Differential Neural Networks for Robust Nonlinear Control

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…a good book that could benefit the researchers and practitioners in the field of intelligent nonlinear control systems. -- International Journal of Adaptive Control and Signal Processing

Product Description
This volume deals with continuous time dynamic neural networks theory applied to the solution of basic problems in robust control theory, including identification, state space estimation (based on neuro-observers) and trajectory tracking. The plants to be identified and controlled are assumed to be a priori unknown but belonging to a given class containing internal unmodelled dynamics and external perturbations as well. The error stability analysis and the corresponding error bounds for different problems are presented. The effectiveness of the suggested approach is illustrated by its application to various controlled physical systems (robotic, chaotic, chemical).

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