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In this study, to reduce the impact that permanent magnet linear synchronous motor (PMLSM) servo system on the sensitivity of external and internal interferences, an adaptive super-twisting-based nonsingular fast terminal sliding mode control (AST-NFTSMC) scheme is put forward. First of all, the mathematical model of PMLSM contains uncertainties is set up, and the control law is established to make position signal converge to given state asymptotically. Second, by introducing the super-twisting algorithm, the chattering caused by nonlinear switching function in traditional method is weakened. However, in actual industrial situations, it is difficult to determine the boundary of lumped disturbance, which makes the switching gains in super-twisting algorithm cannot be accurately selected. Therefore, an adaptive law is introduced to adjust the switching gains online, so that the gains can be dynamically adjusted within a limited range during operation, so as to further weaken chattering. Finally, the practicability of AST-NFTSMC is proved in theory and verified by system experiments. The experimental results prove that AST-NFTSMC can significantly weaken chattering, and result in robust control performance. [ABSTRACT FROM AUTHOR]

In this work, an efficient robust control scheme is proposed for position control of induction motors based on field-oriented control (FOC). The proposed control scheme consists of three interior loops. In the outer loop, the central controller based on the nonsingular fast terminal sliding mode control (NFTSM) is designed. The objective of this loop is to provide the required stator current in the q-axis for regulating the electromagnetic torque. In the inner loops, two fractional-order PI (FOPI) controllers are designed to provide the stator voltages. Besides, since induction motors have a complex mathematical model, time-varying dynamics, and non-linear structure, to deal with these challenges in the controller design, the quantum neural network (QNN) is presented with a novel framework and employed to estimate the lumped uncertainties. This makes the main contribution of the paper. In addition, to further improve system performance, the parameters of the FOPI controllers are tuned by employing the artificial bee colony (ABC) optimization algorithm. The stability of the proposed control approach is proved by Lyapunov's stability theory. According to the results of the comparative simulation, the superiority of this approach is confirmed. • Addressing the position control of the IM using an effective control approach. • Presenting the QNN with a novel framework. • Estimating the lumped uncertainties using the adaptive QNN. • Combining the merits of the FOPI controllers, and NFTSMC. • Tuning the FOPI controllers using the ABC optimization algorithm. [ABSTRACT FROM AUTHOR]

An adaptive nonsingular fast terminal sliding mode control scheme consisting of an adaptive control term and a robust control term for electromechanical actuator is proposed in this article. The adaptive control term with an improved composite adaptive law can estimate the uncertain parameters and compensate for the modelled dynamical uncertainties. While the robust control term, which is based on a modified nonsingular fast terminal sliding mode control method with fast terminal sliding mode (TSM) reaching law, provides fast convergence of errors, and robustifies the design against unmodelled dynamics. Furthermore, the control method eliminates the singular problems in conventional TSM control. On the basis of the finite-time stability theory and the differential inequality principle, it is proved that the resulting closed-loop system is stable and the trajectory tracking error converges to zero in finite time. Finally the effectiveness of the proposed method is illustrated by simulation and experimental study. [ABSTRACT FROM AUTHOR]

In order to improve the performance in the practical engineering applications including so called low-speed video tracking and large-angle swing scanning imaging at the same time for a three-axis universal inertially stabilized platform (UISP), we propose an adaptive nonsingular fast terminal sliding mode control (ANFTSMC) strategy subjected to the uncertain disturbances and input saturation constraints. First of all, a second-order dynamic model is established with uncertain disturbances and input saturation constraints. Secondly, a nonsingular fast terminal sliding mode controller (NTSMC) is constructed to ensure the system error converges to zero fast in a finite time; meanwhile, a novel reaching law based on a modified normal distribution function is designed to adjust the control gain. Thirdly, an adaptive control law is designed to online estimate the parameters of the lumped uncertain disturbances. Additionally, the stability of the control system is proved by Lyapunov theory. Finally, extensive comparative simulations and experiments are carried out, the results comprehensively show the effectiveness and superiority of the proposed control method, which can accelerate convergence, weaken the chattering, and has the better control accuracy and robust performance both in the low-speed tracking and large-angle swing scanning applications. Moreover, the exact dynamic model and the prior knowledge of the upper bounds of the disturbances are not required during the procedure of the controller design, which make it have more extensive application value in practical engineering. [ABSTRACT FROM AUTHOR]