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EN
We provide a framework for hierarchical specification called Hierarchical Decision Process Petri Nets (HDPPNs). It is an extension of Decision Process Petri Nets (DPPNs) including a hierarchical decomposition process that generates less complex nets with equivalent behavior. As a result, the complexity of the analysis for a sophisticated system is drastically reduced. In the HDPPN, we represent the mark-dynamic and trajectory-dynamic properties of a DPPN. Within the framework of the mark-dynamic properties, we show that the HDPPN theoretic notions of (local and global) equilibrium and stability are those of the DPPN. As a result in the trajectory-dynamic properties framework, we obtain equivalent characterizations of that of the DPPN for final decision points and stability. We show that the HDPPN mark-dynamic and trajectory-dynamic properties of equilibrium, stability and final decision points coincide under some restrictions. We propose an algorithm for optimum hierarchical trajectory planning. The hierarchical decomposition process is presented under a formal treatment and is illustrated with application examples.
PL
W artykule przedstawiono analizę stabilności nieliniowej pętli synchronizacji fazy z filtrem o aproksymacji Cauera drugiego rzędu dla dwóch różnych wartości współczynnika falowania. Analizę tą oparto na metodzie Lapunowa, za pomocą której wyznaczono punkty osobliwe pętli i zbadano, czy są one stabilne dla różnych wartości parametrów opisujących układ pętli. Uzyskane wyniki zilustrowano przykładem.
EN
In the paper stability analysis of nonlinear phase-locked loop with second order Cauer lowpass filter for two different values ripple coefficient has been presented. The analysis based on the Lyapunov method, which assistance at definite reinforcement singular points and research its stability for different values describing of the loop system. Presented results were illustrated by an example.
3
Content available remote Colored decision process Petri nets: Modeling, analysis and stability
EN
In this paper we introduce a new modeling paradigm for developing a decision process representation called the Colored Decision Process Petri Net (CDPPN). It extends the Colored Petri Net (CPN) theoretic approach including Markov decision processes. CPNs are used for process representation taking advantage of the formal semantic and the graphical display. A Markov decision process is utilized as a tool for trajectory planning via a utility function. The main point of the CDPPN is its ability to represent the mark-dynamic and trajectory-dynamic properties of a decision process. Within the mark-dynamic properties framework we show that CDPPN theoretic notions of equilibrium and stability are those of the CPN. In the trajectory-dynamic properties framework, we optimize the utility function used for trajectory planning in the CDPPN by a Lyapunov-like function, obtaining as a result new characterizations for final decision points (optimum point) and stability. Moreover, we show that CDPPN mark-dynamic and Lyapunov trajectory-dynamic properties of equilibrium, stability and final decision points converge under certain restrictions. We propose an algorithm for optimum trajectory planning that makes use of the graphical representation (CPN) and the utility function. Moreover, we consider some results and discuss possible directions for further research.
EN
This paper focuses on the hybrid state-feedback guaranteed cost control problem for a class of uncertain linear delay system. Suppose there exist finite candidate controllers with known controller gain matrices and none of the controllers can make the system satisfy guaranteed cost control based on single-Lyapunov function method, sufficient conditions for hybrid state-feedback guaranteed cost control are given and hybrid state-feedback guaranteed control law is constructed. The simulation demonstrates the effectiveness of the method proposed in this paper.
EN
This paper introduces a new robust position variable structure controller design method for robot position systems with parameter perturbations. In most situations, the exact knowledge of the robot dynamics does not exist. For this reason a robust variable structure PD-control scheme is proposed for the set-point regulation problem of robot systems. The controller compensates for the inexact information about the robot system. It uses only some robot bound parameters and measurable joint variables. The sufficient conditions are derived for the existence of a sliding mode in the robot system. The techniques of matrix norm inequalities are often addressed for robustness analysis of the controller. In addition, the stability conditions are also investigated in a global sense. Effective parameter-independent conditions are developed by using a full quadratic form of Lyapunov function. Comparative simulation results with classical PD-controller have been presented indicating that the sliding mode PD-like controller yields faster and smoother performance.
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