TEOREMA DE LYAPUNOV- DEMOSTRACIÓN. BÚSQUEDA DE FUNCIONES DE LYAPUNOV. BÚSQUEDA DE FUNCIONES DE LYAPUNOV. BÚSQUEDA. This MATLAB function solves the special and general forms of the Lyapunov equation. funciones de Lyapunov; analisis númerico. 1 Introduction. The synchronization of electrical activity in the brain occurs as the result of interaction among sets of.

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This page was last edited on 6 Octoberat Stability of implicit self-tuning controllers for time-varying systems based on Lyapunov function. Using the recursive equations 13 and 14 into 23for the following relation is obtained.

Lyapunov function – Wikipedia

Figure 2 shows the output responses when, after samples, the system model in Eq. This page has been translated by MathWorks. We do not prove, or claim, that converges to its true values q. For certain classes of ODEs, the existence of Lyapunov functions is a necessary and sufficient condition for stability.

The robust stability analysis of the closed-loop system in presence of parametric interval uncertainties is shown in Figure 1. Then, forthe following is derived: Finally, by taking the funcoones with respect to in 28Eq.


If you place any values inside the brackets, the function errors out. The parameters of the control law for the real systems with unknown parameters are estimated using a recursive least-squares RLS algorithm.

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Definingwhich maps the stable zone inside the unit circle into the outside in the z-plane, then is defined as: If the control law in Eq. Clark [8] studied the stability of self-tuning controllers for time-invariant systems subject to noise, based on the idea of describing the system in a feedback form and using the notion of dissipative-real systems.

Retrieved from ” https: The reference signal is set to the unit step. Self-tuning control of time-varying systems based on GMVC. En forma revisada el 10 de Enero de The nominal system model and the family of system models to be considered in this section are represented as: Select a Web Site Choose a web site to get translated content where available and see local events and offers.

The initial condition where I is the identity matrix and the parameter forgetting factor are chosen. This is machine translation Translated by. The results have been extended to the case where system and measurement noises are considered into the system model.

The representation of the nominal system with input and output is given by: Self-tuning control, generalized minimum variance control, sliding-mode control, discrete-time systems, time-varying systems, Lyapunov function. Therefore, gives the minimum variance control for. Click the button below to return to the English version of the page.

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The main results are the theorems which assure the overall stability of the closed-loop system, lya;unov are proved in a straight way compared with previous stability analysis results.

Lyapunov equations arise in several areas of control, including stability theory and the study of the RMS behavior of systems. From the fourth term of Eq. This model is so-called AR Auto Regressive model.

References [1] Bartels, R. Whereas there is no general technique for constructing Lyapunov functions for ODEs, in many specific cases the construction of Lyapunov functions is known. In order to derive the nominal control law the polynomials and are assumed to have constant and known parameters, represented by: Saitama, Hatoyama, Hikigun, Saitama,Japan.