Observer-Based Adaptive Synchronization of Multiagent Systems With Unknown Parameters Under Attacks

Fixed-time synchronization of delayed multiple inertial neural network with reaction-diffusion terms under cyber-physical attacks using distributed control and its application to multi-image encryption

This study examines the fixed-time synchronization (FXTS) problem of delayed multiple inertial neural networks (MINNs) against cyber-physical attacks (CPA) execute an uncertain impulse, using reaction-diffusion (RD) terms. Using fixed-time stability theory, the paper derives innovative and practical criteria for FXTS. It also introduces a MINNs to counteract CPA by executing uncertain impulses with RD terms. Designing security control laws for MINNS with RD terms poses significant challenges, particularly when these networks are tasked with cooperative functions in the presence of failures or attacks. A distributed control strategy is introduced to attain FXTS for the delayed MINNs incorporating RD terms. To examine the consequences of CPA, we will build a Lyapunov function and combine it with some M-matrix properties. Additionally, a security control law is provided to guarantee the FXTS of the consider NN system. The demonstrated settling time (ST) of the designated MINNs is provided. From an algorithmic perspective, it is notable that the security framework and control algorithm are designed to select parameters for the feedback gain matrix and coupling strength to achieve synchronization. A numerical model is provided to support the obtained theoretical findings. Finally, our proposition of a multi-image encryption algorithm, utilizing MINNs and secured by robust security protocols, serves to uphold the integrity of electronic healthcare systems, ensuring the safeguarding of sensitive medical data.

Output Feedback-Based Consensus for Nonlinear Multiagent Systems: The Event-Triggered Communication Strategy

The current investigation explores the leader-following consensus problem for nonlinear multiagent systems under the output feedback control mechanism and the event-triggered communication mechanism. Owing to the physical instrument constraints, a significant portion of the state variables is not readily available. Therefore, this article put forward a distributed event-based leader-following consensus protocol only using agents' relative output measurements and underlying neighbors. Furthermore, this article develops two event-triggered mechanisms simultaneously, one is the event-triggered communication mechanism in the sensor-to-controller channel, and another is the event-triggered controller update in the controller-to-actuator track. Besides that, it is proven that the developed event-triggered control protocol can settle the leader-following consensus problem of the nonlinear multiagent systems, and the Zeno behavior is excluded in both the channels. Finally, we perform two simulation examples to illustrate the efficacy of the obtained results.

A New Event-Triggered Type-3 Fuzzy Control System for Multi-Agent Systems: Optimal Economic Efficient Approach for Actuator Activating

This study presents a new approach for multi-agent systems (MASs). The agent dynamics are approximated by the suggested type-3 (T3) fuzzy logic system (FLS). Some sufficient conditions based on the event-triggered scheme are presented to ensure the stability under less activation of the actuators. New tuning rules are obtained for T3-FLSs form the stability and robustness examination. The effect of perturbations, actuator failures and approximation errors are compensated by the designed adaptive compensators. Simulation results show that the output of all agents well converged to the leader agent under disturbances and faulty conditions. Additionally, it is shown that the suggested event-triggered scheme is effective and the actuators are updated about 20–40% of total sample times.