Results 131 to 140 of about 5,845 (148)
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LMI Relaxations in Robust Control
European Journal of Control, 2006zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Robust pole placement in LMI regions
IEEE Transactions on Automatic Control, 1999Summary: We discuss analysis and synthesis techniques for robust pole placement in linear matrix inequality (LMI) regions, a class of convex regions of the complex plane that embraces most practically useful stability regions. The focus is on linear systems with static uncertainty on the state matrix.
Chilali, Mahmoud +2 more
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Rank-one LMIs and Lyapunov's inequality
IEEE Transactions on Automatic Control, 2001The paper proposes an alternative proof of Lyapunov's matrix inequality about the location of the eigenvalues of a matrix in some region of the complex plane. This new proof does not refer to stability of the trajectories of an associated dynamical system and does not use matrix exponentials.
Henrion, D., Meinsma, Gjerrit
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LMI tools for eventually periodic systems
Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301), 2002zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Farhood, Mazen, Dullerud, Geir E.
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2005
This chapter presents an LMI-based method for design of control systems in accordance with the principle of matching and the principle of inequalities. The inputs are assumed to be persistent and/or transient. From the exponential convergence conditions of the unit impulse and the unit step responses, matrix inequalities are derived as a sufficient ...
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This chapter presents an LMI-based method for design of control systems in accordance with the principle of matching and the principle of inequalities. The inputs are assumed to be persistent and/or transient. From the exponential convergence conditions of the unit impulse and the unit step responses, matrix inequalities are derived as a sufficient ...
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Conic sector synthesis - LMI approach
Guidance, Navigation, and Control Conference, 1996An LMI approach for conic sector synthesis is presented. It includes strictly bounded real and strongly positive real synthesis procedures as special cases. The resulting LMI is expressed directly in terms of the original plant state-space matrices.
C.-H. Huang, L. Turan, M. Safonov
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2003
This chapter provides a brief introduction to charged particle optics. It is not meant to be a survey; rather, our intent is to provide enough information to uynderstand how the optical system of focused ion beam system works. We also provide a method to define the resolution of a focused ion beam system in a way that gives a metric for optimization or
Jon Orloff, Mark Utlaut, Lynwood Swanson
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This chapter provides a brief introduction to charged particle optics. It is not meant to be a survey; rather, our intent is to provide enough information to uynderstand how the optical system of focused ion beam system works. We also provide a method to define the resolution of a focused ion beam system in a way that gives a metric for optimization or
Jon Orloff, Mark Utlaut, Lynwood Swanson
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2014
Hamilton invented state space models of nonlinear dynamic systems with his generalized momenta work in the 1800s, but, at that time, the lack of computational tools prevented broad acceptance of the first order form of dynamic equations. With the rapid development of computers in the 1960s, State Space models evoked a formal control theory for ...
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Hamilton invented state space models of nonlinear dynamic systems with his generalized momenta work in the 1800s, but, at that time, the lack of computational tools prevented broad acceptance of the first order form of dynamic equations. With the rapid development of computers in the 1960s, State Space models evoked a formal control theory for ...
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Computational issues in solving LMIs
[1991] Proceedings of the 30th IEEE Conference on Decision and Control, 2002Optimization methods, which have been applied to linear matrix inequality (LMI) problems are described and results are noted. Descent methods are briefly described, and one descent method approached for solving LMI problems is discussed. Convex programming methods and applications are also outlined. Interior point methods are then discussed, and recent
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