Robust Adaptive Control of Induction Motor Based On Perturbation Estimation

This paper investigates a novel robust adaptive control of induction motor based on input-output linearization and perturbation estimation. After representing induction motor as two interconnected subsystems, the lumped term of all nonlinearities, uncertainties and interaction between subsystems are defined as system perturbations and estimated by high-gain perturbation observer. The estimates are employed to achieve the decoupling and robust adaptive linearizing control of flux/speed dynamics. The proposed control can deal with time-varying uncertainties and doesn´t require the detailed model of the induction motor. It can guarantee bounded track errors for bounded time-varying perturbations and achieve asymptotical track when the uncertain parameters converge to unknown constants. The performance of the proposed controller is verified by simulation studies.