Adaptive Control of a Class of Non-Affine Systems using Neural Networks

A neural control synthesis method is considered for a class of non-affine uncertain single-input, single-output systems. The method eliminates a fixed-point assumption and does not assume boundedness on the time derivative of a control effectiveness term. One or the other of these assumptions exist in earlier papers on this subject. Using Lyapunov´s direct method, it is shown that all the signals of the closed-loop system are uniformly ultimately bounded, and that the tracking error converges to an adjustable neighborhood of the origin. Simulation with a Van Der Pol equation with non-affine control terms illustrates the approach.