Neural network based tracking control of a flexible macro-micro manipulator system

Authors:
X. P. Cheng;R. V. Patel
Affiliations:
Defence Research and Development Canada, Suffield, Alberta, Canada;Department of Electrical and Computer Engineering, The University of Western Ontario, London, Ont., Canada N6A 5B9
Venue:
Neural Networks
Year:
2003

Citing 7
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Abstract

In this paper, we address the problem of stable tracking control of a flexible macro-micro manipulator (M3) system. A two-layer neural network is utilized to approximate the nonlinear robot dynamic behavior of the M3 system, and the controllers for the macro and micro arms are developed without any need for prior knowledge of the dynamic model of the controlled M3 system. A learning algorithm for the neural network using Lyapunov stability theory is derived. It is shown that both the tracking error and the weight-tuning error are uniformly ultimately bounded under this new control scheme. Simulation results are presented and compared to those obtained using a PD controller.