Optimization of fuzzy-PID temperature controller based on improved slime mould algorithm

Abstract The temperature control system in narrow and closed spaces such as heating furnaces often has the characteristics of large hysteresis, inertia, and non-linearity. In this scenario, the classical PID controller makes it difficult to achieve a satisfactory control effect, for this reason, domestic and foreign research and practical engineering applications mostly use fuzzy PID controllers. In this paper, we first introduce Tent chaotic mapping, nonlinear feedback updating factor to improve the standard slime mould optimization algorithm (SMA), and then the quantization factor and scale factor are both optimized based on the improved SMA. The simulation is carried out in the standard test function and the typical confined space temperature control system and the results show that compared with classical PID control and fuzzy PID control methods, the proposed controller has a shorter rise time, smaller tracking error, and superior control effect.