2020 (vol. 30) - Number 4

*A.B. Malinowska, R. Kamocki, R. Almeida, T. Odzijewicz:*

On the existence of optimal consensus control for the fractional Cucker--Smale model

*R. Grymin, W. Bożejko, J. Pempera, M. Wodecki, Z. Chaczko:*

Algorithm for solving the Discrete-Continuous Inspection Problem

*T. Kaczorek, A. Ruszewski:*

Global stability of discrete-time nonlinear systems with descriptor standard and fractional positive linear parts and scalar feedbacks

*R. Arora, K. Gupta:*

Fuzzy goal programming technique for multi-objective indefinite quadratic bilevel programming problem

*P. Nowak, J. Czeczot, P. Grelewicz:*

Tuning rules for industrial use of the second-order Reduced Active Disturbance Rejection Controller

*M.I. Gomoyunov:*

Optimal control problems with a fixed terminal time in linear fractional-order systems

*Muhafzan, A. Nazra, L. Yulianti, Zulakmal, R. Revina:*

On LQ optimization problem subject to fractional order irregular singular systems

*M. Blizorukova, V. Maksimov:*

On one algorithm for reconstruction of an disturbance in a linear system of ordinary differential equations

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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