Malmquist orthogonal functions based Tube model predictive control with sliding mode for DC motor servo system

This paper introduces a novel approach to the conventional model predictive control design within a tube model predictive control framework for a DC motor servo system that is an important component of various control systems in process industries. Tube model predictive control proves to be an effective method in the formulation, analysis, and implementation of robust control strategies. The objective is to include all possible trajectories of an uncertain system within a tube of the nominal system trajectories. Therefore, the proposed method incorporates discrete-time generalized Malmquist orthogonal functions for nominal model predictive controller design, which is the first time that these functions are used for this purpose in combination with the auxiliary sliding mode controller. The sliding mode controller has a crucial role in determining the robust dynamics of a closed-loop system in the presence of disturbances and plant nonlinearities. Experimental results of DC servo motor angular position control are presented and discussed for two different sliding mode control algorithms. The analysis shows improved performance in terms of fast reference tracking and disturbance rejection.