Abstract
This paper presents a diagnosis scheme based on a linear matrix inequality (LMI) algorithm for incipient faults in a nonlinear system class with unknown input disturbances. First, the nonlinear system is transformed into two subsystems, one of which is unrelated to the disturbances. Second, for the subsystem that is free from disturbances, a Luenberger observer is constructed; a sliding mode observer is then constructed for the subsystem which is subjected to disturbances, so that the effect of the unknown input disturbances is eliminated. Together, the entire system achieves both robustness to disturbances and sensitivity to incipient faults. Finally, the effectiveness and feasibility of the proposed method are verified through a numerical example using a single‐link robotic arm.
Highlights
An electronic system is structurally complex, involving a number of electronic components
This paper presents a diagnosis scheme based on a linear matrix inequality LMI algorithm for incipient faults in a nonlinear system class with unknown input disturbances
Building on the work of Chen and Chowdhury 9, this paper presents an LMI-based fault diagnosis scheme, which is designed for incipient fault detection in nonlinear systems with unknown input disturbances
Summary
An electronic system is structurally complex, involving a number of electronic components. Incipient faults are important in electronic systems, and some common manifestations include zero drift, reduced precision, delayed response, and equipment aging If these potential incipient faults cannot be detected in time, the long-term stable operation of the devices will be affected and, more importantly, they will cause a decline in production capacity and an increase in the cost of production, or even accidents. There have been few reports on slow faults with a small initial value This is because the sliding mode control is essentially a type of continuous nonlinear control, and buffeting is inevitable for the system output, which causes the incipient fault signals to be submerged in the buffeting signals for a long period of time after their generation, they cannot be detected. Building on the work of Chen and Chowdhury 9 , this paper presents an LMI-based fault diagnosis scheme, which is designed for incipient fault detection in nonlinear systems with unknown input disturbances. The adoption of the LMI algorithm relaxes the selection criteria for key parameters in the design, making it easier to obtain these parameters
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
