In this paper a scheme for detection and isolation of sensor faults in chemical batch reactors is proposed. The scheme is based on a bank of two observers for residual generation which guarantees sensor fault detection and isolation in presence of external disturbances and model uncertainties. In the observers a H∞ approach is adopted for the design of the gains, while the unknown dynamics of the reactor (i.e., the heat released by the reaction) are estimated by an on-line interpolator based on a Radial Basis Functions (RBF) neural network. Finally, the estimates provided by the observers and the sensor measures are processed by a Decision Making System (DMS) that provides information about the faulty sensor and an healthy measure. In order to test the effectiveness of the proposed approach, a simulation case study is developed.

Sensor Fault Detection and Isolation for Chemical Batch Reactors

PIERRI, FRANCESCO
2006-01-01

Abstract

In this paper a scheme for detection and isolation of sensor faults in chemical batch reactors is proposed. The scheme is based on a bank of two observers for residual generation which guarantees sensor fault detection and isolation in presence of external disturbances and model uncertainties. In the observers a H∞ approach is adopted for the design of the gains, while the unknown dynamics of the reactor (i.e., the heat released by the reaction) are estimated by an on-line interpolator based on a Radial Basis Functions (RBF) neural network. Finally, the estimates provided by the observers and the sensor measures are processed by a Decision Making System (DMS) that provides information about the faulty sensor and an healthy measure. In order to test the effectiveness of the proposed approach, a simulation case study is developed.
2006
9780780397972
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11563/13313
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