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140122 ||| eng |
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|a 9783642875168
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|a Curtain, Ruth F.
|e [editor]
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| 245 |
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|a Modelling, Robustness and Sensitivity Reduction in Control Systems
|h Elektronische Ressource
|c edited by Ruth F. Curtain
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| 250 |
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|a 1st ed. 1987
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| 260 |
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|a Berlin, Heidelberg
|b Springer Berlin Heidelberg
|c 1987, 1987
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| 300 |
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|a IX, 494 p
|b online resource
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|a A guide to H? -control theory -- Nonlinear interpolation theory in H? -- Super-optimal Hankel norm approximations -- Hankel norm approximation for infinite dimensional systems and Wiener-Hopf factorization -- Imaginary-axis zeros in multivariable H? -optimal control -- A polynomial approach to H? -optimization of control systems -- Bounds on the achievable accuracy in model reduction -- Recent and new results in rational L2 -approximation -- Design examples using ?-synthesis: Space shuttle lateral axis FCS during reentry -- A necessary and sufficient condition for robustness of stability under known additive perturbation -- Recursive methods for control design based on approximate models -- Performance-robust design via a multi-criteria/multi-model approach — a flight control case study -- Unfalsified modelling in dynamical systems -- Approximative inversion of positive matrices with applications to modelling -- The periodic prediction problem for cyclostationary processes — an introduction -- System identification: design variables and the design objective -- Approximate modelling of deterministic systems -- Some new results on and applications of an algorithm of Agashe -- An application of H? -design and some computational improvements -- Hankel and Toeplitz operators in linear quadratic and H?-designs -- H?-optimal control, LQG polynomial systems techniques and numerical solution procedures -- Optimal H? -interpolation: a new approach -- Some Min-Max optimization problems in infinite-dimensional control systems -- Control system design to minimize maximum errors -- Implications of a characterization result on strong and reliable decentralized control -- Sensitivity minimization as a Nevanlinna-Pick interpolation problem -- The spectral factorization problem for SISOdistributed systems -- 7. List of Participants
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| 653 |
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|a Applied Dynamical Systems
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| 653 |
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|a Computer simulation
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| 653 |
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|a Computer Modelling
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| 653 |
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|a Nonlinear theories
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| 653 |
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|a Dynamics
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| 041 |
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|a eng
|2 ISO 639-2
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| 989 |
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|b SBA
|a Springer Book Archives -2004
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| 490 |
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|a NATO ASI Subseries F:, Computer and Systems Sciences
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| 028 |
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|a 10.1007/978-3-642-87516-8
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| 856 |
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|u https://doi.org/10.1007/978-3-642-87516-8?nosfx=y
|x Verlag
|3 Volltext
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|a 515.39
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| 520 |
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|a Historically, one of the basic issues in control systems design has been robustness: the ability of a controlled plant to withstand variations in or lack of knowledge of its dynamics. Even if the dynamics of a system are accurately known for purposes of implementation, it is often desirable to design a control system based on a simplified model. Consequently it is essential to be able to guarantee a reasonable performance not only for the nominal plant, but also for its neighbouring perturbations: this is the issue of robustness. Since the beginning of this decade major advances have been made in this area, notably using the H -approach; this term is meant to cover the solution of sensitivity reduction, approximation and model reduction, robustness and related control design problems using the mathematics of Hardy spaces and related areas in Harmonic Analysis. This book contains the proceedings of the NATO Advanced Research Workshop on "Modelling, Robustness and Sensitivity Reduction in Control Systems", which was held at the University of Groningen, December 1986. Its aim was to explore the development of H -design techniques and its ramifications in Systems Theory in a unified and systematic way with the emphasis on recent advances and future directions in this fast developing area. In particular the following inter-related aspects were addressed: H -mathematical foundations, model approximation and robustness in control design, optimal sensitivity reduction, modelling and system identification and signal processing
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