Nonlinear Disturbance Observer Based Adaptive Explicit Nonlinear Model Predictive Control Design for a Class of Nonlinear MIMO System

Abstract

In this paper, a nonlinear disturbance observer-based adaptive explicit nonlinear model predictive control scheme is proposed to compensate for external disturbance and parametric uncertainty for a class of nonlinear multi-input-multi-output (MIMO) systems. Here, the analytical solution of the proposed adaptive control scheme is developed by approximating the tracking errors and control efforts with the Taylor series expansion method. In this approach, a nonlinear disturbance observer is used to observe the unknown external disturbance of the system. To restrict the parameters from leaving the compact parameter space, an adaptive parameter estimator using projection-based parameter adaptation laws is used. The performance of the designed control technique is enhanced by incorporating the estimated disturbance and estimated system parameters in the updating control law. Using an aerodynamic laboratory set-up known as the twin-rotor MIMO system (TRMS), the effectiveness of the proposed control algorithm has been verified. Simulation and real-time results show that the proposed control algorithm performs better than the existing control algorithm in the presence of unknown external disturbances and parameter uncertainties.