Fuzzy PID Adaptive Control System Developed in Simulink

This article discusses a fuzzy PID adaptive control system implemented in Simulink. The system employs three distinct fuzzy inference systems (FIS) - dkp, dki, and dkd - to dynamically control the proportional (Kp), integral (Ki), and derivative (Kd)增益 parameters respectively. The primary objective of this system is to enable automatic PID parameter adjustment to adapt to varying operational conditions. Specifically, through fuzzy logic algorithms that process input signals and error metrics, the system autonomously fine-tunes PID parameters to achieve optimized control performance. The implementation typically involves designing membership functions and rule bases for each FIS to handle parameter variations. This adaptive control approach finds extensive applications across diverse systems including robotics, aerospace vehicles, automotive systems, and industrial automation. In summary, this fuzzy PID adaptive system serves as a powerful tool for enhanced control and management of various dynamic systems through intelligent parameter optimization.