Neural network adaptive robust control of nonlinear systems in semi-strict feedback form

J.Q. Gong, Bin Yao
2001 Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148)  
In this paper, the recently proposed neural network adaptive robust control (NNARC) design are generalized to synthesize performance oriented control laws for a class of nonlinear systems transformable to the semi-strict feedback forms through the incorporation of backstepping design techniques. All unknown but repeatable nonlinearities in system are approximated by outputs of multi-layer neural networks to achieve a better model compensation and an improved performance. Through the use of
more » ... ugh the use of discontinuous projections with fictitious bounds, a controlled on-line training of all NN weights is achieved. Robust control terms can then be constructed to attenuate various model uncertainties effectively for a guaranteed output tracking transient performance and a guaranteed final tracking accuracy.
doi:10.1109/acc.2001.946180 fatcat:47ve6mtq25halelcbrt7rpf5ea