Abstract
Fault Detection and Isolation (FDI) using Linear Kalman Filter (LKF) is not sufficient for effective monitoring of nonlinear processes. Most of the chemical plants are nonlinear in nature while operating the plant in a wide range of process variables. In this study we present an approach for designing of Multi Model Adaptive Linear Kalman Filter (MMALKF) for Fault Detection and Isolation (FDI) of a nonlinear system. The uses a bank of adaptive Kalman filter, with each model based on different fault hypothesis. In this study the effectiveness of the MMALKF has been demonstrated on a spherical tank system. The proposed method is detecting and isolating the sensor and actuator soft faults which occur sequentially or simultaneously.
Highlights
Sensors and actuators are playing major role in generating controller output and implementing the control action
The Fault Detection and Isolation (FDI) algorithm consists of making binary decision whether a fault has occurred or not, if fault has occurred isolating the faulty component
The aim of the present study is to develop a Multi Model Adaptive Linear Kalman Filter (MMALKF), which uses multiple Adaptive Linear Kalman Filter (ALKF) each with different hypothesis (Willsky, 1976)
Summary
Sensors and actuators are playing major role in generating controller output and implementing the control action. Malfunction may occur either in plant or in the sensors or in actuators. The controllers are developed by assuming all the sensing and actuating elements are reliable and there is no fault in the system. If bias is present either in the actuator or in the sensor even though control algorithm is advanced one the product quality would not be good. It will affect the economy, safety of the plant and affects the atmosphere. The Fault Detection and Isolation (FDI) algorithm consists of making binary decision whether a fault has occurred or not, if fault has occurred isolating the faulty component. Fault Tolerant Control (FTC) will ensure the continual safe operation of the plant till the scheduled maintenance
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