The Parameter Tuning Method of the Fuzzy PID Control Based on an Improved Differential Evolution Algorithm

The traditional Proportional- Integral-Derivative (PID) controllers face the common issues of convergence to local optima and slow performance in high-dimensional problems of nonlinear and complex systems. To address the above limitations of the PID controllers, this paper proposes a fuzzy PID parameter tuning method based on the improved differential evolution (IDE) algorithm, which combines the uncertainty-handling capability of fuzzy logic with the global optimization features of the differential evolution (DE) algorithm and employs an adaptive mechanism to dynamically adjust mutation factors and crossover probabilities, achieving a balance between global exploration and local exploitation. Subsequently, the improved method is integrated into the design of the fuzzy PID controllers, enhancing adaptability and optimization performance. Simulation results show that compared to the traditional DE algorithms, the proposed method significantly reduces iteration counts, accelerates convergence, and exhibits stronger adaptability in controlling complex nonlinear systems.