This brief is concerned with the time-varying formation problem for second-order networked multi-agent systems, which are subject to random communication delays and packet dropouts in the sensor-to-controller and controller-to-actuator channels of each agent. A cloud-based time-varying formation predictive control method with control input quantization is proposed to actively compensate for those random communication constraints. A definition of quantized time-varying formation is given, and then a necessary and sufficient condition to achieve the quantized time-varying formation as well as the stability of the resulting closed-loop system is obtained, which is independent of random communication constraints and quantization errors. Simulation results are provided to verify the effectiveness of the proposed method.

Dear Editor, This letter investigates a novel stealthy false data injection (FDI) attack scheme based on side information to deteriorate the multi-sensor estimation performance of cyber-physical systems (CPSs). Compared with most existing works depending on the full system knowledge, this attack scheme is only related to attackers' sensor and physical process model. The design principle of the attack signal is derived to diverge the system estimation performance. Next, it is proven that the proposed attack scheme can successfully bypass the residual-based detector. Finally, all theoretical results are verified by numerical simulation.

This paper addresses the cooperative output tracking control problem for a class of leader-following linear heterogeneous networked multi-agent systems subject to random network delays and packet dropouts in the feedback and forward channels of each agent. A state observer is established at the plant side of each agent, and an event-triggering transmission mechanism is introduced to decide which state estimate is transmitted to the corresponding controller so as to save the network resources of the feedback channel. To further compensate for the negative effects of those random communication constraints and the event trigger, a cooperative predictive control scheme with proportional and integral actions is proposed. Then, a necessary and sufficient condition is derived for the stability of the resulting closed-loop system. Finally, simulation results are given to show the effectiveness of the proposed scheme.

This paper presents a observer-based fault estimation method for a class of singularly perturbed systems subjected to parameter uncertainties and time-delay in state and disturbance signal with finite energy. To solve the estimation problem involving actuator fault and sensor fault for the uncertain disturbed singularly perturbed systems with time-delay, the problem we studied is firstly transformed into a standard H-infinity control problem, in which the performance index gamma represents the attenuation of finite energy disturbance. By adopting Lyapunov function with the epsilon-dependence, a sufficient condition can be derived which enables the designed observer to estimate different kinds of fault signals stably and accurately, and the result obtained by dealing with small perturbation parameter in this way is less conservative. A novel multi-objective optimization scheme is then proposed to optimal disturbance attenuation index gamma and system stable upper bound epsilon* , in this case, the designed observer can estimate the fault signals better in the presence of interference when the systems guarantee maximum stability bound. In the end, the validity and correctness of proposed scheme is verified by comparing the error between the estimated faults and the actual faults.

This paper proposes a composite control method that integrates an active fault-tolerant predictive control scheme and an event-triggered mechanism for networked multi-agent systems. The approach considers random communication constraints in the forward and feedback channels as well as actuator faults. At each time instant, the event trigger determines whether to send system outputs based on the current system state. A Kalman filter is then utilized to estimate both the system state and potential faults by incorporating system output information transmitted through the feedback channel. Concurrently, iterative predictions are performed according to the established system model. Furthermore, a predictive sequence of control inputs is generated through the designed control protocol. Leveraging timestamping technology, the system precisely applies the appropriate control commands to the actuator at designated moments. As a result, the proposed control method compensates for both random communication constraints and actuator faults while effectively reducing data transmission over the communication network. Finally, the proposed method is validated through numerical simulations.

This paper addresses the time-varying formation control problem of second-order networked multi-agent systems consisting of a virtual leader and multiple followers, where random communication constraints in the forward and feedback channels as well as actuator and sensor faults are considered. A state observer is designed to estimate the system state and the potential faults, based on which a time-varying formation active fault-tolerant predictive control scheme is proposed. Then, a necessary and sufficient condition is derived to guarantee the stability of the closed-loop system and to achieve the time-varying formation, which is independent of random communication constraints as well as actuator and sensor faults. Finally, simulation results of three contrastive cases are presented to verify the effectiveness of the proposed control scheme.