Adaptive Neural Control of Non-Affine Pure-Feedback Systems

Controlling non-affine nonlinear systems is a challenging problem in the control community. In this paper, an adaptive neural control approach is presented for the completely non-affine pure-feedback system with only one mild assumption. By combining adaptive neural design with input-to-state stability (ISS) analysis and the small-gain theorem, the difficulty in controlling non-affine pure-feedback system is overcome by achieving the so-called "ISS-modularity" of the controller-estimator. The ISS-modular approach provides an effective way for controlling non-affine nonlinear systems with uncertainties. Simulation studies are included to demonstrate the effectiveness of the proposed approach