Fuzzy-PID and interpolation: a novel synergetic approach to process control

Abstract

This paper presents a novel approach for tuning a fuzzy-based proportional-integral-derivative (PID) controller to enhance the control performance of a chemical process control system. The proposed approach combines the advantages of fuzzy- PID and interpolation to achieve improved control performance. Properly tuned PID controllers can help maintain process stability, minimize deviations from setpoints, and ensure efficient operation in industrial systems. Fuzzy logic allows for the incorporation of expert knowledge and linguistic rules, enabling the controller to handle uncertain and imprecise process information. Fuzzy PID controllers combine fuzzy logic and conventional PID control to enhance control performance, particularly in systems with complex or nonlinear dynamic such as chemical plant. It dynamically adjusts the PID parameters—proportional gain (Kp), integral gain (Ki), and derivative gain (Kd)—based on error e(t) and change of error Delta e(t). Interpolation plays a crucial role in this context by filling in the gaps or handling situations not explicitly covered by the fuzzy rules. Comparative studies are conducted to evaluate the performance of the fuzzy PID controller against conventional PID controllers and other advanced control techniques. It is demonstrated that the synergy between fuzzy logic and interpolation not only enhances control performance but also offers a more intuitive and adaptable solution for addressing the complexities of modern chemical process control systems.

Keywords

• Fuzzy
• Linguistic variables
• Interpolation
• FIE