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This paper proposes a new approach for detecting and isolating faults in a non-linear dynamic process using the multiple model approach. The necessary conditions for the assignability of eigenvalues to a region in the s-plane and the necessary conditions to guarantee the stability of fuzzy models for Takagi-Sugeno (T-S) fuzzy observers are derived. The paper is structured in two stages. The first...
This paper investigates the development of a Supervisory Control System with qualitative tasks at the upper level and simple quantitative models at the lower level to control complex non-linear systems. A new quantitative approach for the stability of non-linear fuzzy inference systems using Takagi-Sugeno (T-S) fuzzy models is presented. The necessary conditions for the assignability of eigenvalues...
This paper presents a novel approach to integrating quantitative and qualitative information in fault-diagnosis. This paper investigates the development of a supervisory control scheme for a non-linear system with qualitative tasks at the upper level and a lower level comprising quantitative model based non-linear control. A new quantitative approach for the stability of non-linear fuzzy inference...
This paper presents a model-based procedure for the detection and isolation of actuator faults in a chemical process. The diagnosis system is based on the estimation of process outputs. A dynamic Multi-input, multiple output (MIMO) process of the process under investigation is obtained by identification procedures, exploiting both Auto Regressive exogenous and Takagi-Sugeno (T-S) fuzzy input-output...
This paper is concerned with the argument that the identification of Takagi Sugeno (T-S) fuzzy models from training data should involve an important feature between data fitness and model complexity. One hand a (T-S) fuzzy model with a large number of fuzzy rules may encounter the risk of having an approximation capable of fitting training data well. On the other hand it may be difficult to run this...
Recent approaches to fault detection and isolation (FDI) for dynamic systems using methods of integrating quantitative and qualitative model information, based upon artificial intelligence (AI) techniques are surveyed. In this study, the use of AI methods is considered an important extension to the quantitative model-based approach for residual generation in FDI. When quantitative models are not readily...
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