In this study, wireless sensor networks and time base generators are used to solve the fixed-time containment control problem in multi-agent systems with fixed topologies. A new event-triggered control protocol is proposed, which combines a fully distributed method and a time base generator (TBG). The goal is to converge the states of all followers to the convex hull formed by the leader. The controller reduces communication and improves control efficiency by integrating a fully distributed control mechanism using wireless sensor networks. In addition, a time base generator (TBG) is added to ensure that the dwell time continues to be pre-specified and independent of initial conditions. Using matrix theory, the original system is transformed into an error system, and its stability is analyzed by the Lyapunov method. The necessary and sufficient conditions for solving the time consensus containment control problem in multi-agent systems are determined and Zeno behavior is avoided. The effectiveness of the proposed control algorithm is illustrated by numerical examples.

Bipartite consensus of nonlinear second-order multi-agent systems with directed communication topology is investigated in this article. A kind of novel event-triggered control protocol is proposed, which based on relative information sensing. Different from some conventional event-triggered control for second-order multi-agent systems, the event-triggered control in distributed way for second-order multi-agent systems is studied in this article, which imply that the controller of each follower only needs to collect the local information. To eliminate too large control gain, the control gain of control protocol is further designed based on adaptive way. Moreover, these control algorithms prove that Zeno behavior can be avoided. Finally, the performance of the proposed control protocols is presented by virtue of two simulation examples.

The current research on iterative learning control focuses on the condition where the system relative degree is equal to 1, while the condition where the system relative degree is equal to 0 or greater than 1 is not considered. Therefore, this paper studies the monotonic convergence of the corresponding dynamic iterative learning controller systematically for discrete linear repetitive processes with different relative degrees. First, a 2D discrete Roesser model of the iterative learning control system is presented by means of 2D systems theory. Then, the monotonic convergence condition of the controlled system is analyzed according to the stability theory of linear repetitive process. Furthermore, the sufficient conditions of the controller existence are given in linear matrix inequality format under different relative degrees, which guarantees the system dynamic performance. Finally, through comparison with static controllers under different relative degrees, the simulation results show that the designed schemes are effective and feasible.

In this study, a nonlinear second-order multi-agent systems containment control method based on compensator is discussed. In order to deal with nonlinear systems with inherent time delay, a new compensator-based control algorithm is proposed. The fully distributed compensator is designed to effectively converge the states of all followers to the convex hull formed by the states of leaders. By introducing a compensator, the errors in the system can be corrected and the influence of time delay on the system can be compensated to ensure that the system can achieve the desired performance and stability. Then, the original system is transformed into an error system by using matrix theory, and the stability of the error system is analyzed by using Lyapunov method, and the sufficient conditions for the solvability of the control problem are obtained. Finally, the effectiveness of the control algorithm is verified by matlab simulation.