Abstract
This paper proposes the application of fault-tolerant control (FTC) using weighted fuzzy predictive control. The FTC approach is based on two steps, fault detection and isolation (FDI) and fault accommodation. Fault detection is performed by a model-based approach using fuzzy modeling. Fault isolation uses a fuzzy decision making approach. The model of the isolated fault is used in fault accommodation with a model predictive control (MPC) scheme. This paper uses a weighted fuzzy predictive control scheme, where fuzzy goals and fuzzy constraints are described in a fuzzy objective function. The criteria (goals or constraints) have an associated weight factor, which are chosen by the decision-maker. Two faults were simulated in a three tank benchmark and the respective fuzzy models were identified. The fuzzy FTC scheme proposed in this paper was able to accommodate the simulated faults.
Keywords
- Fault Detection
- Fuzzy Model
- Model Predictive Control
- Fuzzy Decision
- Fuzzy Goal
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Mendonça, L.F., Sousa, J.M.C., Sá da Costa, J.M.G. (2007). Fault Tolerant Control of a Three Tank Benchmark Using Weighted Predictive Control. In: Melin, P., Castillo, O., Aguilar, L.T., Kacprzyk, J., Pedrycz, W. (eds) Foundations of Fuzzy Logic and Soft Computing. IFSA 2007. Lecture Notes in Computer Science(), vol 4529. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72950-1_72
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DOI: https://doi.org/10.1007/978-3-540-72950-1_72
Publisher Name: Springer, Berlin, Heidelberg
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