In this article, we study the issue of adaptive neural output-feedback controller design for a class of uncertain switched time-delay nonlinear systems with nonlower triangular structure. The prominent contribution of this article is that the delay-dependent stability criterion of nonswitched nonlinear systems is successfully extended to that of switched nonlower triangular nonlinear systems. The design algorithm is listed as follows. First, a switched state observer is designed such that the error dynamic system can be generated. Second, neural networks, adaptive backstepping technique, and variable separation method are, respectively, applied to construct a common controller for all subsystems, in which the Lyapunov-Krasovskii functionals are deliberately constructed such that the average dwell-time scheme can be employed to guarantee the stability and performance of the closed-loop system, despite the existence of time delays. Third, the stability analysis process confirms in detail that all the variables of the closed-loop system are semiglobally uniformly ultimately bounded. Finally, simulation study is given to show the validity of the proposed control approach.

In this article, we propose a dynamic event-triggered adaptive prescribed-time output feedback tracking control strategy for nonlinear systems with unknown external disturbances under denial-of-service (DoS) attacks. The presence of malicious intermittent DoS attacks makes the output signal and states of the system unavailable, which in turn leads to more difficulty in the design of the controller. To overcome the above difficulty, we construct a novel composite observer based on the attack compensator, whereby the system states can be reconstructed. Moreover, with the help of the time-varying constraint function, the prescribed-time tracking control problem for nonlinear systems is transformed into the constraint problem of tracking error. At the same time, a new dynamic event-triggered adaptive prescribed-time safety fuzzy controller is built and remains applicable in the systems that operate continuously after the predefined time. The adaptive fuzzy safety control method proposed in this paper ensures that: i) the tracking error converges to the user-specified region in the predefined time; ii) all signals of the closed-loop system remain bounded under intermittent DoS attacks; iii) the repeated transmission of samples from the controller to the actuator can be further reduced, generating fewer events and saving communication resources. Finally, the simulation results of the single-link robotic arm demonstrate the rationality and effectiveness of the developed control algorithm.

This study investigates a separation principle for the H ₂ control of time‐delay systems with partial observations. The authors first consider the linear quadratic regulation problem for time‐delay systems. Based on the dynamic programming technique, the solution to the controller is given in terms of a backward partial difference Riccati equation. Then the estimation problem is investigated for linear discrete‐time systems in the presence of time‐delays. By employing the innovation analysis approach, the linear minimum‐mean‐square error (LMMSE) estimator is developed in terms of a forward partial difference Riccati equation. The Riccati equation is of the same dimension as the plant. Therefore compared with the conventional augmented approach, the presented approach greatly lessens the computational demand when the delay is large. Finally, they show that the separation principle holds in the following sense: an optimal controller can be obtained from two parts, one associated with the optimal control problem when state variable is available, and the other one associated with the LMMSE estimation problem.