Differential Neural Networks for Robust Nonlinear Control is popular PDF and ePub book, written by Alexander S. Poznyak in 2001, it is a fantastic choice for those who relish reading online the Science genre. Let's immerse ourselves in this engaging Science book by exploring the summary and details provided below. Remember, Differential Neural Networks for Robust Nonlinear Control can be Read Online from any device for your convenience.
Differential Neural Networks for Robust Nonlinear Control Book PDF Summary
This book 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, etc.). Contents: Theoretical Study: Neural Networks Structures; Nonlinear System Identification: Differential Learning; Sliding Mode Identification: Algebraic Learning; Neural State Estimation; Passivation via Neuro Control; Neuro Trajectory Tracking; Neurocontrol Applications: Neural Control for Chaos; Neuro Control for Robot Manipulators; Identification of Chemical Processes; Neuro Control for Distillation Column; General Conclusions and Future Work; Appendices: Some Useful Mathematical Facts; Elements of Qualitative Theory of ODE; Locally Optimal Control and Optimization. Readership: Graduate students, researchers, academics/lecturers and industrialists in neural networks.
Detail Book of Differential Neural Networks for Robust Nonlinear Control PDF
- Author : Alexander S. Poznyak
- Release : 01 October 2024
- Publisher : World Scientific
- ISBN : 981281129X
- Genre : Science
- Total Page : 464 pages
- Language : English
- PDF File Size : 18,9 Mb
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