Neural PID control strategy for superheated steam temperature based on minimum entropy

A novel control algorithm is applied to control superheated steam temperature in a power plant. Since the disturbances existing in practical processes are probably non-Gaussian, the performance index of system is constructed by minimizing the entropy. The optimal parameters of controller are obtained and applied to control superheated steam temperature in a power plant. The simulation results verify its effectiveness

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