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第33届中国控制与决策会议

作者： Jiangbo Zhao Jiaquan Zhang Junzheng Wang Xin Zhang Yanlong Wang Key Laboratory of Complex System Intelligent Control and Decision School of AutomationBeijing Institute of Technology Key Laboratory of Servo Motion System Drive and Control Ministry of Industry and Information TechnologySchool of AutomationBeijing Institute of Technology Technical center Xinxing Cathay International Group Co.Ltd. Techenology Center of Special Vehicle Manufacture and Evaluation Engineering of Beijing Beijing North Vehicle Group Co.Ltd.

Local path planning algorithm is one of the key technologies for unmanned ground vehicle(UGV).In order to reduce the computational complexity of the local path planning algorithm and ensure the real-time performance of the algorithm,a non-uniform column grid lines modeling method is introduced,and on this basis,a modeling method for planning paths is *** at the path planning problem in a multi-obstacle environment,the evaluation function of the path is constructed from four aspects,and the covariance matrix adaptive evolution strategy(CMA-ES)is used to solve the nonlinear optimization *** order to further reduce the amount of calculation,the CMA-ES algorithm is improved by the dynamic adjustment strategy of population *** results show that the path planning algorithm can effectively realize the local path planning in complex environment.

关键词： Local path planning CMA-ES Unmanned ground vehicle

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Attitude stability control for Multi-Agent Six Wheel-Legged Robot

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IFAC-PapersOnLine 2020年第2期53卷 9636-9641页

作者： Zhihua Chen Shoukun Wang Junzheng Wang Kang Xu Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing CO 100081.P.R.China Beijing Institute of Technology Beijing CO 100081.P.R.China

Multi wheeled-legged robot systems are MIMO complex systems with multi information fusion. In this paper, a multi-sensor information fusion based wheeled-legged cooperative control strategy is proposed to solve the problem of attitude stability control for the six wheeled-legged robot-BIT-NAZA-II. First, when the robot is wheel motion, the overall attitude of the robot is adjusted by controlling the vertical degree of freedom(DOF) for the Stewart platform. Second, when the wheel movement is on uneven road, the foot end is easy to be suspended or raised. The impedance control method based on the position inner loop is used to solve the problem of leg suspension or raised. Third, in order to ensure the maximum motion space of single leg, the central height controller is designed. Moreover, the control strategy is mainly completed by the central CPU and six bottom CPUs. Six bottom CPUs receive the force information of each leg, and calculate the position of each leg by combining the impedance controller. Meanwhile, the central CPU receives the attitude angle information, calculates the position of each leg by using the attitude controller, takes two different position commands as the input of the central height controller, outputs the calculated position of the central height controller to six bottom CPUs through UPD communication, and the bottom CPU is used to calculate the variation of Stewart platform DOF. Finally, the experimental results of the control strategy in the six wheeled-legged robot system are given, and the feasibility and effectiveness of the control strategy are verified.

关键词： wheeled-legged robot cooperative control attitude stability control CPU controller design

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Path Planning and Evaluation for Obstacle Avoidance of Manipulator Based on Improved Artificial Potential Field and Danger Field

Path Planning and Evaluation for Obstacle Avoidance of Manip...

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第33届中国控制与决策会议

作者： Jiangbo Zhao Qiang Zhao Junzheng Wang Xin Zhang Yanlong Wang Key Laboratory of Complex System Intelligent Control and Decision School of AutomationBeijing Institute of Technology Key Laboratory of Servo Motion System Drive and Control Ministry of Industry and Information TechnologySchool of AutomationBeijing Institute of Technology Technical center Xinxing Cathay International Group Co.Ltd. Technology Center of Special Vehicle Manufacture and Evaluation Enginneering of Beijing Beijing North Vehicle Group Co.Ltd.

This paper takes 6-DOF manipulator as the research object,proposes the improved Artificial Potential Field(APF) method to plan the obstacle avoidance path of the manipulator,and combines the Danger Field(DF) method to evaluate the safety of the path planned using *** to the characteristics of the manipulator,the kinematics model of the manipulator is analyzed,and the ball envelope algorithm is applied to simplify the physical model of the *** with the traditional APF method,the improved APF searches in the joint space and introduces the joint attraction potential to improve the search speed and *** problem of local minimum is dealt with by the combination of adding virtual obstacles and increasing joint attraction *** improved APF not only has the advantages of good real-time performance and smooth path,but also solves the problem of the traditional APF falling into a local minimum,and combines the danger field method to judge the path rationality to ensure no collision with *** simulation verification,the proposed method realizes the obstacle avoidance path planning of the manipulator and the safety evaluation of the planned path.

关键词： Artificial potential field Danger field Obstacle avoidance Path planning Collision detection

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Research on Vibration Isolation control of Six wheel-legged Robot Based on Impedance control

Research on Vibration Isolation Control of Six wheel-legged ...

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第三十九届中国控制会议

作者： Binkai Yue Shoukun Wang Zhihua Chen Kang Xu Junzheng Wang Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Key Laboratory of Servo Motion System Drive and Control Ministry of Industry and Information Technology School of Automation Beijing Institute of Technology

The electric parallel six wheel-legged robot（EPSWLR） is characterized by heavy load and fast moving speed. But the body will shake and vibrate while passing through rough roads, which affects its stability. In order to solve this problem, the single-leg structure based on Stewart structure was equivalent to the impedance system composed of mass block, spring and damping in this paper. Due to changes in environmental forces and environmental impedance parameters caused by environmental changes, the traditional impedance control（IC） still causes force error at the foot end of robot and thus results in poor vibration isolation effect. Therefore, a new adaptive algorithm was proposed in this paper and added to IC algorithm to reduce the force error caused by environmental changes and thus improve the vibration isolation effect. In this paper, the characteristic equation of adaptive impedance control（AIC） algorithm was first obtained and the condition for system stability was calculated based on Routh-Hurwitz stability criterion. Finally, the stability of this system was verified. The simulation experiment combining MATLAB and Adams was designed and performed with EPSWLR. The effectiveness of AIC was proved by monitoring the changes in the force of single leg and the attitude of robot body.

关键词： Electric parallel six wheel-legged robot Impedance control Adaptive algorithm Stewart structure

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Security of Networked control systems with Incomplete Information Based on Game Theory

Security of Networked Control Systems with Incomplete Inform...

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第三十九届中国控制会议

作者： Lei Gao Jian Sun Jun Li Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing Institute of Technology Chongqing Innovation Center China Industrial Control Systems Cyber Emergency Response Team

The security problem of networked control systems（NCSs） suffering denial of service（DoS） attacks with incomplete information is investigated in this paper. Data transmission among different components in NCSs may be blocked due to DoS attacks. We use the concept of security level to describe the degree of security of different components in an NCS. Intrusion detection system（IDS） is used to monitor the invalid data generated by DoS attacks. At each time slot, the defender considers which component to monitor while the attacker considers which place for invasion. A one–shot game between attacker and defender is built and both the complete information case and the incomplete information case are considered. Furthermore, a repeated game model with updating beliefs is also established based on the Bayes’ rule. Finally, a numerical example is provided to illustrate the effectiveness of the proposed method.

关键词： Networked control systems Security DoS attacks Game theory Incomplete information

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Distance- And velocity-based collision avoidance for time-varying formation control of second-order multi-agent systems

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IEEE Transactions on Circuits and systems II: Express Briefs 2021年第4期68卷 1253-1257页

作者： Pang, Zhong-Hua Zheng, Chang-Bing Sun, Jian Han, Qing-Long Liu, Guo-Ping Key Laboratory of Fieldbus Technology and Automation of Beijing North China University of Technology Beijing100144 China State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China School of Software and Electrical Engineering Swinburne University of Technology MelbourneVIC3122 Australia Department of Artificial Intelligence and Automation Wuhan University Wuhan430072 China

This brief addresses the time-varying formation control problem with collision avoidance for second-order multi-agent systems. By taking both distances and velocities between agents into account, a novel collision avoidance scheme is proposed on the basis of conventional distance-based artificial potential field methods. Compared with the latter, the proposed scheme can more accurately determine possible collision situations and thus significantly reduce possible collision areas, which consequently not only can reduce energy consumption, but also has as few adverse effects on formation maintenance as possible. Then a time-varying formation control protocol is designed so as to achieve zero steady-state position and velocity formation tracking errors without collision. Finally, theoretical analysis, numerical demonstration, as well as comparative simulation are provided to verify the effectiveness of the proposed method. © 2004-2012 IEEE.

关键词： Multi agent systems

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Evasion strategies of a three-player lifeline game

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Science China(Information Sciences) 2018年第11期61卷 144-154页

作者： Fan ZHANG Wenzhong ZHA School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex System Information Science Academy China Electronics Technology Group Corporation

This study examines a multi-player pursuit-evasion game, more specifically, a three-player lifeline game in a planar environment, where a single evader is tasked with reaching a lifeline prior to capture. A decomposition method based on an explicit policy is proposed to address the game qualitatively from two main aspects:(1) the evader's position distribution to guarantee winning the game(i.e., the escape zone),which is based on the premise of knowing the pursuers' positions initially, and(2) evasion strategies in the escape zone. First, this study decomposes the three-player lifeline game into two two-player sub-games and obtains an analytic expression of the escape zone by constructing a barrier, which is an integration of the solutions of two sub-games. This study then explicitly partitions the escape zone into several regions and derives an evasion strategy for each region. In particular, this study provides a resultant force method for the evader to balance the active goal of reaching the lifeline and the passive goal of avoiding capture. Finally,some examples from a lifeline game involving more than one pursuer are used to verify the effectiveness and scalability of the evasion strategies.

关键词： lifeline game three-player pursuit-evasion game barrier evasion strategy game of kind

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Online reinforcement learning control by direct heuristic dynamic programming: from time-driven to event-driven

arXiv

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arXiv 2020年

作者： Zhao, Qingtao Si, Jennie Sun, Jian Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing100081 China Department of Electrical Computer and Energy Engineering Arizona State University TempeAZ85287 United States

In this paper time-driven learning refers to the machine learning method that updates parameters in a prediction model continuously as new data arrives. Among existing approximate dynamic programming (ADP) and reinforcement learning (RL) algorithms, the direct heuristic dynamic programming (dHDP) has been shown an effective tool as demonstrated in solving several complex learning control problems. It continuously updates the control policy and the critic as system states continuously evolve. It is therefore desirable to prevent the time-driven dHDP from updating due to insignificant system event such as noise. Toward this goal, we propose a new event-driven dHDP. By constructing a Lyapunov function candidate, we prove the uniformly ultimately boundedness (UUB) of the system states and the weights in the critic and the control policy networks. Consequently we show the approximate control and cost-to-go function approaching Bellman optimality within a finite bound. We also illustrate how the event-driven dHDP algorithm works in comparison to the original time-driven dHDP. Copyright © 2020, The Authors. All rights reserved.

关键词： Learning algorithms

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Multi-UAV 3D Path Planning in Simultaneous Attack

Multi-UAV 3D Path Planning in Simultaneous Attack

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International Conference on control and Automation (ICCA)

作者： Chuyi Xiong Bin Xin Miao Guo Yulong Ding Hao Zhang School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China

ISBN: (数字)9781728190938

ISBN: (纸本)9781728190945

As the key technology of UAV mission planning, path planning has a very important impact on the combat effectiveness of UAV. In order to destroy enemy units, multiple UAVs are often needed to attack the target at the same time. In the complex combat environment, the path planning of multiple UAVs is a very complex problem. On the basis of genetic algorithm, this paper designs a path planning algorithm to ensure that multiple UAVs arrive at the same time from different angles on the premise of satisfying environment constraints and the motion constraints of UAV. The algorithm uses the method of regionalization to initialize the path, designs a reasonable fitness function, and adds an adaptive disturbance operator to plan the path of each UAV. Finally, the length difference between the paths planned for each UAV is taken as the path evaluation factor. Some of the paths are replanned to achieve the goal of the same path length and simultaneous attack by UAV. The effectiveness of the algorithm is verified by experiments in typical combat scenarios, and the superiority of the adaptive disturbance operator in the optimization of the algorithm is verified by the contrast experiment.

关键词： Path planning Radar Planning Optimization Radar detection Genetic algorithms Three-dimensional displays

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A Learning Convolutional Neural Network Approach for Network Robustness Prediction

arXiv

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arXiv 2022年

作者： Lou, Yang Wu, Ruizi Li, Junli Wang, Lin Li, Xiang Chen, Guanrong The Department of Computing and Decision Sciences Lingnan University Hong Kong The Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China The College of Computer Science Sichuan Normal University Chengdu610066 China The Department of Automation Shanghai Jiao Tong University Shanghai200240 China The Institute of Complex Networks and Intelligent Systems Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai201210 China The Department of Control Science and Engineering Tongji University Shanghai200240 China The Department of Electrical Engineering City University of Hong Kong Hong Kong

Network robustness is critical for various societal and industrial networks again malicious attacks. In particular, connectivity robustness and controllability robustness reflect how well a networked system can maintain its connectedness and controllability against destructive attacks, which can be quantified by a sequence of values that record the remaining connectivity and controllability of the network after a sequence of node- or edge-removal attacks. Traditionally, robustness is determined by attack simulations, which are computationally very time-consuming or even practically infeasible. In this paper, an improved method for network robustness prediction is developed based on learning feature representation using convolutional neural network (LFR-CNN). In this scheme, higher-dimensional network data are compressed to lower-dimensional representations, and then passed to a CNN to perform robustness prediction. Extensive experimental studies on both synthetic and real-world networks, both directed and undirected, demonstrate that 1) the proposed LFR-CNN performs better than other two state-of-the-art prediction methods, with significantly lower prediction errors;2) LFR-CNN is insensitive to the variation of the network size, which significantly extends its applicability;3) although LFR-CNN needs more time to perform feature learning, it can achieve accurate prediction faster than attack simulations;4) LFR-CNN not only can accurately predict network robustness, but also provides a good indicator for connectivity robustness, better than the classical spectral measures. © 2022, CC BY.

关键词： complex networks

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