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Torque sensorless decentralized neuro-optimal control for modular and reconfigurable robots with uncertain environments

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NEUROCOMPUTING 2018年 282卷 60-73页

作者： Dong, Bo Zhou, Fan Liu, Keping Li, Yuanchun Changchun Univ Technol Dept Control Sci & Engn Changchun 130012 Jilin Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

A technical challenge of addressing the decentralized optimal control problem for modular and reconfigurable robots (MRRs) during environmental contacts is associated with optimal compensation of the uncertain contact force without using force/torque sensors. In this paper, a decentralized control approach is presented for torque sensorless MRRs in contact with uncertain environment via an adaptive dynamic programming (ADP)-based neuro-optimal compensation strategy. The dynamic model of the MRRs is formulated based on a novel joint torque estimation method, which is deployed for each joint model, and the joint dynamic information is utilized effectively to design the feedback controllers, thus making the decentralized optimal control problem of the environmental contacted MRR systems be formulated as an optimal compensation issue of model uncertainty. By using the ADP method, a local online policy iteration algorithm is employed to solve the Hamilton-Jacobi-Bellman (HJB) equation with a modified cost function, which is approximated by constructing a critic neural network, and then the approximate optimal control policy can be derived. The asymptotic stability of the closed-loop MRR system is proved by using the Lyapunov theory. At last, simulations and experiments are performed to verify the effectiveness of the proposed method. (C) 2017 Elsevier B.V. All rights reserved.

关键词： modular and reconfigurable robot Decentralized control Adaptive dynamic programming (ADP) Optimal control Neural networks

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Adaptive Dynamic Programming-based Decentralized Sliding Mode Optimal Control for modular and reconfigurable robots

Adaptive Dynamic Programming-based Decentralized Sliding Mod...

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IEEE Symposium Series on Computational Intelligence (SSCI)

作者： An, Tianjiao Men, Xiaodong Zhang, Xinyao Li, Yuanchun Dong, Bo Changchun Univ Technol Dept Control Sci & Engn Changchun Peoples R China Northeastern Univ Res Ctr Mech Kinet & Reliabil Qinhuangdao Hebei Peoples R China

ISBN: (纸本)9781728124858

A model-free decentralized sliding mode control (SMC) is proposed via adaptive dynamic programming (ADP) algorithm to solve the problem of optimal tracking control of modular and reconfigurable robots (MRRs) in this paper. The dynamic formulation of MRR is expressed by a synthesis of joint subsystems with interconnected dynamic couplings (IDCs). Based on SMC technique, the optimal control of robotic system is transformed into an optimal compensation problem of unknown dynamics of each subsystem and a neural network (NN) identifier is set up to approximate IDC dynamics. Based on ADP and policy iteration (PI) method, the Hamilton-Jacobi-Bellman (HJB) equation can be addressed by using the critic NN and the optimal control policy can be obtained. The closed-loop robotic system is proved to be asymptotic stable by using the Lyapunov theory. Finally, simulation results are provided to demonstrate the effectiveness of the method.

关键词： Optimal control Decentralized control Adaptive dynamic programming modular and reconfigurable robot

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Decentralized Adaptive Super-Twisting Control for modular and reconfigurable robots with Uncertain Environment Contact 36

Decentralized Adaptive Super-Twisting Control for Modular an...

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第36届中国控制会议

作者： Bo Dong Yan Li Keping Liu Yuanchun Li Department of Control Science and Engineering Changchun University of Technology State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences

ISBN: (纸本)9781538629185

This paper presents a decentralized adaptive super-twisting control method for modular and reconflgurable robots（MRRs） with uncertain environment *** conventional methods that rely on robot-environment contact model or force/torque sensing,this paper addresses the problem of controlling MRRs in contact with uncertain environment that using only local dynamic information of each joint *** dynamic model of MRR is formulated as a synthesis of interconnected *** on the integral sliding mode control（ISMC） technique and the adaptive super-twisting algorithm（ASTA）,the decentralized controller is designed to compensate the model uncertainty in which the up-bound is *** stability of the MRR system is proved by using the Lyapunov *** last,simulations are conducted for 2-DOF MRRs with different configurations under the situations of dynamic contact and collision to investigate the advantage of the proposed approach.

关键词： modular and reconfigurable robot Decentralized control strategy Uncertain environment contact Adaptive supertwisting algorithm Interconnected couplings

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Decentralized optimal control for modular and reconfigurable robots based on adaptive dynamic programming 36

Decentralized optimal control for modular and reconfigurable...

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第36届中国控制会议

作者： Zixu Wang Bo Dong Hongbing Xia Yuanchun Li Department of Control Science and Engineering Changchun University of Technology State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences

ISBN: (纸本)9781538629185

This paper presents a decentralized optimal control method for modular and reconflgurable robots（MRRs） based on adaptive dynamic ***,the dynamic model of MRRs is formulated by using the Newton-Euler iterative algorithm,and then the state space description is ***,the optimal control policy of the MRRs system is obtained based on the policy iteration algorithm,which is used to solve the Hamilton-Jacobi-Bellman（HJB） equation via the critic neural ***,the stability of the closed-loop system is proved by using the Lyapunov ***,simulations are conducted to illustrate the effectiveness for the 2-DOF MRRs.

关键词： modular and reconfigurable robot Decentralized control strategy Adaptive dynamic programming Neural network

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Development of control system architecture for modular and re-configurable robot manipulators

Development of control system architecture for modular and r...

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IEEE International Conference on Mechatronics and Automation

作者： Wang, Daqing Goldenberg, Andrew A. Liu, Guangjun Univ Toronto Dept Mech & Ind Engn 5 Kings Coll Rd Toronto ON M5A 2E2 Canada Ryerson Univ Dept Aerosp Engn Toronto ON M5B 2K3 Canada

ISBN: (纸本)9781424408276

Architecture forms the backbone of robotic control systems and has to be carefully studied before the system is built. In this paper, after insight and exclusive discussions on control system architecture requirements of modular and reconfigurable robot manipulators are presented, a hybrid architecture is proposed and described in details. The proposed architecture has been implemented on a modular and reconfigurable robot, and the testing results show the validity of the proposed architecture.

关键词： modular and reconfigurable robot control system architecture hybrid architecture

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Decentralized control for harmonic drive-based modular and reconfigurable robots with uncertain environment contact

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ADVANCES IN MECHANICAL ENGINEERING 2017年第4期9卷 1-14页

作者： Dong, Bo Li, Yan Liu, Keping Changchun Univ Technol Dept Control Sci & Engn Changchun 130012 Jilin Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing Peoples R China

In this article, a decentralized control strategy is presented for harmonic drive-based modular and reconfigurable robots with uncertain environment contact. Unlike conventional methods that rely on robot-environment contact model or force/torque sensing, this article addresses the problem of controlling modular and reconfigurable robots in contact with uncertain environment using only encoder data of each joint module. By employing a control-oriented harmonic drive model, the dynamic model of modular and reconfigurable robot is formulated as a synthesis of interconnected subsystems, in which the interconnected joint couplings are with small magnitudes. Based on the integral sliding mode control technique and the adaptive super-twisting algorithm, the decentralized controller is designed to compensate model uncertainty in which the up-bound is unknown. The stability of the modular and reconfigurable robot system is proved using Lyapunov theory. Finally, simulations are conducted for 2-degree-of-freedom modular and reconfigurable robots with different configurations under the situations of dynamic contact and collision to investigate the advantage of the proposed approach.

关键词： modular and reconfigurable robot decentralized control strategy uncertain environment contact harmonic drive transmission interconnected couplings

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Development and Performance Comparison of Extended Kalman Filter and Particle Filter for Self-reconfigurable Mobile robots

Development and Performance Comparison of Extended Kalman Fi...

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robotic Intelligence In Informationally Structured Space (RiiSS)

作者： Won, Peter Seong-hoon Biglarbegian, Mohammad Melek, William Univ Waterloo Mech Engn Waterloo ON Canada Univ Guelph Sch Engn Guelph ON Canada

ISBN: (纸本)9781479944644

In this paper we develop two filters, extended Kalman filter (EKF) and particle filter (PF), for autonomous docking of mobile robots and compare the performances of the two filers in terms of accuracy. robots are equipped with IR emitters/receivers and encoders, and their data is used to estimate the distance and orientation of robots, which is needed for docking. The two state estimation methods are compared in simulations under different conditions. Simulation results demonstrate that the estimation accuracy of the EKF is higher than PF when the initial state is correctly estimated. However, when the initial state is not estimated correctly, the state estimation of EKF does not converge to the true value. On the other hand, PF state estimation successfully converges to the true value and the error is more consistent. The result of this work can help researchers and practitioners to design and use proper filters for docking applications.

关键词： modular and reconfigurable robot Infrared Kalman filter Particle filter

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Decentralized Control of reconfigurable robots Using Joint-Torque sensing 3

Decentralized Control of Reconfigurable Robots Using Joint-T...

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3rd RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： Almodaresi, Seyed Mostafa Yazdi Sharif Univ Technol Dept Elect Engn Tehran Iran

ISBN: (纸本)9781467372343

In this paper, a decentralized controller for trajectory tracking of modular and reconfigurable robot manipulators is developed. The proposed control scheme uses joint-torque sensory feedback;also sliding mode control is employed to make both position and velocity tracking errors of robot manipulators globally converging to zero. Proposed scheme also guarantees that all signals in closed-loop systems will be bounded. In contrast to some of prior works in this scheme, each controller uses a smooth law to achieve its purposes. In this method, each controller uses only local information for producing control law hence separated controller can be used to control each module of manipulator and no information exchange between modules is required. Simulation results are provided for a reconfigurable robot with three modules to verify the performance of the proposed scheme. Results show that decentralized control of reconfigurable robots is feasible, in spite of strong dynamic coupling between modules.

关键词： Decentralized control modular and reconfigurable robot nonlinear control robot control joint-torque sensory feedback

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Decentralized Control of reconfigurable robots Using Joint-Torque sensing

Decentralized Control of Reconfigurable Robots Using Joint-T...

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RSI/ISM International Conference on robotics and Mechatronics

作者： Seyed Mostafa Yazdi Almodaresi Electrical Engineering Department Sharif University of Technology Tehran Iran

ISBN: (纸本)9781467372350

关键词： Decentralized control modular and reconfigurable robot nonlinear control robot control joint-torque sensory feedback

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