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New stability conditions for positive continuous-discrete 2D linear systems

Tadeusz Kaczorek (2011)

International Journal of Applied Mathematics and Computer Science

New necessary and sufficient conditions for asymptotic stability of positive continuous-discrete 2D linear systems are established. Necessary conditions for the stability are also given. The stability tests are demonstrated on numerical examples.

New trends in design of observers for time-delay systems

Olivier Sename (2001)

Kybernetika

This paper presents some recent results about the design of observers for time-delay systems. It is focused on methods that can lead to design some useful observers in practical situations. First the links between observability properties and observers design is emphasized. Then some necessary and sufficient conditions and a method are provided to obtain unknown input observers for time-delay systems. Furthermore some H design using Lyapunov–Krasovskii and Lyapunov–Razumikhin theories are presented...

Nilpotent approximation of a trident snake robot controlling distribution

Jaroslav Hrdina, Radomil Matoušek, Aleš Návrat, Petr Vašík (2017)

Kybernetika

We construct a privileged system of coordinates with respect to the controlling distribution of a trident snake robot and, furthermore, we construct a nilpotent approximation with respect to the given filtration. Note that all constructions are local in the neighbourhood of a particular point. We compare the motions corresponding to the Lie bracket of the original controlling vector fields and their nilpotent approximation.

Nilpotent control systems.

Elisabeth Remm, Michel Goze (2002)

Revista Matemática Complutense

We study the class of matrix controlled systems associated to graded filiform nilpotent Lie algebras. This generalizes the non- linear system corresponding to the control of the trails pulled by car.

Noise Shaping in Neural Populations with Global Delayed Feedback

O. Ávila Åkerberg, M. J. Chacron (2010)

Mathematical Modelling of Natural Phenomena

The interplay between intrinsic and network dynamics has been the focus of many investigations. Here we use a combination of theoretical and numerical approaches to study the effects of delayed global feedback on the information transmission properties of neural networks. Specifically, we compare networks of neurons that display intrinsic interspike interval correlations (nonrenewal) to networks that do not (renewal). We find that excitatory and...

Non-cooperative game approach to multi-robot planning

Adam Gałuszka, Andrzej Świerniak (2005)

International Journal of Applied Mathematics and Computer Science

A multi-robot environment with a STRIPS representation is considered. Under some assumptions such problems can be modelled as a STRIPS language (for instance, a Block World environment) with one initial state and a disjunction of goal states. If the STRIPS planning problem is invertible, then it is possible to apply the machinery for planning in the presence of incomplete information to solve the inverted problem and then to find a solution to the original problem. In the paper a planning algorithm...

Non-exchangeable random variables, Archimax copulas and their fitting to real data

Tomáš Bacigál, Vladimír Jágr, Radko Mesiar (2011)

Kybernetika

The aim of this paper is to open a new way of modelling non-exchangeable random variables with a class of Archimax copulas. We investigate a connection between powers of generators and dependence functions, and propose some construction methods for dependence functions. Application to different hydrological data is given.

Non-fragile controllers for a class of time-delay nonlinear systems

Lubomír Bakule, Manuel de la Sen (2009)

Kybernetika

The paper deals with the synthesis of a non-fragile state controller with reduced design complexity for a class of continuous-time nonlinear delayed symmetric composite systems. Additive controller gain perturbations are considered. Both subsystems and interconnections include time-delays. A low-order control design system is first constructed. Then, stabilizing controllers with norm bounded gain uncertainties are designed for the control design system using linear matrix inequalities (LMIs) for...

Non-fragile estimation for discrete-time T-S fuzzy systems with event-triggered protocol

Fei Han, Wei Gao, Hongyu Gao, Qianqian He (2020)

Kybernetika

This paper investigates the non-fragile state estimation problem for a class of discrete-time T-S fuzzy systems with time-delays and multiple missing measurements under event-triggered mechanism. First of all, the plant is subject to the time-varying delays and the stochastic disturbances. Next, a random white sequence, the element of which obeys a general probabilistic distribution defined on [ 0 , 1 ] , is utilized to formulate the occurrence of the missing measurements. Also, an event generator function...

Non-fragile observers design for nonlinear systems with unknown Lipschitz constant

Fan Zhou, Yanjun Shen, Zebin Wu (2024)

Kybernetika

In this paper, the problem of globally asymptotically stable non-fragile observer design is investigated for nonlinear systems with unknown Lipschitz constant. Firstly, a definition of globally asymptotically stable non-fragile observer is given for nonlinear systems. Then, an observer function of output is derived by an output filter, and a dynamic high-gain is constructed to deal with unknown Lipschitz constant. Even the observer gains contain diverse large disturbances, the observer errors are...

Non-fragile sampled data H filtering of general continuous Markov jump linear systems

Mouquan Shen, Guangming Zhang, Yuhao Yuan, Lei Mei (2014)

Kybernetika

This paper is concerned with the non-fragile sampled data H filtering problem for continuous Markov jump linear system with partly known transition probabilities (TPs). The filter gain is assumed to have additive variations and TPs are assumed to be known, uncertain with known bounds and completely unknown. The aim is to design a non-fragile H filter to ensure both the robust stochastic stability and a prescribed level of H performance for the filtering error dynamics. Sufficient conditions for...

Nonlinear actuator fault estimation observer: An inverse system approach via a T-S fuzzy model

Dezhi Xu, Bin Jiang, Peng Shi (2012)

International Journal of Applied Mathematics and Computer Science

Based on a Takagi-Sugeno (T-S) fuzzy model and an inverse system method, this paper deals with the problem of actuator fault estimation for a class of nonlinear dynamic systems. Two different estimation strategies are developed. Firstly, T-S fuzzy models are used to describe nonlinear dynamic systems with an actuator fault. Then, a robust sliding mode observer is designed based on a T-S fuzzy model, and an inverse system method is used to estimate the actuator fault. Next, the second fault estimation...

Nonlinear analysis of vehicle control actuations based on controlled invariant sets

Balázs Németh, Péter Gáspár, Tamás Péni (2016)

International Journal of Applied Mathematics and Computer Science

In the paper, an analysis method is applied to the lateral stabilization problem of vehicle systems. The aim is to find the largest state-space region in which the lateral stability of the vehicle can be guaranteed by the peak-bounded control input. In the analysis, the nonlinear polynomial sum-of-squares programming method is applied. A practical computation technique is developed to calculate the maximum controlled invariant set of the system. The method calculates the maximum controlled invariant...

Nonlinear Bayesian state filtering with missing measurements and bounded noise and its application to vehicle position estimation

Lenka Pavelková (2011)

Kybernetika

The paper deals with parameter and state estimation and focuses on two problems that frequently occur in many practical applications: (i) bounded uncertainty and (ii) missing measurement data. An algorithm for the state estimation of the discrete-time non-linear state space model whose uncertainties are bounded is proposed. The algorithm also copes with situations when some measurements are missing. It uses Bayesian approach and evaluates maximum a posteriori probability (MAP) estimates of states...

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