This article addresses the adaptive bipartite event-triggered output consensus issue for heterogeneous linear multiagent systems. We consider both cooperative interaction and antagonistic interaction between neighbor agents in both fixed and switching topologies. An adaptive bipartite compensator consisting of time-varying coupling weights and dynamic event-triggered mechanism is first proposed to estimate the leader's state in a fully distributed manner. Different from the existing methods, the proposed compensator has three advantages: 1) it does not depend on any global information of the network graph; 2) it avoids the continuous communication between neighbor agents; and 3) it is applicable for the signed communication topology. Assume that the system states are unmeasurable, and we thus design the state observer. Based on the devised compensator and observer, the distributed control law is developed such that the bipartite event-triggered output consensus problem can be achieved. Moreover, we extend the results in fixed topology to switching topology, which is more challenging in that state estimation is updated in two cases: 1) the interaction graph is switched or 2) the event-triggered mechanism is satisfied. It is proven that no agent exhibits Zeno behavior in both fixed and switching interaction topologies. Finally, two examples are provided to illustrate the feasibility of the theoretical results.

This article presents a novel event-driven guaranteed cost control method for nonlinear systems subject to actuator faults. For the purpose of handling the problem of actuator faults and obtaining the event-driven approximate optimal guaranteed cost control approach for general nonlinear dynamics, the reinforcement learning (RL) algorithm is utilized to develop a sliding-mode control (SMC) strategy. To begin with, the unknown faults can be estimated by designing a fault observer. Meanwhile, an SMC technique is presented aiming at countering the effect of abrupt faults. In addition, the optimal performance of the equivalent sliding mode dynamics is considered, then an event-driven guaranteed cost control mechanism is implemented by using RL principle. In the control process, a general cost function, which has a simpler structure, is given to reduce the computation complexity. At the same time, a modified cost function is approximated to obtain optimal guaranteed cost control by using a single critic neural network (NN). In addition, a modified weight update law for critic NN is presented to relax the persistence of excitation (PE) condition. Moreover, a newly triggering condition, which is easy to be implemented, is designed, and the critic NN update law makes sure that the system states are stable. Furthermore, in light of the Lyapunov analysis, it is demonstrated that the developed event-driven control method guarantees the uniformly ultimately bounded (UUB) property of all the signals. Finally, three simulation results are given to validate the designed control method.

In this paper, by incorporating the event-triggered mechanism and the adaptive dynamic programming algorithm, a novel near-optimal control scheme for a class of unknown nonlinear continuous-time non-zero-sum (NZS) differential games is investigated. First, a generalized fuzzy hyperbolic model based identifier is established, using only the input-output data, to relax the requirement for the complete system dynamics. Then, under the event-based framework, the coupled Hamilton-Jacobi equations are derived for the multiplayer NZS games. Then, the adaptive critic design method is employed to approximate the optimal control policies; thus, an identifier-critic architecture is developed to obtain the event-triggered controller. By the virtue of the Lyapunov theory, a state-dependent triggering condition, which is different from the existing works, is developed to achieve the stability of the closed-loop control system both for the continuous and jump dynamics. Finally, two numerical examples are simulated to substantiate the feasibility of the analytical design.

This article studies an event-triggered communication and adaptive dynamic programming (ADP) co-design control method for the multiplayer nonzero-sum (NZS) games of a class of nonlinear discrete-time wireless sensor-actuator network (WSAN) systems subject to input constraints. By virtue of the ADP algorithm, the critic and actor networks are established to attain the approximate Nash equilibrium point solution in the context of the constrained control mechanism. Simultaneously, as the sensors and actuators are physically distributed, a decentralized event-triggered communication protocol is presented, accompanied by a dead-zone operation which avoids the unnecessary events. By predefining the triggering thresholds and compensation values, a novel adaptive triggering condition is derived to guarantee the stability of the event-based closed-loop control system. Then resorting to the Lyapunov theory, the system states and the critic/actor network weight estimation errors are proven to be ultimately bounded. Moreover, an explicit analysis on the nontriviality of the interevent times is also provided. Finally, two numerical examples are conducted to validate the effectiveness of the proposed method.

The secure practical fault-tolerant output regulation of multiagent systems (MASs) with denial-of-service (DoS) attacks is considered in this paper. Different from most existing output regulation problems: 1) The leader matrix is only known to a part of followers; 2) The communication networks are unreliable and there exist DoS attacks; 3) Actuator faults exist in the MASs. Firstly, to overcome the impact of DoS attacks, the adaptive edge-event-triggered observer is designed to estimate the leader's matrix and state. The novel edge-event-triggered mechanism enables asynchronous intermittent communication between agents, and the adaptive learning rate makes the observer design independent of the global information for the communication topology. Secondly, in order to compensate for the impact of actuator faults on system stability, a novel resilient adaptive event-triggered fault-tolerant controller is designed, and it has zero-order holder (ZOH) characteristics and avoids chattering phenomenon. Finally, two simulation examples well show the effectiveness of our developed methods.

This article addresses the decentralized control problem of continuous-time nonlinear large-scale interconnected systems by the means of echo state network (ESN). The interconnected terms between the subsystems are treated as the disturbances added to the system dynamics, then the control problem is solved by the proposed robust controllers. By designing a cost function for the nominal subsystems, the robust controller is obtained by solving optimal controllers. The stability of the interconnected systems is proved by a composite Lyapunov function. The online adaptive dynamic program (ADP) method is employed to solve the transformed optimal problem, where a single ESN is utilized to approximate the critic cost and control policy. The optimal control policies of all the isolated subsystems are obtained simultaneously. The closed-loop stability of the feedback nominal systems is also proved, in a uniformly ultimately boundedness (UUB) manner. In the simulation, a large-scale interconnected system with four subsystems is provided to verify the effectiveness of the proposed decentralized controllers.