Multi-Objective Optimization and Parameter Tuning for Turbine PID Controller

Abstract

The tuning of PID controller parameters is the most important task in PID design process. A new tuning method is presented for PID parameters, based on multi-objective optimization technique and multi-attribute decision making method. Three performances of a PID controller, i.e. the accurate set point tracking, disturbance attenuation and robust stability are studied simultaneously. These specifications are usually competitive and any acceptable solution requires a tradeoff among them. A hybrid approaches is proposed. In the first stage, a Non-dominated Sorting Genetic Algorithm II (NSGA II) is employed to approximate the set of Pareto solution through an evolutionary optimization process. In the subsequent stage, a multi-attribute decision making (MADM) approach is adopted to rank these solutions from best to worst and to determine the best solution in a deterministic environment with a single decision maker. The ranking of Pareto solution is based on entropy weight and TOPSIS method. A turbine PID design example is conducted to illustrate the analysis process in present study. The effectiveness of this universal framework is supported by the simulation results.