Neuro-fuzzy generalized predictive control of boiler steam temperature

Power plants are nonlinear and uncertain complex systems. Reliablecontrol of superheated steam temperature is necessary to ensure highefficiency and high load-following capability in the operation ofmodern power plant. A nonlinear generalized predictive controllerbased on neuro-fuzzy network (NFGPC) is proposed in this paper. Theproposed nonlinear controller is applied to control the superheatedsteam temperature of a 200MW power plant. From the experiments onthe plant and the simulation of the plant, much better performancethan the traditional controller is obtained.