Adaptive integral backstepping controller for linear induction motors - Omar Mahmoudi; Abdelkrim Boucheta (Institute of Advanced Engineering and Science, 2019)
Linear induction motors offer the possibility to perform a direct linear motion without the nead of mechanical rotary to linear motion transformers. The main problem when controlling this kind of motors is the existence of indesirable behaviours such as end effect and parameter variations, which makes obtaining a precise plant model very complicated. This paper proposes an adaptive backstepping control technique with integral action based on lyapunov stability approach, which can guarantee the convergence of position tracking error to zero despite of parameter uncertainties and external load disturbance. Parameter adaptation laws are designed to estimate mover mass, viscous friction coefficient and load disturbance, which are assumed to be unknown constant parameters; as a result the compensation of their negative effect on control design system. The performance of the proposed control design was tested through simulation. The numerical validation results have shown good performance compared to the conventional backstepping controller and proved the robustness of the proposed controller against parameter variations and load disturbance.