Abstract
The chapter presents fundamentals of mathematical modeling with special focus on “black box” models. Bio-inspired empirical models—various types of neural networks, hybrid systems with fuzzy logic, fuzzy neural networks and artificial immune systems are commonly used when there is insufficient phenomenological knowledge about objects and processes or when rapid computation is required for solutions. A multilayer perceptron structure (MLP) is used for SOFC fuel cell modeling and the presented Model Predictive Control or immune system optimization may be used in future for fuel cell operation control and optimization.
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Świrski, K. (2011). Advanced Methods in Mathematical Modeling. In: Advanced Methods of Solid Oxide Fuel Cell Modeling. Green Energy and Technology. Springer, London. https://doi.org/10.1007/978-0-85729-262-9_3
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DOI: https://doi.org/10.1007/978-0-85729-262-9_3
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