학술논문
Adaptive neural network control of bilateral teleoperation with time delay
Document Type
Conference
Author
Source
The 2nd International Conference on Control, Instrumentation and Automation Control, Instrumentation and Automation (ICCIA), 2011 2nd International Conference on. :871-876 Dec, 2011
Subject
Language
Abstract
This paper proposes a novel architecture for bilateral teleoperation with a master and slave nonlinear robotic systems under constant communication delays. We basically extend the passivity based coordination architecture to improve position and force tracking and consequently transparency in the face of offset in initial conditions, environmental contacts and unknown parameters such as friction coefficient. This structure provides robust stability against constant delay and guarantee position and force tracking. The proposed controller employ a stable neural network in each side to approximate unknown nonlinear functions in the robot dynamics, thereby overcoming some limitation of adaptive control and guarantee good performance. An adaptation algorithm is developed to train the NN controller in order to stabilize the whole system. Furthermore, it is demonstrate that the tracking error of desired trajectory and NN weights are bounded. Simulation results show that NN controller tracking performance is superior to conventional coordination controller tracking performance.