Intelligent control of nonlinear power plant using immune algorithm based multiobjective optimization

This paper focuses on design of nonlinear power plant controller using immune based multiobjective fuzzy approach. The thermal power plant is typically regulated by the fuel flow rate, the spray flow rate, and the gas recirculation flow rate. However, strictly maintaining the steam temperature can be difficult due to heating value variation to the fuel source, time delay changes in the main steam temperature, the change of the dynamic characteristics in the steam-turbine system. Up to the present time, PlD controller has been used to operate this system. However, it is very difficult to achieve an optimal PID gain with no experience, since the gain of the PlD controller has to be manually tuned by trial and error. These parameters by multiobjective based on immune network algorithms could be used for the tuning of nonlinear power plant.