Parameters Optimization of Aeroengine PID Controller Based on Genetic Algorithms

Aeroengine control system is extremely complex, genetic algorithms are applied to the aeroengine serial PID controller parameters optimization because shortcomings exist in the conventional optimization methods. By using real value encoding, crossover and mutation probabilities, the global searching ability and the convergence speed of the genetic algorithms were significantly improved. According to control requirements of aeroengine, terms which represent overshoot, rise time and steady-error of the system in the performance index function were introduced and properly weighted. Simulation results show that satisfactory dynamic and steady-state performance of the aeroengine serial PID control system is acquired by applying this optimization method. Multi-objective genetic algorithms can provide an excellent method for large-scale complex systems optimization.