2001
DOI: 10.1016/s0096-3003(99)00292-1
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An efficient and stable approach for computation of Lyapunov characteristic exponents of continuous dynamical systems

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Cited by 41 publications
(47 citation statements)
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“…There are many algorithms that can calculate LCEs (Wolf et al, 1985;Rangarajan et al, 1998;Udwadia and Bremen, 2001), in this paper, a simple and high-efficiency algorithm is presented here to calculate Lyapunov characteristic exponents. In this method, QR -factorization is the fundamental solution of the system.…”
Section: The Methods Of Lyapunov Characteristic Exponentsmentioning
confidence: 99%
“…There are many algorithms that can calculate LCEs (Wolf et al, 1985;Rangarajan et al, 1998;Udwadia and Bremen, 2001), in this paper, a simple and high-efficiency algorithm is presented here to calculate Lyapunov characteristic exponents. In this method, QR -factorization is the fundamental solution of the system.…”
Section: The Methods Of Lyapunov Characteristic Exponentsmentioning
confidence: 99%
“…Let z − * be the one-periodic fixed point of the reduced controlled hybrid Poincaré map (21). Determination of this fixed point using expressions (21)- (22) is realized according to the previous section. Moreover, let K = [KǨ], whereK is a scalar.…”
Section: Dimension Reduction Of the Controlled Hybrid Poincaré Mapmentioning
confidence: 99%
“…Based on relations in (22), the controlled hybrid Poincaré map under the OGY control law (23) can be recast as:…”
Section: Reduced-dimension Controlled Hybrid Poincaré Map Under the Omentioning
confidence: 99%
“…LCEs provide a way to characterize the asymptotic behavior of nonlinear dynamical 10.020 systems by measuring the mean exponential growth (or shrinking) of perturbations with respect to a nominal trajectory. LCEs allow to measure the sensitivity of a dynamical system to small changes in initial conditions.…”
Section: Introductionmentioning
confidence: 99%
“…
A general method for accurately computing the Lyapunov characteristic exponents (LCEs) of continuous dynamical systems has been developed in [10]. In this paper, this method is extended to implementations on systems of arbitrary dimensions.
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mentioning
confidence: 99%