System Identification for Robust Control Using Noncanonical Bases

System Identification for Robust Control Using Noncanonical Bases PDF Author: GIANONE LÁSZLÓ
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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System Identification for Robust Control Using Noncanonical Bases

System Identification for Robust Control Using Noncanonical Bases PDF Author: GIANONE LÁSZLÓ
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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System Identification for Robust Control

System Identification for Robust Control PDF Author: Qiang Zhan
Publisher:
ISBN:
Category : Robust control
Languages : en
Pages : 298

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System Identification for Robust Control Design

System Identification for Robust Control Design PDF Author: R. L. Kosut
Publisher:
ISBN:
Category :
Languages : en
Pages : 192

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System Identification for Robust Control Design

System Identification for Robust Control Design PDF Author:
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Intergration of System Identification and Robust Controller Designs for Flexible Structures in Space

Intergration of System Identification and Robust Controller Designs for Flexible Structures in Space PDF Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 20

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Fuzzy System Identification and Adaptive Control

Fuzzy System Identification and Adaptive Control PDF Author: Ruiyun Qi
Publisher: Springer
ISBN: 3030198820
Category : Technology & Engineering
Languages : en
Pages : 282

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Book Description
This book provides readers with a systematic and unified framework for identification and adaptive control of Takagi–Sugeno (T–S) fuzzy systems. Its design techniques help readers applying these powerful tools to solve challenging nonlinear control problems. The book embodies a systematic study of fuzzy system identification and control problems, using T–S fuzzy system tools for both function approximation and feedback control of nonlinear systems. Alongside this framework, the book also: introduces basic concepts of fuzzy sets, logic and inference system; discusses important properties of T–S fuzzy systems; develops offline and online identification algorithms for T–S fuzzy systems; investigates the various controller structures and corresponding design conditions for adaptive control of continuous-time T–S fuzzy systems; develops adaptive control algorithms for discrete-time input–output form T–S fuzzy systems with much relaxed design conditions, and discrete-time state-space T–S fuzzy systems; and designs stable parameter-adaptation algorithms for both linearly and nonlinearly parameterized T–S fuzzy systems. The authors address adaptive fault compensation problems for T–S fuzzy systems subject to actuator faults. They cover a broad spectrum of related technical topics and to develop a substantial set of adaptive nonlinear system control tools. Fuzzy System Identification and Adaptive Control helps engineers in the mechanical, electrical and aerospace fields, to solve complex control design problems. The book can be used as a reference for researchers and academics in nonlinear, intelligent, adaptive and fault-tolerant control.

System Identification and Robust Control

System Identification and Robust Control PDF Author: Steen Tøffner-Clausen
Publisher:
ISBN:
Category :
Languages : en
Pages : 335

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Identification for robust control using an H-infinity norm

Identification for robust control using an H-infinity norm PDF Author: Ton J. J. van den Boom
Publisher:
ISBN: 9789061442615
Category :
Languages : en
Pages : 37

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Identification for Robust Control: System Modeling for Synthesis of Control Laws

Identification for Robust Control: System Modeling for Synthesis of Control Laws PDF Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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One of the major theoretical contribution of our project is a new two-degree of freedom controller design approach based on a generic optimal control scheme. This is a new structure how to design optimal pole placement controllers. The scheme (named as a generic two-degree of freedom (G2DF) system) is based on a special (Keviczky-Banyasz, or shortly K-B) parametrization. It was proved that the optimality of this scheme in H2 and/or H sub infinity spaces can be reached by special selection of two serial filters obtained from the solution of low order Diophantine equations and/or Navenlina-Pick approximation paradigm. A new controller refinement technique was introduced which allows to determine the reachable maximum bandwidth under an amplitude constraint for the control action by iteratively redesigning the applied reference model as a new step in the basic iterative scheme. It succeeded to derive a new uncertainty relationship limiting the product of control performance and robustness. In the generic scheme where the investigation was performed the control and identification errors are the same, so this inequality limits the product of the model accuracy and a robustness measure of the closed loop control system. The different separate phases of identification for and design of robust control can properly be handled in a new approach combining the classical "minimum variance" like control with the a concept of "maximum variance" input design for robust identification for control. This "triple" control approach gradually (iteratively or recursively, depending on the applied scheme) improves the frequency spectrum of an initial reference input signal excitation approaching and concentrating on the vital medium frequency domain around the cross-over frequency

Applications of System Identification and Multivariable Robust Control Techniques for a Two-input Two-output System

Applications of System Identification and Multivariable Robust Control Techniques for a Two-input Two-output System PDF Author: Sudarsan Vasudevan
Publisher:
ISBN:
Category :
Languages : en
Pages : 220

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