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Mechanical Design and Dynamic Compliance control of Lightweight Manipulator

International Journal of automation and computing 2021年第6期18卷 926-934页

作者： Shao-Lin Zhang Yue-Guang Ge Hai-Tao Wang Shuo Wang State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China

In the existing modular joint design and control methods of collaborative robots, the inertia of the manipulator link is large,the dynamic trajectory planning ability is weak, the collision stop safety strategy is dependent, and the adaptability and safety to the changing environment are limited. This paper develops a six-degree-of-freedom lightweight collaborative manipulator with real-time dynamic trajectory planning and active compliance control. Firstly, a novel motor installation, joint transmission, and link design method is put forward to reduce the inertia of the links and improve intrinsic safety. At the same time, to enhance the dynamic operation capability and quick response of the manipulator, a smooth planning of position and orientation under initial/end pose and velocity constraints is proposed. The adaptability to the environment is improved by the active compliance control. Finally, experiments are carried out to verify the effectiveness of the proposed design, planning, and control methods.

关键词： Lightweight manipulator mechanical design dynamic trajectory planning compliance control robot control

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An Optimal control Based Trajectory Planning Method for Cooperative Merging Maneuvers 3

An Optimal Control Based Trajectory Planning Method for Coop...

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3rd International Symposium on Intelligent Robotics and systems, ISoIRS 2023

作者： Wang, Qi Ge, Hao Duan, Xuting Zhou, Jianshan School of Transportation Science and Engineering Beihang University State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control State Key Laboratory of Air Traffic Management System and Technology Beijing China Nanjing Research Institute of Electronic Engineering State Key Laboratory of Air Traffic Management System and Technology Nanjing China School of Transportation Science and Engineering Beihang University State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Beijing China

ISBN: (纸本)9798350339963

Due to the prediction errors and diverse driving styles of surrounding vehicles, traffic congestion and even accidents can occur in the traffic bottleneck area where vehicles merge into the main road. To ensure that connected and automated vehicles (CAVs) can quickly and efficiently merge into the main road, this paper proposes a cooperative trajectory planning method based on optimal control for vehicle cut-in scenarios. A optimal control model is constructed, and a quintic polynomial is used to generate the initial solution of the optimal control problem to accelerate the solution process and improve the success rate. Finally, The obtained merging trajectory is then synchronized with the movement of vehicles on the main road to optimize their actions and ensure a safe merging process. Joint simulation with Robot Operating system (ROS) and RVIZ is utilized, and the results show that the proposed algorithm can quickly obtain cooperative results, the locally successful merging trajectory meets the requirements of smoothness and safety, and if the solution does not allow merging, the merging vehicle is instructed to terminate the execution. © 2023 IEEE.

关键词： Trajectories

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Novel sliding-mode disturbance observer-based tracking control with applications to robot manipulators

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Science China(Information Sciences) 2021年第7期64卷 80-91页

作者： Tairen SUN Long CHENG Zengguang HOU Min TAN School of Electrical and Information Engineering Jiangsu University State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences School of Artificial Intelligence University of Chinese Academy of Sciences

This paper proposes a sliding-mode disturbance observer(SMDOB)-based tracking controller for a class of nonlinear systems with modeling uncertainties and external disturbances. The SMDOB is constructed using an extended state observer embedded by a filtered sliding mode term. The chattering caused by the sliding mode is compressed by the frequency bandwidths of both the extended state observer and the control system. The novelties of the proposed controller are as follows:(1) The semiglobal asymptotical stability of the combined controller-observer system is guaranteed without the boundedness assumption of the time derivatives of modeling uncertainties;(2) the SMDOB can be implemented with a low complexity because of only three parameters to be tuned. Applications to robot manipulators illustrate the effectiveness of the SMDOB-based tracking control strategy.

关键词： adaptive control robot manipulator disturbance observer sliding mode

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Graph-based Selection-Activation Reinforcement Learning for Heterogenous Multi-agent Collaboration

Graph-based Selection-Activation Reinforcement Learning for ...

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第43届中国控制会议

作者： Hao-Xiang Chen Xi-Wen Zhang Jun-Nan Shen State Key Laboratory of Intelligent Control and Decision of Complex System School of Automation Beijing Institute of Technology Chongqing Innovation Center Beijing Institute of Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

In practical applications of multi-agent systems, agents are often heterogeneous, and each type of them typically has different task objectives. For heterogeneous multi-agent reinforcement learning(HMARL), the diversity of agent types and the unbalanced agent number of each type can lead to the curse of dimensionality and non-stationary. Moreover, the increase in the number of heterogeneous agents may result in slow convergence during training. This paper proposes a graph-based selection-activation reinforcement learning(GSARL) method for training heterogenous multi-agent collaboration strategies. It first constructs agents based on their types, then extracts the global adjacency matrices and the ally adjacency matrices from the agents' observations, and calculates the global feature matrices. Afterwards, GSARL utilizes hierarchical graph convolutional network to sequentially convolve the global information and ally information, obtaining action logits based on agent types. By using the neural topology graph and the selection-activation method, the optimal multi-agent collaboration configuration is obtained through combinatorial optimization. Experiments are conducted in an adversarial combat simulation environment involving collaborative Unmanned Aerial Vehicles(UAVs) and Unmanned Ground Vehicles(UGVs). Simulation results show that the proposed method can accelerate convergence while allowing that each type of heterogeneous agents can leverage its unique advantages.

关键词： Multi-Agent system Hierarchical Graph Convolutional Network Heterogenous Multi-Agent Collaboration

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Line Feature Based Visual Servo control with TDE for Underwater Vehicle Manipulator systems Target Grasping

Line Feature Based Visual Servo Control with TDE for Underwa...

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IEEE International Conference on Unmanned systems (ICUS)

作者： Yunfei Zhang Xinyu Bian Yize Sun Zongyu Zhang Hai Huang Xu Yang National Key Laboratory of Autonomous Marine Vehicle Technology Harbin Engineering University Harbin China State Key Laboratory of Management and Control for Complex System Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (数字)9798350384185

ISBN: (纸本)9798350384192

Underwater vehicle manipulator systems (UVMSs) is becoming a research hotspot in the field of marine intelligent equipment. Introducing visual feedback equipped with cameras in the loop to guide UVMS to complete the grasping has comprehensive advantages of response speed, work efficiency and intelligence. In this paper, mapping between the feature error and the motion of the UVMS generalized degrees of freedom is established to realize the suspended grasping under the coordinated motion of the vehicle body and the manipulator. Then, a UVMS motion control algorithm based on time delay estimation (TDE) is constructed for visual servo autonomous grasping process, the TDE of which is used to estimate and compensate the lumped interference in real time. The Lyapunov theory is applied to analyze its stability and its control performance is verified through simulation experiments. The simulation results shew the effectiveness of the proposed visual servo control with TED method based on line features.

关键词： Visualization Heuristic algorithms Dynamics Estimation Grasping Stability analysis Servomotors Vehicle dynamics Underwater vehicles Manipulator dynamics

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Completed attention convolutional neural network for MRI image segmentation

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High Technology Letters 2022年第3期28卷 247-251页

作者： ZHANG Zhong LV Shijie LIU Shuang XIAO Baihua Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission Tianjin Normal UniversityTianjin 300387P.R.China State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190P.R.China

Attention mechanism combined with convolutional neural network(CNN) achieves promising performance for magnetic resonance imaging(MRI) image segmentation,however these methods only learn attention weights from single scale,resulting in incomplete attention learning.A novel method named completed attention convolutional neural network(CACNN) is proposed for MRI image ***,the channel-wise attention block(CWAB) and the pixel-wise attention block(PWAB) are designed to learn attention weights from the aspects of channel and pixel *** a result,completed attention weights are obtained,which is beneficial to discriminative feature *** method is verified on two widely used datasets(HVSMR and MRBrainS),and the experimental results demonstrate that the proposed method achieves better results than the state-of-theart methods.

关键词： magnetic resonance imaging(MRI)image segmentation completed attention convolutional neural network(CACNN)

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Extended NNs-Based Adaptive Event-Triggered Asymptotic control for Nonlinear systems Against Actuator Faults 7

Extended NNs-Based Adaptive Event-Triggered Asymptotic Contr...

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7th International Symposium on Autonomous systems, ISAS 2024

作者： Liu, Shanlin Zhang, Yingwei Zhao, Xudong Wang, Hesheng Northeastern University College of Information Science and Engineering Shenyang China Northeastern University State Laboratory of Synthesis Automation of Process Industry Shenyang China Dalian University of Technology Faculty of Electronic Information and Electrical Engineering Dalian China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9798350363173

In this article, an adaptive event-triggered asymp¬totically fault-tolerant control (FTC) issue for nonlinear systems with actuator faults is investigated. An extended neural networks (NNs) technique is introduced to estimate unknown functions of the system under consideration. Compared with traditional NNs that ignore approximation errors, the proposed extended NNs further processes approximation errors, reducing the conservatism of the proposed algorithm. Then, within the framework of backstepping method, a new adaptive control strategy is developed by combining event-triggered mechanism (ETM) and bound estimation (BE) approach, which ensures the asymptotic convergence of system states while also reducing the transmission of unnecessary information, thus improving the utilization of communication resources. At the same time, the designed controller eliminates the adverse effects of actuator failures and system nonlinear terms. Finally, a simulation example of a single-link robot system is provided to demonstrate that the developed control strategy can ensure that all signals are bounded and system states are asymptotically convergent. © 2024 IEEE.

关键词： Approximation algorithms

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Event-Triggered Energy Optimization of Wireless Sensor Networks 19

Event-Triggered Energy Optimization of Wireless Sensor Netwo...

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19th IEEE International Conference on Networking, Sensing and control, ICNSC 2022

作者： Liu, Lu Song, Ruizhuo Wei, Qinglai School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China Institute of Automation Chinese Academy of Sciences The State Key Laboratory of Management and Control for Complex Systems Beijing China

ISBN: (纸本)9781665472432

Aiming at limited communication and energy re-sources in wireless sensor networks (WSN s), this paper proposes an energy management scheme of WSNs via adaptive dynamic programming (ADP) based on event-triggered mecha-nism (ETM). The optimal control strategy obtained by iteration can schedule the sensor nodes and make the nodes switch between working and sleeping situations, thus improving the energy utilization and extending the service life of the energy-constrained WSNs. Firstly, the mathematical model of WSNs is established, and the state is estimated by extended Kalman filter (EKF) algorithm to improve the measurement accuracy. Then, ADP solves the designed value function to achieve the scheduling plan. On the premise of system stability, ETM is applied to activate the controller on demand, which can reduce communication burden and save WSNs energy consumption. Finally, the simulation experiment reveals that the proposed algorithm can reduce the unnecessary triggering times of the controller effectively while ensuring the requirements, and avoid data congestion and interaction resource waste. © 2022 IEEE.

关键词： Energy utilization

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Gradient Projection Differential Neural Solution for Quadratic Optimization with Quadratic Constraints: An ACP Perspective

Gradient Projection Differential Neural Solution for Quadrat...

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2023 IEEE International Conference on systems, Man, and Cybernetics, SMC 2023

作者： Liufu, Ying Liu, Mei Jin, Long Wang, Feiyue School of Information Science and Engineering Lanzhou University Lanzhou China College of Computer Qinghai Normal University Xining China Institute of Automation The State Key Laboratory for Management and Control of Complex Systems Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798350337020

In recent years, quadratic optimizations have become increasingly popular in engineering. However, conventional methods that investigate this problem from the perspective of a canonical form with linear constraints are not effective in dealing with the significant challenges posed by quadratic constraints in practice. This paper proposes a solution framework for the quadratic optimization with quadratic constraints (QOQC) based on innovative artificial societies, computational experiments, and parallel execution (ACP) framework. Then, a gradient projection differential neural solution (GPDNS) is proposed to address this. To illustrate the effectiveness of the GPDNS model in solving the QOQC system, numerical simulations are provided. Overall, this paper presents the potential of innovative approaches like the ACP framework to enhance our capabilities in addressing challenging optimization systems. © 2023 IEEE.

关键词： ACP constraints differential neural solution numerical simulation Quadratic optimization with quadratic

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Exploring the Interactive Dynamic Influences Between Chinese and US’s Future Markets 10th

Exploring the Interactive Dynamic Influences Between Chinese...

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10th China Conference on Command and control, C2 2022

作者： Huang, Haitao Zheng, Xiaolong Zeng, Daniel Dajun The State Key Laboratory of Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9789811960512

In this paper, we focus on investigating the interactive dynamic influences between Chinese and US’s future markets. Based on Chinese and US’s futures daily closing prices, we construct Planar Maximally Filtered Graph of futures’ influences in different periods of time by calculating the Effective Transfer Entropy between different futures and find that influence strength between futures in US’s and Chinese future markets is time-varying. We further confirm that agriculture futures both in Chinese and US’s markets are relatively independent from other futures. And metal futures in LME and COMEX exert influences on Chinese metal, fuel and industrial product futures continuously. In contrast, fuel futures in NYMEX only affect Chinese fuel futures during economic shocks merely. These findings can give us some new insights into the direction, strength and underlying dynamics of influences between Chinese and US’s future market and further guide people make better choices. © 2022, Chinese institute of Command and control.

关键词： Entropy

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