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2017 (vol. 27) - Number 2


W. Bozejko, M. Wodecki:

Discrete Systems: Theory and Applications. Special issue.



G. Bocewicz, Z. Banaszak, I. Nielsen:

Delivery-flow routing and scheduling subject to constraints imposed by vehicle flows in fractal-like networks



W. Bozejko, A. Gnatowski, R. Idzikowski, M. Wodecki:

Cyclic flow shop scheduling problem with two-machine cells



W. Bozejko, M. Uchronski,, Z. Chaczko, M. Wodecki:

Parallel patterns determination in solving cyclic flow shop problem with setups



J. Brodny, S. Alszer, J. Krystek, M. Tutak:

Availability analysis of selected mining machinery



K. Chmielewska, D. Formanowicz, P. Formanowicz:

The effect of cigarette smoking on endothelial damage and atherosclerosis development - modeled and analyzed using Petri nets



A. Galuszka, J. Krystek, A. Swierniak, T. Grzejszczak, C. Lungoci:

Information management in passenger traffic supporting system design as a multi-criteria discrete optimization task



M. Kardynska, J. Smieja:

Sensitivity analysis of signaling pathway models based on discrete-time measurements



J. Kasprzyk, P. Krauze, S. Budzan, J. Rzepecki:

Vibration control in semi-active suspension of the experimental off-road vehicle using information about suspension deflection



M. Koryl, D. Mazur:

Towards emergence phenomenon in business process management



M. Koryl:

Active resources concept of computation for enterprise software



H. Krawczyk, M. Nykiel:

Mobile devices and computing cloud resources allocation for interactive applications



W. Mitkowski, W. Bauer, M. Zagórowska:

Discrete-time feedback stabilization



J. Pempera:

An exact block algorithm for no-idle RPQ problem



K. Rzosinska, D. Formanowicz, P. Formanowicz:

The study of the influence of micro-environmental signals on macrophage differentiation using a quantitative Petri net based model



K. Skrzypczyk , M. Mellado:

Vehicle navigation in populated areas using predictive control with environmental uncertainty handling



W. Bozejko, J. Pempera, M. Wodecki:

A fine-grained parallel algorithm for the cyclic flexible job shop problem




ACS Abstract:

2012 (Volume 22)
Number 4
1.

Two steps piecewise affine identification of nonlinear systems

2.

Flexible job shop problem - parallel tabu search algorithm for multi-GPU

3.

On the application of control models technique to investigation of some ecological and economic problems

4.

Analysis of the job shop system with transport and setup times in deadlock-free operating conditions

5.

Two stage EMG onset detection method

6.

Multi-machine scheduling problem with setup times

7.

Determination of positive realizations with reduced numbers of delays or without delays for discrete-time linear systems

8.

Simulation-based design of monotonically convergent iterative learning control for nonlinear systems

9.

Setpoint weighted PID controller tuning for unstable system using heuristic algorithm

10.

Hierarchical filtration for distributed linear multisensor systems



Two steps piecewise affine identification of nonlinear systems

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J. Stevek, A. Szhucs, M. Kvasnica, M. Fikar, S. Kozak
(Slovak University of Technology, Slovak Rep.)

Given a set of input-output measurements, the paper proposes a method for approximation of a nonlinear system by a piecewise affine model (PWA). First step of the two-stage procedure is identification from input-output data, in order to obtain an appropriate nonlinear function in analytic form.  The analytic expression of the model can be represented either by a static nonlinear function or by a dynamic system and can be obtained using a basis function expansion modeling approach. Subsequently we employ nonlinear programming to derive optimal PWA approximation of the identified model such that the approximation error is minimized. Moreover, we show that approximation of multivariate systems can be transformed into a series of one-dimensional approximations, which can be solved efficiently using standard optimization techniques.

keywords: piecewise affine systems, piecewise linear, approximation, nonlinear systems, orthogonal polynomials, basis function expansion

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Flexible job shop problem - parallel tabu search algorithm for multi-GPU

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W. Bozejko
(Wroclaw University of Technology, Poland)
M. Uchronski
(Wroclaw Centre of Networking and Supercomputing, Poland)
M. Wodecki
(University of Wroclaw, Poland)

In the paper we propose a new framework for the distributed tabu search algorithm designed to be executed with the use of a multi-GPU cluster, in which cluster of nodes are equipped with multicore GPU computing units. The proposed methodology is designed specially to solve difficult discrete optimization problems, such as a flexible job shop scheduling problem, which we introduce as a case study used to analyze the efficiency of the designed synchronous algorithm.

keywords: jobs scheduling, flexible manufacturing, parallel algorithm, discrete optimization

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On the application of control models technique to investigation of some ecological and economic problems

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M. Blizorukova, V. Maksimov
(Ural Federal University and Institute of Mathematics and Mechanics, Russia)

The paper discusses a method of auxiliary controlled models and the application of this method to solving some problems of identification and robust control for differential equations. The objects that the method is suggested to be used are two systems of nonlinear differential equations describing some ecological and economic processes. Two solving algorithms, which are stable with respect to informational noises and computational errors, are presented. The algorithms are tested by model examples.

keywords: controlled models, identification, robust control

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Analysis of the job shop system with transport and setup times in deadlock-free operating conditions

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J. Krystek, M. Kozik
(Silesian University of Technology, Poland)

This paper presents a generalized job-shop problem taking into consideration  transport time between workstations and setups machines in deadlock-free operating conditions. The automated transportation system, employing a number of automated guided vehicles is considered. The completion time of all jobs was applied as the optimization criterion. The created computational application was used to solve this problem in which chosen priority algorithms (FIFO, LIFO, LPT, SPT, EDD and LWR) were implemented. Various criteria were used to assess the quality of created schedules. Numerical results of the comparative research were presented for various criteria and rules of the priority.

keywords: job shop, production schedule, transport, setup time, dispatch rules, deadlock

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Two stage EMG onset detection method

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J. Drapala, K. Brzostowski
(Wroclaw University of Technology, Poland)
A. Szpala, A. Rutkowska-Kucharska
(University School of Physical Education, Wroclaw, Poland)

Detection of the moment when a muscle begins to activate on the basis of EMG signal is important task for a number of biomechanical studies. In order to provide high accuracy of EMG onset detection, we developed novel method, that give results similar to that obtained by an expert. By means of this method, EMG is processed in two stages. The first stage gives rough estimation of EMG onset, whereas the second stage performs local, precise searching. The method was applied to support signal processing in biomechanical study concerning effect of body position on EMG activity and peak muscle torque stabilizing spinal column under static conditions.

keywords: EMG signal processing, real EMG recordings, expectation-maximization, kernel density estimation, event detection

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Multi-machine scheduling problem with setup times

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W. Bozejko
(Wroclaw University of Technology, Poland)
M. Uchronski
(Wroclaw Centre of Networking and Supercomputing, Poland)
M. Wodecki
(University of Wroclaw, Poland)

In this paper we consider a multi-machine scheduling problem with setup times, which is determined in the literature as the flexible job shop problem. It belongs to the strongly NP-complete complexity class. We propose an algorithm based on the tabu search method. The new elimination criteria were used in the construction process of blocks of the critical path.

keywords: jobs scheduling, block properties, discrete optimization

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Determination of positive realizations with reduced numbers of delays or without delays for discrete-time linear systems

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T. Kaczorek
(Bialystok University of Technology, Poland)

A new modified state variable diagram method is proposed for determination of positive realizations with reduced numbers of delays and without delays of linear discrete-time systems for a given transfer function. Sufficient conditions for the existence of the positive realizations of given proper transfer function are established. It is shown that there exists a positive realization with reduced numbers of delays if there exists a positive realization without delays but with greater dimension. The proposed methods are demonstrated on a numerical example.

keywords: state diagram method, determination, linear, discrete-time, delay, realization

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Simulation-based design of monotonically convergent iterative learning control for nonlinear systems

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K. Delchev
(Bulgarian Academy of Sciences, Sofia, Bulgaria)

This paper deals with a simulation-based design of model-based iterative learning control (ILC) for multi-input, multi-output nonlinear time-varying systems. The main problem of the implementation of the nonlinear ILC in practice is possible inadmissible transient growth of the tracking error due to a non-monotonic convergence of the learning process. A model-based nonlinear closed-loop iterative learning control for robot manipulators is synthesized and its tuning depends on only four positive gains of both controllers - the feedback one and the learning one. A simulation-based approach for tuning the learning and feedback controllers is proposed to achieve fast and monotonic convergence of the presented ILC. In the case of excessive growth of transient errors this approach is the only way for learning gains tuning by using classical engineering techniques for practical online tuning of feedback gains.

keywords: simulation-based design, iterative learning control, nonlinear dynamic systems, learning controller, feedback controller

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Setpoint weighted PID controller tuning for unstable system using heuristic algorithm

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V. Rajinikanth
(St.Joseph's College of Engineering, Tamilnadu, India)
K. Latha
(Anna University, Tamilnadu, India)

Most of the real time chemical process loops are unstable in nature and designing a suitable controller for such systems are difficult than open loop stable processes. In this work, an attempt is made with a two degree of freedom setpoint weighted PID controller tuning procedure for a class of unstable systems using the recent heuristic algorithms such as Particle Swarm Optimization and Bacterial Foraging Optimization. The problem considered in this study is to aptly tune the controller in order to enhance the overall closed loop performance. A novel objective function proposed in this study is used to monitor the heuristic algorithms in order to get the optimal controller parameters like Kp, Ki, Kd, and alpha with minimized iteration number. The proposed method is validated with a simulation study and this helps to accomplish enhanced system performance such as smooth reference tracking, satisfactory disturbance rejection, and error minimization for a class of unstable systems.

keywords: setpoint weighted PID, unstable system, particle swarm optimization, bacterial foraging optimization, objective function

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Hierarchical filtration for distributed linear multisensor systems

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Z. Duda
(Silesian Technical University, Poland)

In the paper two filtration algorithms for distributed multisensor system are presented. The first one is derived for a linear dynamical system composed of local subsystems described by local state equations. Local estimates are sent to a central station to be fused and formed an optimal global estimate. The second algorithm is derived for a  system observed by local nodes that determine estimates of the whole system using local information and periodically aggregated information from other nodes. Periodically local estimates are sent to the central station to be fused. Owing to this a reduced communication can be achieved.

keywords: multisensor system, distributed Kalman filtering, decentralized filtration, hierarchical fusion, aggregated information

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