Event-triggered-based adaptive sliding mode control for networked linear control systems

This paper investigates the robust stabilization of the adaptive sliding mode control for a class of linear systems subjected to external disturbance via event-triggered communication (ETC) scheme. First, in order to reduce the bandwidth utilization, a discrete ETC scheme is proposed and the networked sliding mode function is derived using the ETC scheme. Based on the derived sliding mode function, a reduced-order networked sliding mode dynamics with communication delay is established. Second, by constructing a Lyapunov–Krasovskii functional (LKF), asymptotic stability and stabilization criteria of the reduced-order sliding mode dynamics are given in the form of linear matrix inequalities. According to the stabilization result, a novel event-triggered-based adaptive sliding mode controller is designed while guaranteeing the reachability of the sliding surface. Finally, simulation results illustrate the effectiveness and merit of the developed method.

Continuous sliding mode control for the translational oscillator with a rotating actuator system

The stabilization and disturbance rejection of the translational oscillator with a rotating actuator (TORA) are considered in this paper. To deal with the control issues, a novel continuous sliding mode control method is designed for the TORA system. Compared with existing sliding mode control methods for the TORA system, the proposed method here is continuous. Specifically, first, a global diffeomorphism is introduced for the model of the TORA system. Then, an elaborate sliding manifold is constructed, and a continuous sliding mode control scheme is developed to ensure the convergence of the sliding manifold. Furthermore, rigorous theoretical analysis is given. Finally, simulation tests are carried out, and the obtained simulation results demonstrate that the proposed method exhibits superior stabilization control performance and strong robustness.

Data-driven model-free adaptive fractional-order sliding mode control for the SMA actuator with prescribed performance

In this paper, a novel data-driven model-free adaptive fractional-order sliding mode controller with prescribed performance is proposed for the shape memory alloy (SMA) actuator. Due to the strong asymmetric saturated hysteresis nonlinear characteristics of the SMA actuators, it is not easy to establish an accurate model and develop an effective controller. Therefore, we present a controller without using the model of the SMA actuators. In other words, the proposed controller depends merely on the input/output (I/O) data of the SMA actuators. To obtain the reasonable compensation for hysteresis, enhance the noise robustness of the controller, and reduce the chattering, a fractional-order sliding mode controller with memory characteristics is employed to improve the performance of the controller. In addition, the prescribed performance control (PPC) strategy is introduced in our work to guarantee the tracking errors converge to a sufficiently small boundary and the convergence rate is not less than a predetermined value which are significant and considerable in practical engineering applications of the SMA actuator. Finally, experiments are carried out, and results reveal the effectiveness and success of the proposed controller. Comparisons with the classical Proportional Integral Differential (PID), model-free adaptive control (MFAC), and model-free adaptive sliding mode control (MFAC-SMC) are also performed.