An improved Sliding Mode Observer for parameter estimation in induction motor drive with optimised gains

Abstract

ABSTRACT This paper represents the online parameter identification and continuous updating in the controller of Induction Motor Drives (IMD). The online measure of parameters improves the operation of the speed estimator, particularly nearer to the zero speed, and also computes the adaptive slip angular frequency. The parameter of speed estimation is performed by the improved Optimized Constant Rate Reaching Law (OCRRL)-based sliding mode observer (SMO), and electrical parameters of stator resistance, mutual inductance, and rotor time constant estimation is performed by Improved Adaptive SMO (IASMO). To enhance the monitoring reliability driven by parameter mismatches, an Online Parameter Estimation Control (OPEC) is presented. Lyapunov’s stability function is used to develop OPEC’s motor parameter adaptive rule. The conventional SMO suffers from the problem of higher chattering phenomena at the sliding surface, especially at very low and zero speeds. An improved OCRRL-based SMO dissolves this issue. Further, to enhance the performance by eliminating the time required for manual tuning of gains of observers in IASMO and PI controllers in Indirect Field Oriented Control (IFOC) are obtained by the Grey Wolf Optimization (GWO) technique. The effectiveness and performance of the proposed observers are tested and verified for possible operating conditions.