2021 (vol. 31) - Number 3

*Vanya R. Barseghyan:*

The problem of control of rod heating process with nonseparated conditions at intermediate moments of time

*Khadidja Bentata , Ahmed Mohammedi, Tarak Benslimane:*

Development of rapid and reliable cuckoo search algorithm for global maximum power point tracking of solar PV systems in partial shading condition

*Jakub Musial, Krzysztof Stebel and Jacek Czeczot:*

Self-improving Q-learning based controller for a class of dynamical processes

*Ramesh Devarapalli and Vikash Kumar:*

Power system oscillation damping controller design: a novel approach of integrated HHO-PSO algorithm

*T. Kaczorek:*

Poles and zeros assignment by state feedbacks in positive linear systems

*Saule Sh. Kazhikenova and Sagyndyk N. Shaltakov, Bekbolat R. Nussupbekov:*

Difference melt model

*R. Almeida and N. Martins, E. Girejko and A.B. Malinowska, L. Machado:*

Evacuation by leader-follower model with bounded confidence and predictive mechanisms

*B. Zhao and R. Zhang, Y. Xing:*

Evaluation of medical service quality based on a novel multi-criteria decision-making method with unknown weighted information

*Stefan Mititelu, Savin Treanta:*

Efficiency in vector ratio variational control problems involving geodesic quasiinvex multiple integral functionals

*D.K. Dash and P.K. Sadhu, B. Subudhi:*

Spider monkey optimization (SMO) – lattice Levenberg–Marquardt recursive least squares based grid synchronization control scheme for a three-phase PV system

*Suresh Rasappan and K.A. Niranjan Kumar:*

Dynamics, control, stability, diffusion and synchronization of modified chaotic colpitts oscillator

ACS Abstract:

**2008 (Volume 18)**

Number 3

**Compensation of the scan-period irregularities in LQG control systems**

Jan Cvejn(University of Pardubice, Faculty of Electrical Engineering and Informatics, Czech Republic) |

Computer-based control applications, especially if they run under general-purpose opera-ting systems, often exhibit variance of the scan period of processing inputs and outputs. Although this phenomenon is usually neglected when discrete control algorithms are used, it can cause worse performance of the control loop in comparison to theoretical case. In this paper we describe a modified discrete LQG control algorithm that takes disturbances of the scan period into account and partially compensates their effect. This modification concerns both the state estimation and generating the control output. We also show that such a controller can be implemented even on relatively simple hardware platforms if the system dynamics is time-invariant.

**keywords:** LQG controller, stochastic control, hybrid systems

**Remarks about DC motor control**

Jerzy Baranowski, Marek Dlugosz, Wojciech Mitkowski(Faculty of Electrical Engineering, AGH University of Science and Technology, Krakow, Poland) |

**keywords:** DC motor control, linear-quadratic control, minimum-energy control, dead-beat control, dead-beat observer, discrete LQ control, nolinear observer, observer optimization, nonlinear dynamical feedback

**Concepts of learning in assembler encoding**

Tomasz Praczyk(Naval University, Gdynia, Poland) |

**keywords:** evolutionary neural networks, reinforcement learning

Regulation of absorption packed column of CO2 using discrete fuzzy input-output linearization

R. Illoul, S. Bezzaoucha(cole Polytechnique Nationale d'Alger, 10 Avenue Hacen Badi, El-Harrach, Algiers, Algeria) | A. Selatnia(Laboratory of Process Control, Department of Chemical Engineering, Ecole Polytechnique Nationale d'Alger, Algiers, Algeria) |

**keywords:** CO2 absorption packed column, MEA, modeling, fuzzy control, PI regulation, input-output linearization

**Accelerator's supervisory control system based on CANbus**

Mirosław Dach(PSI - Paul Scherrer Institut, Villigen, Switzerland) | Jan Werewka(AGH University of Science and Technology, Department of Automatics, Computer Science Laboratory, Kraków, Poland) |

**keywords:** RT systems, distributed systems, field bus, time analysis, CAN, accelerator

**Stable output feedback model predictive control design: LMI approach**

Vojtech Vesely(URPI, Faculty of Electrical Engineering and IT, Slovak University of Technology, Bratislava, Slovak Republic) | Ruth Bars(Budapest University of Technology and Economics, Department of Automation and Applied Information, Budapest, MTA-BME Control Research Group, Hungary) |

**keywords:** model predictive control, quadratic stability, Lyapunov function

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