Structural Dynamic Systems Computational Techniques and Optimization: Dynamic Analysis and Control Techniques: 14 (Gordon and Breach International Series in Engineering, Technolo) - Hardcover

9789056996581: Structural Dynamic Systems Computational Techniques and Optimization: Dynamic Analysis and Control Techniques: 14 (Gordon and Breach International Series in Engineering, Technolo)

Hardcover

ISBN 10: 9056996584 ISBN 13: 9789056996581

Publisher: CRC Press, 1999

This specific ISBN edition is currently not available.

There are various techniques to optimize either structural parameters, or structural controllers, but there are not many techniques that can simultaneously optimize the structural parameters and controller. The advantage of integrating the structural and controller optimization problems is that structure and controller interaction is taken into account in the design process and a more efficient overall design (lower control force/lighter weight) can be achieved, and also multidisciplinary design optimization can be performed. The down side is that the combined optimization problem is more difficult to formulate and solve, and computations are increased. This volume is a comprehensive treatment of dynamic analysis and control techniques in structural dynamic systems and the wide variety of issues and techniques that fall within this broad area, including the interactions between structural control systems and structural system parameters.

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From the Back Cover

Inspired by the structure of the human brain, artificial neural networks have found many applications due to their ability to solve cumbersome or intractable problems by learning from data. Neural networks can adapt to new environments by learning, and deal with information that is noisy. inconsistent, vague, or probabilistic. This volume of Neural Network Systems Techniques and Applications is devoted to Optimization Techniques, including systems structures and computional methods.
Coverage includes:
* A unified view of optimal learning.
* Orthogonal transformation techniques.
* Sequential constructiive techniques.
* Fast back propagation algorithms.
* Neural networks with nonstationary or dynamic outputs.
* Applications to constraint satisfaction.
* Unsupervised learning neural networks.
* Optimum Cerebellar Model of Articulation Controller systems.
* A new statistical theory of optimum neural learning.
* The role of the Radial Basis Function in nonlinear dynamical systems.
Practitioners, researchers, and students in industrial, manufacturing, mechanical, electrical, and computer engineering will find this volume a unique reference to a diverse array of methods for achieving optimization.|Inspired by the structure of the human brain, artificial neural networks have found many applications due to their ability to solve cumbersome or intractable problems by learning from data. Neural networks can adapt to new environments by learning, and deal with information that is noisy. inconsistent, vague, or probabilistic. This volume of Neural Network Systems Techniques and Applications is devoted to Optimization Techniques, including systems structures and computional methods.
Coverage includes:
* A unified view of optimal learning.
* Orthogonal transformation techniques.
* Sequential constructiive techniques.
* Fast back propagation algorithms.
* Neural networks with nonstationary or dynamic outputs.
* Applications to constraint satisfaction.
* Unsupervised learning neural networks.
* Optimum Cerebellar Model of Articulation Controller systems.
* A new statistical theory of optimum neural learning.
* The role of the Radial Basis Function in nonlinear dynamical systems.
Practitioners, researchers, and students in industrial, manufacturing, mechanical, electrical, and computer engineering will find this volume a unique reference to a diverse array of methods for achieving optimization.

About the Author

Cornelius T. Leondes received his B.S., M.S., and Ph.D. from the University of Pennsylvania and has held numerous positions in industrial and academic institutions. He is currently a Professor Emeritus at the University of California, Los Angeles. He has also served as the Boeing Professor at the University of Washington and as an adjunct professor at the University of California, San Diego. He is the author, editor, or co-author of more than 100 textbooks and handbooks and has published more than 200 technical papers. In addition, he has been a Guggenheim Fellow, Fulbright Research Scholar, IEEE Fellow, and a recipient of IEEE's Baker Prize Award and Barry Carlton Award.

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