Much recently, an internal model approach from output regulation theory has been adopted to solve the speed tracking control problem of permanent magnet synchronous motor (PMSM) system on simulation level. A striking advantage of this approach is that it can achieve multiple goals including trajectory tracking, disturbance rejection and robustness simultaneously. This paper further studies a position tracking control problem of PMSM system under nonlinear load torque disturbance. A nonlinear internal model based output feedback controller is proposed, which can achieve exact position tracking and allow certain parameter uncertainties. Besides simulation results, a real-time experimental setup is built and experimental results are provided to illustrate the effectiveness of the proposed controller. It is worth mentioning that the proposed controller can lead to a high precision position tracking performance under nonlinear load torque disturbance.

This paper proposes an adaptive tracking control scheme for an electronic throttle valve (ETV) based on recursive terminal sliding mode (RTSM) control strategy in the presence of parametric uncertainties and lumped disturbance. The developed RTSM dynamical structure for the controller is composed of a fast nonsingular terminal sliding surface and a recursive integral terminal sliding function, such that not only is the reaching phase eliminated, but also a sequential finite-time zero-convergence of both the recursive sliding surfaces and position tracking error are guaranteed. Due to the difficulty in ensuring a satisfactory tracking performance with respective to a broad range of operation conditions in practice, an adaptive mechanism is further developed to estimate both the lumped uncertainty bound and the sliding mode parameters, such that no prior knowledge of the system is required in the controller leading to the effective improvement of the flexibility and simplicity of sliding mode-based ETV control systems. Comparative experiments are conducted to verify that the proposed control enjoys a fast finite-time convergence and superior robustness with respect to uncertainties and disturbances.