Neuro-adaptive control of mobile manipulators based on compensation of approximation error

2002 ◽  
Vol 38 (16) ◽  
pp. 935 ◽  
Author(s):  
Choon-Young Lee ◽  
Tae-Dok Eom ◽  
Ju-Jang Lee
Keyword(s):  
Adaptive Control ◽  
Approximation Error ◽  
Mobile Manipulators

scholarly journals Adaptive PD Control Based on RBF Neural Network for a Wire-Driven Parallel Robot and Prototype Experiments

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Yuqi Wang ◽  
Qi Lin ◽  
Xiaoguang Wang ◽  
Fangui Zhou
Keyword(s):  
Neural Network ◽  
Adaptive Control ◽  
Control Method ◽  
Rbf Neural Network ◽  
Approximation Error ◽  
Wind Tunnel Test ◽  
Parallel Robot ◽  
Network Control ◽  
Pd Control ◽  
Control Scheme

An adaptive PD control scheme is proposed for the support system of a wire-driven parallel robot (WDPR) used in a wind tunnel test. The control scheme combines a PD control and an adaptive control based on a radial basis function (RBF) neural network. The PD control is used to track the trajectory of the end effector of the WDPR. The experimental environment, the external disturbances, and other factors result in uncertainties of some parameters for the WDPR; therefore, the RBF neural network control method is used to approximate the parameters. An adaptive control algorithm is developed to reduce the approximation error and improve the robustness and control precision of the WDPR. It is demonstrated that the closed-loop system is stable based on the Lyapunov stability theory. The simulation results show that the proposed control scheme results in a good performance of the WDPR. The experimental results of the prototype experiments show that the WDPR operates on the desired trajectory; the proposed control method is correct and effective, and the experimental error is small and meets the requirements.

Mobile Operations Performed by Mobile Manipulators on Irregular Terrain - Torque Compensation Using Neural Networks for Disturbance Torques Produced by Irregular Terrain -

1998 ◽  
Vol 10 (5) ◽  
pp. 377-386 ◽  
Author(s):  
Mamoru Minami ◽  
◽  
Masatoshi Hatano ◽  
Toshiyuki Asakura ◽  
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Adaptive Control ◽  
Control System ◽  
Horizontal Plane ◽  
Mobile Manipulator ◽  
Mobile Manipulators ◽  
Adaptive Control System ◽  
Control Performance ◽  
Irregular Terrain

In the present study, we propose a control system for mobile operations of mobile manipulators traveling on irregular terrain. Irregularities exist even in structures such as man-made floors of factories and buildings. Since the hand of a mobile manipulator is often required to operate precisely while traveling on irregular terrain and it is subject to disturbance torques caused by traveling on terrain, a method for decreasing control errors caused by disturbances due to terrain must be considered. In the present paper, an adaptive control system including a compensator that uses a neural network, i.e., a neuro adaptive control system, is proposed. In addition, we discuss the control performance of the proposed control system, and show that the control system can decrease control errors occurring on irregular terrain to the levels of errors that occur while traveling on a horizontal plane.

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