Neural Network-Based Adaptive Dynamic Surface Control for Inverted Pendulum System
In this paper, a novel neural network (NN)-based adaptive dynamic surface control (DSC) is proposed for inverted pendulum system. This scheme overcomes the problem of “explosion of complexity” which is inherent in the traditional backstepping technique. Meanwhile, the effect of input saturation constrains is considered in the control design. All the signals in the closed-loop system are proved uniformly ultimately bounded. Finally, the experimental platform simulation results are used to demonstrate the effectiveness of the proposed scheme.
KeywordsInverted pendulum system Neural network Dynamic surface control Input saturation
This work is supported in part by the National Natural Science Foundation of China (Grant No. 51179019, 60874056), the Natural Science Foundation of Liaoning Province (Grant No. 20102012), the Program for Liaoning Excellent Talents in University (LNET) (Grant No. LR2012016), and the Fundamental Research Funds for the Central Universities (2011QN097).
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