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:

**2006 (Volume 16)**

Number 1

**Optimization of vibration acceleration in a quarter car suspension model**

Andrzej Turnau, Maciej Rosół(Department of Automatics, AGH University of Science and Technology, Kraków, Poland) |

**keywords:** active suspensions, optimal control, LQR

**Lipschitz continuity of fuzzy controller**

Darina Bártová, Jaromir Kukal, Dana Majerová(ICT Prague, Department of Computing and Control Engineering, Czech) |

*ŁA*was used for the realization of the proposed fuzzy controller. The realization of fuzzification and control algorithm is trivial. The only problem is in the defuzzification. Neither Mamdani nor Larsen approaches are continuous in general. Both MOM and COG techniques generate discontinuous output behaviour. That is why we developed a new defuzzification method based on Łukasiewicz algebra. Thus, the proposed technique of defuzzification is based on propositional logic and it helps to realize a class of Lipschitz continuous fuzzy controllers. The controllers were realized in the Matlab environment.

_{sqrt}**keywords:** ?ukasiewicz algebra, square root, Lipschitz continuity, Matlab, fuzzy control

**Predictive feedback approach to structural vibration suppression**

Ryszard Leniowski(Rzeszów University of Technology, Rzeszów, Poland) | Lucyna Leniowska(University of Rzeszów, Rzeszów, Poland) |

The problem of active vibration control of a plate has been vastly researched and described in recent years. Theoretical and experimental results demonstrate the effectiveness of the designed controllers and indicate the potential of control techniques for reducing transient and steady state dynamics in structural acoustic systems. The examples from the computational studies, confirmed that vibration levels could be effectively reduced, however, the implementation procedures are not yet ideal, still exists the gap between experimental and simulations findings. To overcome this problem, authors propose extension for the Fuzzy-PID controller, with an on-line identification technique coupled with a control scheme, for a plate vibration suppression. It is assumed, that the system to be regulated is unknown, the control schemes presented in this work have the ability to identify and suppress a plate vibrations with only an initial estimate of the system order. A prediction method implemented was designed using a neural network (NN) identification algorithm, based on the well-known Runge-Kutta methods. This algorithm is similar to described by Wang and Lin [14], but it uses a computation structure of Runge-Kutta-3/8, with radial cosine basis neural network.

**keywords:** active vibration control, plate vibrations, clamped boundary condition, predictive methods, computer simulation, Runge-Kutta neural network

**Bounding approach to parameter estimation without prior knowledge on modeling error and application to quality modeling in drinking water distribution systems**

Kazimierz Duzinkiewicz(Department of Control Engineering, Faculty of Electrical Engineering and Automatic Control, Gdańsk University of Technology, Poland ) |

**keywords:** modeling errors, bounding method, parameter estimation, uncertain dynamic systems, robust control

**On sliding mode based non linear PID design for position control of permanent magnet synchronous machine with unknown load torque**

L. Nezli, M. Tadjine, M.S. Boucherit(Process Control Laboratory, Electrical Engineering Departement Ecole Nationale Polytechnique, Algers, Algeria) |

**keywords:** non linear PID control, sliding mode, backstepping, PMS machine, robustness, current-position tracking, feedback linearizing control

**The steering of the ship motion: a**

*μ*-synthesis approachWitold Gierusz(Gdynia Maritime University, Gdynia, Poland) |

*H*

_{∞}controller and the parametric and nonparametric uncertainties. The next part presents the requirements which should be fulfilled by regulator to be the robust one and it describes the way how to calculate the multivariable robust controller via D-K iteration. In the last part of the paper exemplary results of the steering process from simulation and the real-time trials illustrates the control quality of the obtained closed-loop system.

**keywords:** training ship, multivariable system, robust control, structured singular value, real-time steering

**Hierarchical stochastic control in a large scale linear system**

Zdzisław Duda(Institute of Automatic Control, Silesian University of Technology, Gliwice, Poland) |

**keywords:** large scale systems, hierarchical control structure, decentralized stochastic control

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