Improved adaptation mechanism in MRAC scheme with nonlinear reference model for nonlinear uncertain systems

Abstract

Abstract This paper proposes a direct Model Reference Adaptive Control (MRAC) architecture integrating a nonlinear reference model for a class of MIMO nonlinear systems with parameter uncertainty. The proposed Lyapunov-based adaptive rule makes the MRAC architecture favourable for a class of nonlinear MIMO systems in the presence of uncertainties. The systematic method also allows nonlinear MRAC architecture to be built as flexible as possible, making it more practical and straightforward to apply in real-time for nonlinear uncertain systems. To demonstrate the effectiveness of the proposed MRAC rule, it is compared against classical MRAC approach through simulations and experiments performed on 3 DoF laboratory helicopter. In addition, the robustness analysis of the proposed MRAC approach is also performed through Monte Carlo simulations.