Online PI controller tuning for a nonlinear plant using genetic algorithm

Abstract

Proportional - Integral - Derivative (PID) controller performs well for linear systems. For systems with nonlinearity, controller parameters need to be tuned every time for new operating point to obtain `local gain parameters'. These local gain parameters are not sufficient to get satisfactory performance at other operating points. In this paper a novel approach `Aggregate Fitness Function' is presented to obtain the `global gain parameters' that works satisfactorily at various operating points. Online optimization scheme with Genetic Algorithm (GA) is adopted to tune the Proportional-Integral (PI) controller parameters for setpoint tracking of DC Motor by minimizing Integral-Time-Absolute-Error (ITAE). Hardware validation of the results is presented and studied. The plant under study is DC Motor Control Module (MS15) from M/S LJ CREATE™. M/S National Instrument (NI) based software and hardware components i.e. LabVIEW™ and its add-ons toolkit and Data Acquisition (DAQ) Card has been utilized for online tuning and closed loop run time control. The simulation and run time results clearly show the efficiency of the proposed approach.