Active fault-diagnosis method using adaptive allocator and fault-tolerant adaptive control system design

Abstract

A new approach to the active fault diagnosis (AFD) for input redundant plants is presented in this paper. A test signal which helps the diagnosis is injected to the plant in addition to nominal control input in the AFD typically. One feature of the proposed AFD is adaptive allocation of the test signal. The adaptive allocator which distributes the test signal and injects it to the redundant actuators is introduced in this paper. A fault-diagnosis (FD) system that estimates fault location and its magnitude from adaptive parameter of the adaptive allocator is constructed with a simple neural network (NN) model. Furthermore, a A fault-tolerant adaptive control system which includes the adaptive test signal allocator is designed based on the model reference adaptive control (MRAC) technique. The adaptive laws of the adaptive allocator and controller are derived by using a suitable Lyapunov function. By performing experiments using a two-input redundant plant, we show the effectiveness and applicability of the proposed AFD and MRAC system.

two-step detection method for actuator and sensor failures based on self-repairing PID control

“…As a countermeasure to this problem, our previous works have proposed a self-repairing PID (SRPID) control for plants with sensor failures that exploits an I-controller (an integrator) and an auxiliary signal to detect failures exactly (Takahashi, 2016). The SRPID belongs to a class of active fault-tolerant controls (AFTC) (Jiang, Staroswiecki, & Cocquempot, 2003;Wang, Zhou, Qin, & Wang, 2008;Kawaguchi, Araki, Sato, Kuroda, & Asami, 2020). Compared to the other AFTCs, one of the advantages is that no information about the plants is necessary to detect failures.…”

Adaptive rapid neural observer-based sensors fault diagnosis and reconstruction of quadrotor unmanned aerial vehicle

“…The fault detection (FD) and isolation approach is suggested for the quadrotor unmanned aerial vehicle with the consideration of total or partial actuator failure; in their approach, they have used linear time-varying observer for the actuator FD (Guzm an-Rabasa et al, 2019). The active fault diagnosis is presented by Kawaguchi et al (2020); the significant property of their approach is the adaptive allocation of the signal, in which they have used neural network (NN) for the adaptive approximation, and the FTC is also presented based on the model reference adaptive control method. The radial basis functions neural network technique is used for the identification and classification of internal fault current of power transformer (Umasankar & Kalaiarasi, 2014).…”