TechnologyBeijing 100144China China Industrial Control Systems Cyber Emergency Response Team Beijing 100040China

This paper,from the view of a defender,addresses the security problem of cyber-physical systems(CPSs)subject to stealthy false data injection(FDI)attacks that cannot be detected by a residual-based anomaly detector without other defensive *** detect such a class of FDI attacks,a stochastic coding scheme,which codes the sensor measurement with a Gaussian stochastic signal at the sensor side,is proposed to assist an anomaly detector to expose the FDI *** order to ensure the system performance in the normal operational context,a decoder is adopted to decode the coded sensor measurement when received at the controller *** this detection scheme,the residual under the attack can be significantly different from that in the normal situation,and thus trigger an *** design condition of the coding signal covariance is derived to meet the constraints of false alarm rate and attack detection *** minimize the trace of the coding signal covariance,the design problem of the coding signal is converted into a constraint non-convex optimization problem,and an estimation-optimization iteration algorithm is presented to obtain a numerical solution of the coding signal covariance.A numerical example is given to verify the effectiveness of the proposed scheme.

关键词： Attack detection cyber-physical systems(CPSs) stealthy FDI attacks stochastic coding

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