Speed Control of a DC Motor with a Type-2 Fuzzy Logic Controller Subject to a Large Disturbance

Abstract

In this paper the methodology of an application of a type-2 fuzzy logic controller for the speed control of a direct current machine subject to a stochastic and deterministic large signal is presented. A type-2 PI fuzzy logic controller using the Enhanced Karnick- Mendel algorithm (EKM) is proposed. This has a better runtime on the conventional Karnick-Mendel algorithm (KM). The nonlinear model of a 5 HP separately excited DC Motor including an armature voltage limiter is used. A 100% increment in the load torque is applied. This is a braking torque. This paper is a continuation of the research presented in [11]. Where, a type-2 PI fuzzy logic controller using a KM for the speed control of DC motor subject to a small disturbance in load and speed reference is analyzed. The type-2 PI controller is tuned based on a type-1 PI controller. The performance of both controllers is compared. The quantitative performance of both controllers is measured in terms of integral square error (ISE), integral absolute error (IAE) and integral time absolute error (ITAE). Tests show the advantage of the type-2 PI fuzzy controller when the motor load is subject to a stochastic and deterministic large disturbance. This is explained by the better handling of uncertainty and nonlinear behavior of type-2 PI. The robustness, in the results of both fuzzy controllers, presents stability in nonlinear sceneries when exposed to stochastic and deterministic large signals.