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

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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Research on Foot Trajectory Tracking of Parallel Wheel-legged Robot based on Dynamic Model Predictive control

Research Square

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Research Square 2020年

作者： Liu, Daohe Wang, Shoukun Chen, Zhihua Wang, Junzheng Key Laboratory of Complex System Intelligent Control and Decision School of Automation Beijing Institute of Technology Beijing100081 China Key Laboratory of Sefvo Motion System Drive and Control School of Automation Beijing Institute of Technology Beijing100081 China

In this paper, the foot trajectory tracking control for parallel structure of the six wheel-legged robot is investigated. The accuracy of trajectory tracking and dynamic response with heavy load are the main challenges of parallel mechanism. To guarantee the tracking performance and improve dynamic response frequency to posture input, a method based on dynamic model predictive control is proposed under the establishment of dynamic model of single leg. Newton-Eulerian equation is derived and converted into a discrete state space expression for velocity loop control, appropriate parameters including prediction time domain, control time domain and proportional gain are determined by co-simulation. Desired sinusoidal trajectories with different frequencies are tracked with satisfactory performance in terms of accuracy and response frequency. Finally, comparative experimental results using BIT-NAZA robot derived from the proposed control strategy indicate that the delay error and amplitude error are better than PI controller under the same conditions. This research can provide theoretical and engineering guidance for accurate planning of intelligent robot, and facilitate the control performance of wheel-legged robot in practical system. © 2020, CC BY.

关键词： Dynamic models

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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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Local Path Planning Algorithm for UGV Based on Improved Covariance Matrix Adaptive Evolution Strategy

Local Path Planning Algorithm for UGV Based on Improved Cova...

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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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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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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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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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Observer-based finite time H ∞ control of nonlinear discrete time-varying systems with an adaptive event-triggered Mechanism

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Journal of the Franklin Institute 2020年第16期357卷 11668-11689页

作者： Menghua Chen Hamid Reza Karimi Jian Sun School of Automation Beijing Institute of Technology Beijing 100081 China Department of Mechanical Engineering Politecnico di Milano Milan 20156 Italy Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing 100081 China

The problem of finite time stability and synthesis is discussed for nonlinear discrete time-varying systems by using the T-S fuzzy model. To reduce the communication network resources, two adaptive event-triggered mechanisms (AETMs) are taken into consideration in sensor-to-observer (S/O) and observer-to-controller (O/C) channels. The thresholds of the AETMs are adjusted according to the estimation error rather than some fixed ones. Sufficient conditions for developing an observer-based time-varying control are obtained, which ensure the time-varying error system to be finite time stable and satisfy the H ∞ performance simultaneously. Moreover, using the singular value decomposition technique, recursive linear matrix inequalities conditions are obtained for computing the gains of the controller and observer. Finally, the superiority and applicability of the proposed method are demonstrated by examples.

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Coordinated motion control and event-based obstacle-crossing for four wheel-leg independent motor-driven robotic system via MPC

arXiv

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arXiv 2020年

作者： Liu, Dongchen Wang, Junzheng Wang, Shoukun The National Key Laboratory of Complex System Intelligent Control and Decision School of Automation Beijing Institute of Technology Beijing10081 China The Ministry of Industry and Information Technology Key Laboratory of Servo Motion System Drive and Control School of Automation Beijing Institute of Technology Beijing10081 China

This work investigates the coordinated motion control and obstacle-crossing problem for a four wheel-leg independent motor-driven robotic system via a model predictive control (MPC) approach based on an event-triggering mechanism. The modeling of a wheel-leg robotic control system with a dynamic supporting polygon is organized. The system dynamic model is 3 degrees of freedom ignoring the pitch, roll, and vertical motions. The single wheel dynamic is analyzed considering the characteristics of the motor-driven and the Burckhardt nonlinear tire model. As a result, an over-actuated predictive model is proposed with the motor torques as inputs and the system states as outputs. As the supporting polygon is only adjusted at certain conditions, an event-based triggering mechanism is designed to save hardware resources and energy. The MPC controller is evaluated on a virtual prototype as well as a physical prototype. The simulation results guide the parameter tuning for the controller implementation in the physical prototype. The experimental results on these two prototypes verify the efficiency of the proposed approach. © 2020, CC BY.

关键词： Geometry

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An Improved Segmentation Method for Porous Transducer CT Images

An Improved Segmentation Method for Porous Transducer CT Ima...

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2019第十一届数字图像处理国际会议

作者： Meiling Wang Ruoyu Guo Ke Ning Li Ming Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision

The paper presents an improved image segmentation method with a straightforward workflow for porous transducer CT images,which can be used to establish porous transducer three-dimensional model and further study its *** distribution of CT images is firstly analyzed and Gaussian filtering is conducted to reduce divergence of CT *** improved fully convolutional neural network model based on U-Net,for which multi-channel images are set as network input,is trained using training *** proposed method improves pore connectivity of the segmentation *** of porosity and permeability relative errors as well as MIOU on test set shows that the proposed method is an effective and generic two-phase segmentation method for porous transducer CT images without need of adjusting any parameters.

关键词： Porous transducer image segmentation permeability pore connectivity fully convolutional neural network

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