The resistance furnace temperature system has low accuracy and big overshoots with fuzzy control. The fuzzy PID controller is used to optimize the resistance furnace temperature system, and the design scheme is developed. The fuzzy control and PID control are combined to control the system. If the system's deviation is large the fuzzy control is adopted, else PID control is adopted. The genetic algorithm is adopted to train the controller's membership functions, control rules and parameters. The global optimum of the controller's parameters can be achieved. Matlab simulation results indicate that the resistance furnace temperature system with fuzzy PID control is more dynamic, robust, and highly precise.
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