This paper focuses on the speed regulation of a permanent-magnet synchronous motor (PMSM) with an uncertain extended load disturbance. A novel super-twisting sliding-mode control (NSTSMC) was proposed via a nonlinear integral sliding surface and a modified reaching law, effectively suppressing the chattering phenomenon. In addition, the NSTSMC can improve the convergence performance with a 0.04 s settling time, satisfying the super-twisting algorithm stability condition. For the novel integral sliding surface, the integral power term of the system state variables was incorporated into the conventional sliding surface to effectively improve the convergence rate and anti-disturbance ability. Moreover, an extended sliding-mode disturbance observer (ESO) was used to estimate the lumped extended disturbance and add the corresponding feedback compensation value from the sliding-mode disturbance observer to the output of the speed controller for the improved robustness of the system. The ESO-NSTSMC was developed to improve the performance of PMSM speed regulation by combining the advantages of the novel integral sliding surface, achieving a settling time of 0.01 s without overshoot. We confirm the performance of the proposed NSTSMC through a PMSM speed simulation and demonstrate that the controller can enhance the dynamic performance and robustness of the system.

In this article, a novel strategy called enhanced super-twisting active disturbance rejection control (ESTADRC), as well as a nonlinear observer (NOB), is used to implement a speed control scheme for permanent-magnet synchronous motors with intricate internal dynamics, and it exhibits nonlinearity and variable parameters. A new reaching law is formulated within a super-twisting sliding mode control (STSMC) framework, and a comprehensive procedure for finite convergence time analysis is provided. The convergence region of the state variables of the system is obtained using a Lyapunov function. ESTADRC is developed by integrating STSMC and linear active disturbance rejection control (LADRC), whereas the NOB is employed to estimate the motor’s position or angle value. Simulations demonstrated that the proposed approach is valid and effective compared with super-twisting active disturbance rejection control and LADRC.

In this study, a sliding-mode controller is designed using an adaptive reaching law with a super-twisting algorithm. A dynamic model of a drone is designed with a quadrotor that has four motors and considers disturbances and model uncertainties. Given that the drone operates as an under-actuated system, its flight stability and maneuverability are influenced by the discontinuous signal produced by the reaching law of the sliding-mode control. Therefore, this study aims to improve the sliding-mode control and stability of drone flight using the proposed adaptive law, which is based on exponential properties. The discontinuous signal of a conventional strategy is overcome using the super-twisting algorithm, and the drone rapidly reaches equilibrium using the proposed adaptive law that utilizes the sliding surface value. The proposed control strategy covers a higher dimension than the conventional sliding-mode control strategy; the system stability is proven using the strict Lyapunov function. The reaching time estimation results are introduced and used to compare the respective reaching times of the control strategies. To verify the superior performance of the proposed control method, multiple experiments are conducted under various situations and realizations. The simulation results prove that the proposed control method achieved a superior rapid response, stable maneuvering, and robustness with shorter reaching time.