Lyapunov Based Two-stage Robust Model Reference Adaptive Controller for Linear Plants with Time Varying Bounded Uncertainties

A robust model reference adaptive controller (MRAC) is developed for linear plants with bounded structured uncertainties. The control rule is implemented in two stages to achieve robustness and state tracking and output tracking. In the first stage, state tracking is achieved and after that, in the second stage, output tracking is achieved. Output error identification is used to estimate the bounded uncertainties associated with state matrix, input matrix and output matrix. The control rules are based on these estimates of uncertainties. All the states are assumed to be available for measurement and the estimates of the uncertainties are proved to converge to their actual values. Lyapunov's method is used to achieve bounded signals. Simulation results for a plant with different types of structured uncertainty show the effectiveness of the present method.