VARIABLE ARGUMENTS PID CONTROL FOR MAIN STEAM TEMPERATURE SYSTEM BASED ON IMMUNE GENETIC OPTIMIZATION

Aiming at engineering application, the paper put forward a new control strategy of improved Variable Arguments Proportional-Integral-Derivative(VAPID),which has a good control effect on both regulating and set-point following. For the common large time-delay object happen frequently in the industrial practice, it has a quite good disturbance resistance and a strong robustness. In order to get a better performance for the variable-parameter PID control, a concept of robust tuning is put forward, meanwhile an immune genetic algorithm is also applied to robust optimal tuning of VAPID. Simulation is proceeded for the steam temperature system in a plant under such a control which has a severe uncertainty of parameters and multi-disturbance, as well as a large time-delay. The results show that the immune genetic algorithm is capable to complete a global optimization due to its immune feedback and genetic mechanism that is successful and effective for optimizing VAPID controller. The simulation results also demonstrate that the multi-model main steam temperature control system has an excellent regulation performance under different steam loads, and the optimization by using immune genetic algorithm and VAPID has a perfectible application future to the initial ones.