The problem of event-triggered prescribed performance control for a class of uncertain nonlinear systems with unknown control directions and faults is investigated. Compared with the existing methods, a new set of error transformation functions is defined for the first time. Although no approximate structure is adopted, prescribed performance control (PPC) and event triggered control (ETC) are realized simultaneously for the nonlinear system considered in this paper for the first time. The proposed control scheme can guarantee that all closed-loop signals are bounded, and the tracking error, as well as all state errors, converges within the adjustable constraint functions. Finally, two simulation experiments verify the effectiveness of the proposed algorithm.

A novel hierarchical control framework combining computed-torque-like control (CTLC) with disturbance-observer-based event-triggered robust model predictive control (DO-ET-RMPC) is proposed for the trajectory tracking control of robotic manipulators with bounded disturbances and state and control input constraints. The CTLC approach is first used to cancel the exact nonlinear dynamics of the original tracking error system to obtain a set of decoupling linear tracking error subsystems, thus reducing the optimization complexity of model predictive control (MPC). The composite DO-ET-RMPC scheme is then developed based on the so-called dual-mode MPC approach to robustly stabilize the tracking error subsystems, which could improve the robustness of MPC and save its computational resources simultaneously. The continuous-time theoretical properties of the DO-ET-RMPC scheme, considering disturbances and state and control input constraints simultaneously, are provided for the first time, including the avoidance of Zeno behavior, robust constraint satisfaction, recursive feasibility, and stability. In the end, the superiorities of the proposed control scheme are verified by the comparative simulations.

This article investigates the integral sliding-mode control (SMC) problem for T-S fuzzy systems via the periodic event-triggered method. First, in order to remove the assumption that the inter-execution time has a uniform upper bound, a novel sliding variable error function is added into the event-triggering mechanism. Second, in order to avoid the extra information transmission, a new sliding-mode switching function consisting of the triggering state information is proposed to design the event-triggered integral SMC (ISMC) law. In addition, the ultimate boundedness of sliding motion can be ensured via using a designed event-triggered ISMC law. A sufficient condition of boundedness is given in the form of linear matrix inequality, which is employed to solve the controller gain matrix. Finally, the effectiveness of theoretical results can be illustrated via three illustrative examples.

This article investigates the event-triggered synchronization control problem of discrete-time neural networks (DNNs) in the case of periodic sampled-data. A discrete-time periodic event-triggered mechanism is adopted to evaluate the measurements, which avoids formulating the triggering function in a continuous manner and saves energy consumption. Under this framework, an event-triggered dynamic output-feedback controller is designed to achieve the goal of synchronization. A piecewise Lyapunov functional is constructed to analyze the sawtooth-like pattern of sampled-error signals. Thereafter, the synchronization criteria are formulated for the considered DNNs. The co-designed issue is further discussed for the control gains and triggering parameter. Finally, a simulation example is presented to show the effectiveness of the proposed method.

In this article, we investigate the periodic event-triggered synchronization of discrete-time complex dynamical networks (CDNs). First, a discrete-time version of periodic event-triggered mechanism (ETM) is proposed, under which the sensors sample the signals in a periodic manner. But whether the sampling signals are transmitted to controllers or not is determined by a predefined periodic ETM. Compared with the common ETMs in the field of discrete-time systems, the proposed method avoids monitoring the measurements point-to-point and enlarges the lower bound of the inter-event intervals. As a result, it is beneficial to save both the energy and communication resources. Second, the "discontinuous" Lyapunov functionals are constructed to deal with the sawtooth constraint of sampling signals. The functionals can be viewed as the discrete-time extension for those discontinuous ones in continuous-time fields. Third, sufficient conditions for the ultimately bounded synchronization are derived for the discrete-time CDNs with or without considering communication delays, respectively. A calculation method for simultaneously designing the triggering parameter and control gains is developed such that the estimation of error level is accurate as much as possible. Finally, the simulation examples are presented to show the effectiveness and improvements of the proposed method.