Optimal Fractional Fuzzy PID Controller for Speed Control of Nonlinear DC Motor with Uncertainty
Year: 2026
Type: article
Abstract: This paper presents an optimal fractional-order fuzzy PID (FO-PID) controller designed for the speed control of nonlinear DC motors subject to parametric uncertainties and time-varying load disturbances. The proposed strategy integrates fractional-order calculus with fuzzy logic to overcome the limitations of conventional integer-order PID controllers in handling system nonlinearities, specifically the back-EMF characteristic and varying inertia. The controller employs a Takagi-Sugeno fuzzy inference system to dynamically tune the proportional, integral, and derivative gains, as well as the fractional integral and derivative orders, in real-time based on the tracking error and its fractional derivative. The tuning problem is formulated as a multi-objective optimization task subject to robust stability constraints derived from Lyapunov direct methods. The objective function minimizes a weighted Integral of Time-weighted Absolute Error (ITAE), penalizes control effort, and enforces stability margins by considering the worst-case parameter variations within defined interval bounds. To solve this non-convex optimization problem, a Multi-Objective Differential Evolution algorithm with Constraint Handling (MODE-CH) is implemented, incorporating a penalty function for constraint violations. The approach ensures closed-loop exponential stability even under worst-case uncertainties, offering a rigorous, mathematically grounded solution for robust speed control in uncertain DC motor systems.
Source: OICC Press Journals
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7204204452