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Safe consensus control of cooperative-competitive multi-agent systems via differential privacy

Jiayue Ma, Jiangping Hu (2022)

Kybernetika

This paper investigates a safe consensus problem for cooperative-competitive multi-agent systems using a differential privacy (DP) approach. Considering that the agents simultaneously interact cooperatively and competitively, we propose a novel DP bipartite consensus algorithm, which guarantees that the DP strategy only works on competitive pairs of agents. We then prove that the proposed algorithm can achieve the mean square bipartite consensus and ( p , r ) -accuracy. Furthermore, a differential privacy...

Self-bounded controlled invariant subspaces in measurable signal decoupling with stability: minimal-order feedforward solution

Elena Zattoni (2005)

Kybernetika

The structural properties of self-bounded controlled invariant subspaces are fundamental to the synthesis of a dynamic feedforward compensator achieving insensitivity of the controlled output to a disturbance input accessible for measurement, on the assumption that the system is stable or pre-stabilized by an inner feedback. The control system herein devised has several important features: i) minimum order of the feedforward compensator; ii) minimum number of unassignable dynamics internal to the...

Separation principle for nonlinear systems: a bilinear approach

Mohamed Hammami, Hamadi Jerbi (2001)

International Journal of Applied Mathematics and Computer Science

In this paper we investigate the local stabilizability of single-input nonlinear affine systems by means of an estimated state feedback law given by a bilinear observer. The associated bilinear approximating system is assumed to be observable for any input and stabilizable by a homogeneous feedback law of degree zero. Furthermore, we discuss the case of planar systems which admit bad inputs (i.e. the ones that make bilinear systems unobservable). A separation principle for such systems is given.

Set membership estimation of parameters and variables in dynamic networks by recursive algorithms with a moving measurement window

Kazimierz Duzinkiewicz (2006)

International Journal of Applied Mathematics and Computer Science

The paper considers a set membership joint estimation of variables and parameters in complex dynamic networks based on parametric uncertain models and limited hard measurements. A recursive estimation algorithm with a moving measurement window is derived that is suitable for on-line network monitoring. The window allows stabilising the classic recursive estimation algorithm and significantly improves estimate tightness. The estimator is validated on a case study regarding a water distribution network....

Simple environment for developing methods of controlling chaos in spatially distributed systems

Łukasz Korus (2011)

International Journal of Applied Mathematics and Computer Science

The paper presents a simple mathematical model called a coupled map lattice (CML). For some range of its parameters, this model generates complex, spatiotemporal behavior which seems to be chaotic. The main purpose of the paper is to provide results of stability analysis and compare them with those obtained from numerical simulation. The indirect Lyapunov method and Lyapunov exponents are used to examine the dependence on initial conditions. The net direction phase is introduced to measure the symmetry...

Simplification of the generalized state equations

Tanel Mullari, Ülle Kotta (2006)

Kybernetika

The paper studies the problem of lowering the orders of input derivatives in nonlinear generalized state equations via generalized coordinate transformation. An alternative, computation-oriented proof is presented for the theorem, originally proved by Delaleau and Respondek, giving necessary and sufficient conditions for existence of such a transformation, in terms of commutativity of certain vector fields. Moreover, the dual conditions in terms of 1-forms have been derived, allowing to calculate...

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...

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