Genetic algorithm-based parameters optimization of thermal process control system

On the basis of analysis to the thermal process of power plant and simple genetic algorithm, a improved genetic algorithm is introduced to optimize controller parameters of thermal process. In the genetic algorithm, floating-point genes, rank-based model, elitist model and parallel algorithm are used. The premature convergence is eliminated, the global and local searching ability is improved. The MATLAB program of genetic algorithm of controller parameters optimization is given. A single loop PID control system and a superheat steam control system is optimized and optimal parameters are given. It is shown by simulation research that the genetic algorithm is better than traditional methods, satisfactory, control results can be got with the optimized parameters.