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Sliding mode controller-observer design for multivariable linear systems with unmatched uncertainty

A. Jafari Koshkouei, Alan S. I. Zinober (2000)

Kybernetika

This paper presents sufficient conditions for the sliding mode control of a system with disturbance input. The behaviour of the sliding dynamics in the presence of unmatched uncertainty is also studied. When a certain sufficient condition on the gain feedback matrix of the discontinuous controller and the disturbance bound holds, then the disturbance does not affect the sliding system. The design of asymptotically stable sliding observers for linear multivariable systems is presented. A sliding...

Sliding-mode pinning control of complex networks

Oscar J. Suarez, Carlos J. Vega, Santiago Elvira-Ceja, Edgar N. Sanchez, David I. Rodriguez (2018)

Kybernetika

In this paper, a novel approach for controlling complex networks is proposed; it applies sliding-mode pinning control for a complex network to achieve trajectory tracking. This control strategy does not require the network to have the same coupling strength on all edges; and for pinned nodes, the ones with the highest degree are selected. The illustrative example is composed of a network of 50 nodes; each node dynamics is a Chen chaotic attractor. Two cases are presented. For the first case the...

Smooth homogeneous asymptotically stabilizing feedback controls

H. Hermes (2010)

ESAIM: Control, Optimisation and Calculus of Variations

If a smooth nonlinear affine control system has a controllable linear approximation, a standard technique for constructing a smooth (linear) asymptotically stabilizing feedbackcontrol is via the LQR (linear, quadratic, regulator) method. The nonlinear system may not have a controllable linear approximation, but instead may be shown to be small (or large) time locally controllable via a high order, homogeneous approximation. In this case one can attempt to construct an asymptotically stabilizing...

Soft computing in modelbased predictive control footnotemark

Piotr Tatjewski, Maciej Ławrynczuk (2006)

International Journal of Applied Mathematics and Computer Science

The application of fuzzy reasoning techniques and neural network structures to model-based predictive control (MPC) is studied. First, basic structures of MPC algorithms are reviewed. Then, applications of fuzzy systems of the Takagi-Sugeno type in explicit and numerical nonlinear MPC algorithms are presented. Next, many techniques using neural network modeling to improve structural or computational properties of MPC algorithms are presented and discussed, from a neural network model of a process...

Soft variable structure control in time-delay systems with saturating input

Przemysław Ignaciuk (2021)

Kybernetika

In order to achieve a short regulation cycle, time-optimal control has been considered in the past. However, the sensitivity to errors and uncertainties, and implementation difficulties in the practical systems, have incited other research directions to meet this objective. In this paper, soft Variable Structure Control (VSC) is analyzed from the perspective of linear time-delay systems with input constraint. The desired fast convergence under a smoothly varying control signal is obtained. The stability...

Stabilization of nonlinear stochastic systems without unforced dynamics via time-varying feedback

Patrick Florchinger (2016)

Kybernetika

In this paper we give sufficient conditions under which a nonlinear stochastic differential system without unforced dynamics is globally asymptotically stabilizable in probability via time-varying smooth feedback laws. The technique developed to design explicitly the time-varying stabilizers is based on the stochastic Lyapunov technique combined with the strategy used to construct bounded smooth stabilizing feedback laws for passive nonlinear stochastic differential systems. The interest of this...

Stabilization of nonlinear stochastic systems without unforced dynamics via time-varying feedback

Patrick Florchinger (2018)

Kybernetika

In this paper we give sufficient conditions under which a nonlinear stochastic differential system without unforced dynamics is globally asymptotically stabilizable in probability via time-varying smooth feedback laws. The technique developed to design explicitly the time-varying stabilizers is based on the stochastic Lyapunov technique combined with the strategy used to construct bounded smooth stabilizing feedback laws for passive nonlinear stochastic differential systems. The interest of this...

Stabilization of partially linear composite stochastic systems via stochastic Luenberger observers

Patrick Florchinger (2022)

Kybernetika

The present paper addresses the problem of the stabilization (in the sense of exponential stability in mean square) of partially linear composite stochastic systems by means of a stochastic observer. We propose sufficient conditions for the existence of a linear feedback law depending on an estimation given by a stochastic Luenberger observer which stabilizes the system at its equilibrium state. The novelty in our approach is that all the state variables but the output can be corrupted by noises...

State elimination for nonlinear neutral state-space systems

Miroslav Halás, Pavol Bisták (2014)

Kybernetika

The problem of finding an input-output representation of a nonlinear state space system, usually referred to as the state elimination, plays an important role in certain control problems. Though, it has been shown that such a representation, at least locally, always exists for both the systems with and without delays, it might be a neutral input-output differential equation in the former case, even when one starts with a retarded system. In this paper the state elimination is therefore extended...

Currently displaying 361 – 380 of 438