Fault Detection and Identification - a Filter Investigation

TL;DR

This paper presents a new active fault tolerant control system that integrates an unscented Kalman filter for fault detection with a nonlinear model predictive controller, enhancing system reliability.

Contribution

It introduces a novel fault detection and identification approach using an unscented Kalman filter combined with nonlinear model predictive control.

Findings

Successful integration of unscented Kalman filter with nonlinear MPC

Enhanced fault detection and identification capabilities

Improved system robustness and fault tolerance

Abstract

This paper develops a new active fault tolerant control system based on the concept of analytical redundancy. The novel design consists of an observation filter based fault detection and identification system integrated with a nonlinear model predictive controller. A number of observation filters were designed, integrated with the nonlinear controller and tested before reaching the final design which comprises an unscented Kalman filter for fault detection and identification together with a nonlinear model predictive controller to form an active fault tolerant control system design.