Adaptive output feedback control methodology applicable to non-minimum phase nonlinear systems

摘要: An adaptive output feedback control methodology is developed for a class of uncertain multi-input multi-output nonlinear systems using linearly parameterized neural networks. The can be applied to non-minimum phase if the zeros are modeled sufficient accuracy. architecture comprised linear controller and network. network operates over tapped delay line memory units, system's input/output signals. laws neural-network weights employ observer nominal error dynamics. Ultimate boundedness signals shown through Lyapunov's direct method. Simulations an inverted pendulum on cart illustrate theoretical results.