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Abstract
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Article Information:
Sensor and Actuator Fault Detection and Isolation in Nonlinear System using Multi Model Adaptive Linear Kalman Filter
M. Manimozhi and R. Saravana Kumar
Corresponding Author: M. Manimozhi
Submitted: October 19, 2013
Accepted: November 12, 2013
Published: May 05, 2014 |
Abstract:
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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.
Key words: Fault detection and isolation, multi model adaptive linear kalman filter, nonlinear, residual generation, Spherical tank , state estimation,
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Cite this Reference:
M. Manimozhi and R. Saravana Kumar, . Sensor and Actuator Fault Detection and Isolation in Nonlinear System using Multi Model Adaptive Linear Kalman Filter. Research Journal of Applied Sciences, Engineering and Technology, (17): 3491-3498.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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