This article devotes to investigate the fuzzy optimal consensus problem for multiagent systems (MASs) subject to denial-of-service (DoS) attacks by using the dynamic event-triggered (DET) strategy. The interval type-2 (IT2) fuzzy systems are employed to model the MASs, which combines with the DET fuzzy controller to establish a closed-loop system. Moreover, two piecewise functions are designed, and the triggered interval in a DoS period is decomposed into some subsets with a sampling interval. Therefore, the closed-loop system is reconstructed to facilitate stability analysis. The piecewise Lyapunov-Krasovskii functional is designed, and the system stability is deduced with and without DoS attacks, respectively. By considering the relationship of the piecewise Lyapunov functional, all agents are ensured to be exponentially stable, and the closed-loop system satisfies an optimal control performance. Two examples show the feasibility of the proposed theory finding. Note to Practitioners—Cyberattacks lead to control failure or data breach of MASs due to data tampering and communication interruption. Besides, the controller based on DET mechanism can save limited network resources. Hence, this research focuses on MASs with parameter uncertainties under DoS attacks in interval type-2 fuzzy form, and a DET fuzzy control scheme is proposed to guarantee system security. The Lyapunov-Krasovskii functional with sampling information is constructed to promote stability verification, and slack matrices are also introduced. This study aims to reveal the design principles of DET fuzzy secure control scheme for MASs under DoS attacks. The conducted stability analysis and DET strategy adapt to the background of engineering application.

This brief investigates the robust optimal tracking control for a three Mecanum wheeled mobile robot (MWMR) with the external disturbance by the aid of online actor-critic synchronous learning algorithm. The Euler-Lagrange motion equation of MWMR subject to slipping is established by analyzing the structural characteristics of Mecanum wheels. Concatenating the tracking error with the desired trajectory, the tracking control problem is converted into a time-invariant optimal control problem of an augmented system. Then, an approximate optimal tracking controller is obtained by applying online actor-critic synchronous learning algorithm. With the help of Lyapunov-based analysis, the ultimately bounded tracking can be guaranteed. Finally, simulation results show the effectiveness of synchronous learning algorithm and approximate optimal tracking controller.

In this article, the optimal leader-following consensus of nonlinear second-order delayed multiagent systems with input constraints is addressed. To begin with, a novel intermittent event-triggered (IET) control protocol is proposed, and a novel time-delay piecewise differential inequality is established to effectively integrate state delay, intermittent control, and event-triggered strategy. Then, by the proposed control protocol and inequality, two criteria for the consensus of the second-order delayed multiagent systems and its optimality under input saturation are derived successively. Furthermore, a constrained-input PI algorithm and a critic-only online RL algorithm are devised for designing IET optimal control and approximate IET optimal controller, respectively. Finally, two numerical examples are created to verify the efficacy of the basic research.

This paper focuses on the problem of adaptive tracking for a class of stochastic mechanical control systems with unknown parameters. By reasonably introducing random noise, a method to construct stochastic Lagrangian control systems is given. Under some milder assumptions, an adaptive tracking controller is designed such that the mean square of the tracking error converges to an arbitrarily small neighborhood of zero by tuning design parameters.