Neural networks direct adaptive control for a class of MIMO uncertain nonlinear systems

This paper presents a direct adaptive control scheme based on multi-layer neural networks for a class of multi-input multi-output (MIMO) nonlinear systems with unknown nonlinearity. The on-line updating rules of the neural networks parameters are obtained by Lyapunov stability theory. All signals in the closed-loop system are bounded and the output tracking error converges to a small neighborhood of zero. In this sense the closed-loop system is stable. The effectiveness of the control scheme is verified by a simulation of two link manipulator.