Abstract
A two-layer Recurrent Neural Network Model (RNNM) and an improved Backpropagation-through-time method of its learning are described. For a complex nonlinear plants identification, a fuzzy-neural multi-model, is proposed. The proposed fuzzy-neural model, containing two RNNMs is applied for real-time identification of nonlinear mechanical system. The simulation and experimental results confirm the RNNM applicability.
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Baruch, I.S., Martín Flores, J., Carlos Martínez, J., Nenkova, B. (2000). Fuzzy-Neural Models for Real-Time Identification and Control of a Mechanical System. In: Artificial Intelligence: Methodology, Systems, and Applications. AIMSA 2000. Lecture Notes in Computer Science, vol 1904. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45331-8_28
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DOI: https://doi.org/10.1007/3-540-45331-8_28
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