A Comparative Analysis of two Controllers for Trajectory Tracking Control: Application to a Biological Process

Abstract

The aim of the present work is to guarantee the trajectory tracking of a nonlinear biological process and compare two control approaches. The main objective of this work is to elaborate a fuzzy model and build a fuzzy controllers for a biological process by using the fuzzy Takagi-Sugeno. Two controllers are synthesized, the parallel distributed compensation control and optimal fuzzy linear quadratic integral control. In both cases, the physical constraints on the manipulated inputs are respected. In addition, the case with and without the observer is presented, where a fuzzy observer based control is used with unmeasurable premise variables. Finally, the performances and the effectiveness of both the modeling and the control are demonstrated via simulations.