Asynchronous robust fuzzy event-triggered control of nonlinear systems

In this article, the disturbance observer (DOB)-based memory integral sliding-mode control (ISMC) is designed for the permanent magnet synchronous motor (PMSM) model subject to mismatched disturbance through the Takagi-Sugeno (T-S) fuzzy approach. Different from the previous studies, a memory-based ISMC scheme that has a constant delay is taken for the first time to design the ISMC for the T-S fuzzy systems. The DOB is given to estimate the disturbances, which are incorporated in the controller design to counteract the disturbance. To fully abide by the model characteristics of the PMSM-based T-S fuzzy systems and DOB, an integral-type fuzzy switching surface function (IFSSF), which involves state-dependent input matrix and memory parameter simultaneously, is defined. From the IFSSF, the fuzzy ISMC is designed to ensure the reachability condition in finite time. Besides that, the designed fuzzy ISMC can effectively attenuate the mismatched disturbances based on the H∞ control theory. Also, a set of sufficient conditions is derived to ensure the global asymptotic stability for the sliding-mode dynamics by the proposed controller. Finally, the applicability of designed DOB-based memory fuzzy ISMC methodology is demonstrated by a controller design for the PMSM model.

Resources limitations of embedded systems and networked control systems have motivated the development of novel controller implementation paradigms in order to reduce the potential conservatism of traditional clock-driven setups. In this context periodic event-triggered control has recently been proposed. Based on a periodically evaluated and state-dependent criterion, it is decided, at every sampling instant, whether the control input needs to be updated or not. In this paper we propose a method for the design of periodic event-triggered controllers for nonlinear systems. We follow an emulation-based approach as we start from a known (continuously evaluated) event-triggered controller and we provide a systematic technique to select the sampling period and to redesign the triggering condition to approximately maintain the guarantees ensured by the original controller. The method is illustrated on a physical system and we compare the obtained results with other available event-based implementations.

In this paper we present a synthesized integral sliding mode controller (ISMC) that can stabilize an underactuated unicycle system. The unicycle consists of a wheel and a saddle that is modeled as an inverse pendulum. The only driving force is the torque applied to the shaft of the wheel, hence it is underactuated. Based on a linear approximation model, a linear controller using LQR method is designed. The control error bound achieved by the linear controller is derived for the unicycle. Next, the matched system nonlinearity of the unicycle is compensated, hence the error bound is reduced. The proposed synthesized ISMC consists of the linear controller, nonlinear compensation, a switching term, and an integral sliding surface. The synthesized ISMC can effectively reject the matched disturbance, and minimize the influence from unmatched disturbances, thus yielding a further reduced error bound.

In this paper, sliding mode controller (SMC) and integral sliding mode controller (ISMC) are designed for a variable speed wind turbine. The main objective of the controller is to optimize the energy captured from the wind at below rated power. To overcome the steady state error, the ISMC is introduced. However, in the presence of large uncertainties, ISMC control approach produces oscillatory phenomenon due to the higher needed gain. To eliminate the tradeoffs between the ISMC tracking performance and the high gain at the control input, we have introduced a new method based on the modification of the output tracking error through the use of the exponential function in order to eliminate the reaching phase. The stability of the proposed ISMC is analyzed by Lyapunov theory and the control action didn't show any chattering. The simulation results of ISMC are presented and the control performance is compared with conventional SMC.

This paper focuses on the fuzzy adaptive predefined-time control for fractional-order nonlinear systems with time-varying deferred constraints. First, a modified dynamic surface control technique is introduced to address the problem of computational complexity exposed in the backstepping framework, and the interval type-2 fuzzy logic systems are applied to model the unknown nonlinearities of the systems. Next, a shifting function and the barrier Lyapunov function with variational barrier bounds are formulated to deal with the constraints issue. Particularly, the constraint conditions can be satisfied within a predetermined time, even if they are transgressed initially. Furthermore, a switching threshold event-triggered controller is devised to balance the control energy and communication resources. With the help of the predefined-time stability criterion, it is proven that the presented predefined-time event-triggered controller can ensure that all the signals involved in the closed-loop system are bounded and the tracking error fluctuates to a small neighborhood of the origin in a predefined-time interval. Finally, two simulation examples are provided to confirm the effectiveness of the put-forward control algorithm.

This paper presents a novel integral sliding mode control (ISMC) for singularly perturbed systems (SPSs) with matched disturbances. Firstly, a linear state feedback control law for the fast subsystem of SPS is designed, and the slow subsystem can be obtained. Secondly, an ISMC incorporating the disturbance estimate provided by a disturbance observer is designed. In order to attenuate matched disturbances, the Lyapunov function is employed to determine the gain of ISMC by solving a linear matrix inequality (LMI). As a result, the closed-loop slow subsystem under the ISMC is exponentially stable, and the full-order SPSs are exponentially stable under the composite control law. Finally, the effectiveness and advantages of the proposed method are demonstrated by simulations.

In this note, the event-triggered adaptive control for a class of uncertain nonlinear systems is considered. Unlike the traditional adaptive event-triggered control, the controller and parameter estimator are event-triggered simultaneously. Asymptotical convergence of stabilization error is guaranteed. To solve this problem, we design a set of event-triggering conditions, which is updated for each triggering. At the same time, the input-to-state stable assumption is not needed. It is shown that the proposed control schemes guarantee that all the closed-loop signals are globally bounded and the stabilization error converges to the origin asymptotically. Simulation results illustrate the effectiveness of our scheme.

Finite-time stabilization of linear systems by bounded event-triggered and self-triggered control

An enhanced tracking control of marine surface vessels based on adaptive integral sliding mode control and disturbance observer

The issue of non-fragile observer-based adaptive integral sliding mode control for a class of Takagi–Sugeno (T-S) fuzzy descriptor systems with uncertainties and unmeasurable premise variables is investigated. General nonlinear systems are represented by nonlinear T-S fuzzy descriptor models, because premise variables depend on unmeasurable system states and fuzzy models have different derivative matrices. By introducing the system state derivative as an auxiliary state vector, original fuzzy descriptor systems are transformed into augmented systems for which system properties remain the same. First, a novel integral sliding surface, which includes estimated states of the sliding mode observer and controller gain matrices, is designed to obtain estimation error dynamics and sliding mode dynamics. Then, some sufficient linear matrix inequality (LMI) conditions for designing the observer and the controller gains are derived using the appropriate fuzzy Lyapunov functions and Lyapunov theory. This approach yields asymptotically stable sliding mode dynamics. Corresponding auxiliary variables are introduced, and the Finsler's lemma is employed to eliminate coupling of controller gain matrices, observer gain matrices, Lyapunov function matrices, and/or observer gain perturbations. An observer-based integral sliding mode control strategy is obtained to assure that reachability conditions are satisfied. Moreover, a non-fragile observer and a non-fragile adaptive controller are developed to compensate for system uncertainties and perturbations in both the observer and the controller. Finally, example results are presented to illustrate the effectiveness and merits of the proposed method.

Finite-time event-triggered consensus control for high-speed train with gradient resistance

This article concentrates on the sliding mode control (SMC) problem of nonlinear unmanned marine vehicles (UMVs) over a finite time horizon. In view of the nonlinearity and variability of the marine environment, the UMVs are characterized by the Takagi-Sugeno (T-S) fuzzy system. To improve the utilization of network resources, a novel adaptive event-triggered protocol is proposed. This protocol can dynamically adjust the threshold parameters in response to denial-of-service (DoS) attacks. An integral sliding mode controller is designed, which can achieve the ideal sliding mode within any given brief time interval. Through the Lyapunov theory, sufficient conditions for finite-time <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathcal {H}_{\infty }$</tex-math></inline-formula> control are given. Compared with existing results, our method presents more robust performance and faster convergence rates. Finally, simulations are presented to confirm the feasibility and effectiveness of the proposed method.

Dynamic event-triggered composite anti-disturbance fault-tolerant tracking control for ships with disturbances and actuator faults

Fuzzy controllers are often used in the standard form of fuzzy sliding-mode controllers. The tuning of the numerous possible parameters of the fuzzy controller for optimal behaviour is difficult and time-consuming. Linguistically represented system knowledge as well as heuristic design principles of a control expert are expressed by fuzzy control principles, and are implemented in order to adapt the nonlinear input output characteristic of the fuzzy sliding-mode controller. Here, a detailed outline for the implementation of the linguistically defined adaptation law is given. Analysing the adaptation strategy, the adaptation algorithm itself proves to be of fuzzy sliding-mode controller type. Using Lyapunov theory, an analytic expression relating system uncertainties with parameter exactness is given. Simulation results for an inverted pendulum with time-varying pendulum length illustrate the effectiveness of the adaptation algorithm.

Adaptive disturbance observer-based event-triggered fuzzy control for nonlinear system