In this article, we present an active fault tolerant control scheme based on fault detection and isolation (FDI) for a class of uncertain systems subject to sensor faults. The FDI unit consists of a fault detection (FD) module and a fault isolation (FI) module, to determine when and where the sensor fault happens. It is noted that the FD module is based on a proposed adaptive interval observer where adaptive parameters instead of conservative uncertainty bounds are used, as a result, the sensitivity to faults is improved. When the FD module detects a fault, a compensation controller (CC) and an FI module are activated. The CC is designed to maintain some level of performance assuming all sensors are faulty. After the FI module determines the location of the fault, a reconfigured controller is activated to give improved performance with reduced conservatism. Importantly, the unmeasurable states and faulty output are approximated as a linear combination of their upper and lower bounds, and linear parameter are determined by adaptive laws. Finally, a simulation example is utilized to verify the effectiveness of the proposed scheme.
In this paper, the fixed‐time synchronization for complex‐valued bidirectional associative memory (BAM) neural networks with time delays is studied. Based on the fixed‐time stability, the Lyapunov functional method and some inequality techniques, a new criterion is presented to guarantee that the addressed systems achieve synchronization in fixed time and a more accurate estimation independent of the initial conditions is given for the settling time. Meanwhile, a new nonlinear delayed controller different from the existing ones is designed. In the end, two numerical examples are provided to illustrate the effectiveness of the obtained result.
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