This article investigates the periodic event-triggered sliding mode control problem for switched uncertain Takagi–Sugeno (T-S) fuzzy systems with the external nonlinear disturbance. Firstly, to reduce the utilization of the network bandwidth, a logistic event-triggering scheme is designed, and the triggering threshold can be adaptively adjusted based on the current triggering information. Then, for preventing the controller from using the extra information, an auxiliary function known as the triggering sliding mode function is constructed and added into the triggering condition. The T-S fuzzy event-triggered sliding mode controller and the sampling period are designed simultaneously to deal with structured uncertainty. Then, the sufficient criteria of practical stability and the border of the practical sliding mode region around the specified sliding surface are given, respectively. Finally, the effectiveness of the proposed method is showed by a tunnel diode circuit system model.

In most existing results, event-triggered controllers are designed based on the backstepping design approach for uncertain strict-feedback nonlinear systems (SFNSs). However, the transmitted signals in the event-triggered scheme (ETS) are discontinuous, which makes the repetitive differentiation of virtual control signals undefined. To overcome this deficiency, this article designs an event-triggered adaptive controller for uncertain SFNSs based on the fully actuated system (FAS) approach. Since the system states and the adaptive parameters are only updated at each triggering instant, the original dynamics cannot be completely removed by using the FAS approach, leading to that the asymptotic stability of the control system is difficult to be guaranteed. To handle such a problem, an ETS with the adaptive parameters is constructed based on Lyapunov method to compensate the effect of triggering. As a result, the asymptotic stability of the system can be guaranteed in the presence of nonlinearities without the global Lipschitz condition, and Zeno behavior can be avoided by using the contradiction method. Furthermore, a positive lower bound for interevent intervals can be got by adding a constant into the ETS, which ensures that the system is practically stabilizable under the bounded nonlinearities. Finally, two simulation examples are presented to demonstrate the superiority and effectiveness of the proposed approach.

Recently, event-triggered control has received increasing attention due to its advantages on saving computation and communication resources. For the controller design of nonlinear systems, backstepping method plays a vital role in most existing results. However, the backstepping control with an event-triggered scheme (ETS) merely ensures the practical stability of the system subject to uncertainties. Additionally, backstepping techniques encounter a significant challenge known as “complex explosion” when dealing with high-dimensional systems. To address such issues, this paper proposes an event-triggered adaptive sliding mode control (SMC) scheme for a class of uncertain strict feedback nonlinear systems (SFNSs) based on fully actuated system (FAS) approach. By model transformation, an FAS model of the original systems is obtained, which makes the solution of control law simple and effective. Then, a high-order sliding mode surface is designed based on FAS model, where a hyperbolic tangent function is introduced such that a nonlinear equivalent control law can be synthesized to compensate the effect of ETS. As a result, a sliding mode dynamic with fewer variables is derived. Furthermore, the stability analysis ensures the asymptotic convergence of control system without requiring global Lipschitz conditions. Finally, the effectiveness of the proposed control strategy is also illustrated by a practical example.

The event-triggered sliding mode control (SMC) problem for uncertain networked switched systems with the external unknown nonlinear disturbance is investigated. A neural network (NN) receiving the triggered state is utilized to approximate the external unknown nonlinear disturbance. First, a novel adaptive mode-dependent continuous-time event-triggering scheme (ETS) based on NN weights' estimations is proposed to reduce the burden of the network bandwidth. Then, using the time-varying Lyapunov function method, a novel adaptive NN event-triggered sliding mode controller is established and a dwell-time switching law is obtained, which can guarantee ultimate boundedness, and attain the sliding region around the specified sliding surface for switched systems. Further, a new integral sliding surface that depends on the system states at switching instants and includes the exponential term is proposed. Obtaining the boundary of the sliding mode region relies on the exponential term for continuous-time systems. Moreover, the Zeno behavior can be avoided under the proposed continuous-time ETS by dividing event-triggering signals and switching signals. Finally, a comparative example and a switched Chua's Circuit example are given to illustrate the effectiveness of the proposed method.

In this article, a high-order fully actuated (HOFA) approach is proposed for the output tracking control of flexible servo (FS) systems with uncertainties and disturbances. The dynamics of FS systems is first converted into an HOFA model, based on which the position tracking controller can be synthesized in a straightforward way, and a linear extended state observer (LESO) is constructed to handle the “differential explosion” problem. The controller and observer gains are explicitly solved via the bandwidth parameterization method, which gains a huge benefit for practical use. Furthermore, an LESO-based disturbance observer (DO) is designed to suppress the state estimation errors, which can further improve the control accuracy. The theoretical results of control system stability are provided in an analytical way. Comparative experimental results show that the maximum control errors of the proposed approach are, respectively, reduced by 45.8% and 55.0% relative to some existing methods under uncertainties and disturbances, which demonstrates the superiority of the proposed approach.