Abstract
To obtain a more efficient intelligent controller, this paper presents a modified cloud theory-based particle swarm optimization (CTPSO) algorithm to improve fuzzy PID controller. Cloud evolution and mutation methods based on cloud theory are introduced to tune inertia weight of particle swarm optimization algorithm (PSO), which can improve the optimization accuracy and speed of PSO. The comparative experiments indicate that CTPSO performs better than PSO and other optimization algorithm recently proposed by other researchers. The CTPSO is used to set the initial PID control parameters and optimize control rules of fuzzy PID controller. According to an engineering case of the 180°C-die heater’s temperature control, the novel optimized fuzzy PID controller can suppress the oscillation and overshoot significantly. It also owns smaller adjustment time, static error and better comprehensive performance compared with the initial controller.
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