A new L 2-gain disturbance rejection controller and adaptive adjustment are combined into a hybrid robust control scheme, which is proposed for robot tracking control systems. The proposed controller deals mainly with external disturbances and nonlinear uncertainty in motion control. A neural network (NN) is used to approximate the uncertainties in a robotic system. Meanwhile, the approximating error of the NN is attenuated to a prescribed level by the adaptive robust controller. The adaptive techniques of NN will improve robustness with respect to uncertainty of system, as a result, improving the dynamic performance of robot system. A simulation example demonstrates the effectiveness of the proposed control strategy. © 2010 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Yu, Z. G., Shen, Y. L., Song, S. M., & Zhang, D. W. (2010). Neural networks L 2-gain control for robot system. In Lecture Notes in Electrical Engineering (Vol. 67 LNEE, pp. 513–520). https://doi.org/10.1007/978-3-642-12990-2_59
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