AIMSA 2000: Artificial Intelligence: Methodology, Systems, and Applications pp 292-300 | Cite as
Fuzzy-Neural Models for Real-Time Identification and Control of a Mechanical System
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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.
Keywords
Friction Force Fuzzy Rule Static Friction Force Friction Compensation Recurrent Neural Network Model
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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