This article investigates the problem of distributed formation tracking control for second-order multiagent systems with unknown inertias. The leader-follower longitudinal formation control is considered and the target is to make followers achieve the same speed with the leader and maintain a desired longitudinal spacing. To make sure that the transient time is within user’s preset time and the communication and computation resources are reduced, we focus on the event-triggered predefined-time control problem. To solve the problem, we design a node-based event-triggered controller in which coupling weights are updated based on an adaptive mechanism. Moreover, a state transformation is considered, and by analyzing the predefined-time stability of the transformed state, both the predefined-time longitudinal formation and the boundedness of controller are proved. Note that, with the adaptive updating mechanism, the control parameters do not depend on the information of Laplacian matrix and the bounds of unknown inertias. Thus, the formation is scalable for the case where some agents leave or join in the formation. Furthermore, to avoid updating the desired spacing manually when agents join or leave, we propose a fully distributed event-triggered predefined-time desired spacing decision algorithm based on distributed resource allocation algorithm. With the combination of the proposed spacing decision algorithm and controller, the longitudinal formation control is more scalable, time-saving and energy-saving.

This article studies event-triggered control for the prescribed-time bipartite consensus of first-order multiagent systems. For each agent, the new event-triggered control law and triggering condition are constructed without continuous interneighboring communication. Based on the Lyapunov stability theory and the algebraic graph theory, permissible value ranges of the designed parameters are established to guarantee that all agents reach bipartite consensus in a completely prespecified time. Moreover, a comprehensive theoretical discussion is provided to show that the Zeno behavior can be excluded during the whole time span except the prespecified settling time T . The simulation results demonstrate the feasibility of the provided methods.

This article considers the energy-limited denial-of-service attack scheduling problem on remote state estimation under signal-to-interference-plus-noise ratio-based channels. The goal of the attacker is to design the optimal attack strategy to degrade the control performance of cyber-physical systems and to reduce his energy consumption. First, to weigh the importance between the current and future rewards, an optimization problem with a discount factor is formulated, which is used to reflect the attacker’s goal. Next, a Markov decision problem (MDP) is formulated to solve the optimization problem. Due to the difficulty of solving the high-dimensional MDP with unknown transition and reward functions, a value iteration adaptive dynamic programming method is proposed to achieve an approximate optimal solution. Also, convergence analysis of the proposed algorithm is carried out. Finally, simulation results are presented to show the efficiency and feasibility of the obtained results.

This paper studies the leader-following consensus problem for linear and Lipschitz nonlinear multiagent systems where the communication topology has a directed spanning tree with the leader as the root. Due to the constraints of communication bandwidth and storage space, agents can only receive uniform quantized information. We first consider the leader-following consensus problem for linear multiagent systems via quantized control. Then, in order to reduce the communication load, an event-triggered control strategy is investigated to solve the consensus problem for linear multiagent systems with uniform quantization. It is shown that leader-following practical consensus can be achieved and no Zeno behavior occurs in this case. Furthermore, the proposed control strategies are extended to investigate the leader-following consensus problem for multiagent systems with Lipschitz nonlinear dynamics. Simulation results are given to demonstrate the feasibility and effectiveness of the theoretical analysis.

The problems of Extended Strict Positive Realness (ESPR) analysis and synthesis for a class of discrete-time systems with polytopic uncertainty are considered. An equivalent condition of ESPR for discrete-time systems is first given in terms of linear matrix inequalities (LMIs). Moreover, a sufficient condition for the uncertain systems to be robustly stable with ESPR is established by stability with ESPR of vertex systems. Furthermore, a condition on robust stability with ESPR for the uncertain systems is obtained in terms of linear matrix inequalities. Based on this result, a simple approach to the design of a linear state-feedback controller which stabilizes robustly the uncertain systems and achieves ESPR is proposed. A numerical example is worked out to illustrate the efficiency of the proposed approach.

The control problem of networked control systems via output feedback is considered in this paper. In the system, a sensor is connected to a linear controller/actuator via a network. The plant is controlled alternately by an open loop controller and a closed loop controller. Necessary and sufficient conditions for the exponential stability of such systems are derived in terms of the network dwell times and the system parameters. Based on the results, a simple procedure for designing the output feedback controller is presented. Numerical simulation shows the feasibility and efficiency of the proposed method.