Determination of Model, Implement and Compare New Two Optimal Adaptive Fault Diagnosis Observers with Six Observers
The gain matrix of the observer (OAD) checks the proposed Lyapunov condition using the LMI approach, whereas the gain matrix of the observer (OAL) confirms the proposed Lyapunov condition using the LMI technique. The performance of the observers can be verified using Matlab software by comparing them to six different linear observers: the Luenberger Observer (LO), Kalman (Filter) Observer (KO), Unknown Input Observer (UIO), Augmented Robust Observer (ARO), High Gain Observer (HGO), and Sensitive High Gain Observer (SHGO). The anticipated disturbances and faults include white noise, coloured noise, and non-Gaussian faults, with a MIMO DC servomotor serving as a performance benchmark. The comparative findings reveal that each observer detects effectively, but that more tweaking according to plant type is required to increase activity. The new observers (OAD) and (OAL), on the other hand, are the best at diagnosing faults and disturbances utilising each one’s suggested fault diagnostic criteria, as well as having good state estimation performance.
Ahmad Hussain Al-Bayati
Computer Science Department, University of Kirkuk, Iraq.
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