Fault diagnosis based on observer method

Abstract

With the emergence of large-scale and high-performance modern production system, how to effectively improve the safety performance of the control system has become an urgent problem to be solved.[1] Fault detection and diagnosis as the main means to improve the reliability of the control system have been widely valued. Fault diagnosis is a technique to use the information in the system to detect the faults in time and take corresponding measures to ensure the safety and reliability of the system. In view of the nonlinear systems containing uncertainties, this paper combined with state observer, adaptive control, fuzzy logic, neural network and genetic algorithm are investigated in theory, such as nonlinear system fault diagnosis scheme based on observer. The main research is as follows: Firstly, the research status of fault diagnosis technology is introduced, the main method of fault diagnosis is analyzed systematically, and the fault diagnosis technology based on observer is expounded. Then, the intelligent algorithm is introduced into the control system fault diagnosis, and the fault diagnosis method based on adaptive fuzzy observer is proposed. Finally, the design and performance of the fault diagnosis scheme are verified by a numerical example. The simulation results show that the method is effective for fault diagnosis of nonlinear systems with uncertain factors.