Adaptive fuzzy observer-based cooperative control of unknown fractional-order multi-agent systems with uncertain dynamics

Periodic event-triggered modified repetitive control with equivalent-input-disturbance estimator based on T-S fuzzy model for nonlinear systems

In this paper, the periodic signal tracking and the disturbance rejection problems are considered for a class of time-varying delay nonlinear systems with unknown exogenous disturbances under limited communication resources. The Takagi–Sugeno (T-S) fuzzy model is used to approximate the nonlinear system. The developed scheme achieves periodic reference tracking and improves the performance of periodic and aperiodic unknown disturbances rejection effectiveley. This can be operated by incorporating the equivalent-input-disturbance (EID) estimator with the modified repetitive controller (MRC) scheme. Moreover, a fuzzy periodic event-triggered feedback observer (FPETFO) is proposed for the purpose of reducing the computational burden, energy consumption and saving communication resources. The periodic event-triggered technique is designed to observe the occurrence of an event which is described by an error signal. When this error signal exceeds a prescribed threshold, the event occurs and the current data are transmitted; otherwise, there is a zero-order hold to keep data unchanged. The overall system consists of MRC, EID and FPETFO based on a T-S fuzzy model. Then, some sufficient conditions are derived to gurantee the asymptotic stability of the overall system subjected to unknown disturbances using the Lyapunov–Krasovskii functional (LKF) stability theory and linear matrix inequalities (LMIs). The fuzzy state feedback controller and observer gains are designed using the LMI and matrix decomposition approaches. Simulation results illustrate the effectiveness and feasibility of the proposed scheme with comparative study.

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.