Adaptive Event-Triggered PIO-Based Anti-Disturbance Fault-Tolerant Control for MASs With Process and Sensor Faults
Xiang‐Gui Guo, Bo-Qun Wang, Jianliang Wang, Zheng‐Guang Wu, Lei Guo
Abstract
This article investigates the event-triggered mechanism (ETM)-based anti-disturbance fault-tolerant control problem for multi-agent systems subject to process/sensor faults and external disturbances over undirected graph. A novel proportional-integral observer (PIO) that requires neither the fault derivative information nor the output derivative information is constructed to estimate simultaneously the system states and process/sensor faults and compensate for the disturbances. With the support of the reconstruction information, a fault-tolerant scheme is developed to guarantee the uniform ultimate boundedness in finite time. It is worth mentioning that the proposed PIO can improve the observer accuracy by incorporating a disturbance compensation term and each agent's PIO depends on its own state information only, which makes the PIO structurally simple and computationally inexpensive. Meanwhile, an adaptive Zeno-free ETM, as the first attempt to cope with the situation where process/sensor faults and external disturbances exist simultaneously but the state information is unavailable, is proposed to reduce energy consumption and the frequency of controller updates. Finally, a numerical example demonstrates the effectiveness and merits of the proposed control scheme.