The Experts below are selected from a list of 747702 Experts worldwide ranked by ideXlab platform
S. Prajna - One of the best experts on this subject based on the ideXlab platform.
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Robust Stability Analysis of Nonlinear Hybrid Systems
IEEE Transactions on Automatic Control, 2009Co-Authors: Antonis Papachristodoulou, S. PrajnaAbstract:We present a methodology for robust Stability Analysis of nonlinear hybrid systems, through the algorithmic construction of polynomial and piecewise polynomial Lyapunov-like functions using convex optimization and in particular the sum of squares decomposition of multivariate polynomials. Several improvements compared to previous approaches are discussed, such as treating in a unified way polynomial switching surfaces and robust Stability Analysis for nonlinear hybrid systems.
R.d. Braatz - One of the best experts on this subject based on the ideXlab platform.
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Global Stability Analysis for discrete-time nonlinear systems
Proceedings of the 1998 American Control Conference. ACC (IEEE Cat. No.98CH36207), 1998Co-Authors: E. Rios-patron, R.d. BraatzAbstract:Developing computationally-efficient nonconservative Stability Analysis tools for generic nonlinear systems has eluded researchers for the past century. While this is a challenging problem, any nonlinear system can be approximated arbitrarily closely as a network of interconnections of linear systems and bounded monotonic nonlinear operators. A computational approach is developed for the Stability Analysis of such networks. The main Stability Analysis tool is formulated as a linear matrix inequality feasibility problem, which can be solved by ellipsoid or interior point algorithms. The nonlinear Stability Analysis tools are applied to artificial neural networks, which are nonlinear process modeling tools that have been heavily studied in the past ten years, and are the only generic black-box nonlinear models significantly used in the process industries. Ideas for future work are outlined.
Antonis Papachristodoulou - One of the best experts on this subject based on the ideXlab platform.
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Robust Stability Analysis of Nonlinear Hybrid Systems
IEEE Transactions on Automatic Control, 2009Co-Authors: Antonis Papachristodoulou, S. PrajnaAbstract:We present a methodology for robust Stability Analysis of nonlinear hybrid systems, through the algorithmic construction of polynomial and piecewise polynomial Lyapunov-like functions using convex optimization and in particular the sum of squares decomposition of multivariate polynomials. Several improvements compared to previous approaches are discussed, such as treating in a unified way polynomial switching surfaces and robust Stability Analysis for nonlinear hybrid systems.
M.-c. Laiou - One of the best experts on this subject based on the ideXlab platform.
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Stability Analysis of systems with nonlinearities
Proceedings of 35th IEEE Conference on Decision and Control, 1996Co-Authors: U. Jonsson, M.-c. LaiouAbstract:Stability Analysis of systems with nonlinearities is considered. Multipliers that describe the nonlinearities are used for the Analysis. It is in particular shown how Popov multipliers can be combined with multipliers for slope restricted nonlinearities. The Stability Analysis can be approximated by a feasibility test for linear matrix inequalities. This requires that we choose a finite dimensional subspace for the set of multipliers. The choice of suitable subspace is discussed and an example is given where a duality argument gives a bound for the possible performance of the multiplier for slope restricted nonlinearities.
P. Khargonekars - One of the best experts on this subject based on the ideXlab platform.
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Computational experiments in robust Stability Analysis
Proceedings of the 36th IEEE Conference on Decision and Control, 1Co-Authors: A. Yoon, P. KhargonekarsAbstract:We take a "computational experiments" approach to robust Stability Analysis problems. Many robust control problems have been shown to be NP hard but in spite of this, it is important to develop effective techniques for solving them. A typical robust Stability Analysis problem is taken and formulated as an optimization problem to which several optimization algorithms are applied.
