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Fast optimal feedback controller for electric linear actuator used in spreading systems of road spreaders

100%

Dobrowolski D. , Dobrowolski J. , Piekarska W. , Stępień S.

nr 6

Fast optimal feedback controller for electric linear actuator used in spreading systems of road spreaders

100%

Dobrowolski D. , Dobrowolski J. , Piekarska W. , Stępień S.

tom Vol. 67, nr 6

1041--1047

Modern and innovative road spreaders are now equipped with a special swiveling mechanism of the spreading disc. It allows for adjusting asymmetrical or a symmetrical spreading pattern and provides for the possibility to maintain the size of the spreading surface and achieve an accurately defined spreading pattern with spreading widths. Thus the paper presents a modelling and control design methodology, and the concept is proposed to design high-performance and optimal drive systems for spreading devices. The paper deals with a nonlinear model of an electric linear actuator and solution of the new intelligent/optimal control problem for the actuator.

Gillnet selectivity to roach, Rutilus rutilus, from the Szczecin Lagoon, Poland

75%

Psuty I. , Draganik B. , Blady W.

Acta Ichthyologica et Piscatoria

2007

tom 37

nr 1

17-23

Background. Roach, Rutilus rutilus, comprise a large proportion of the total catch in the Szczecin Lagoon, and are caught mainly as bycatch in gillnets targeting perch, Perca fluviatilis. The minimum landing length for roach and perch is 17 cm TL and the minimum mesh size is 30 mm bar length. However, little is known about the selectivity of roach, which may have implications for implementing effective regulations. Consequently, the aims of the study were to estimate roach selectivity curves and to compare the results with perch selectivity. Materials and Methods. The study was based on the length frequency of catch from standardized fishing practice with commercial gillnets of mesh sizes ranging from 25 to 35 mm (bar length) and modelled using various generalized linear models. The best model was selected using deviance criteria. Results. The log-normal selectivity model provided the best fit, with spread relevant to mesh size under the assumption of equal fishing power. The estimated parameters were 18.7 cm and 1.5 (mode and spread of selectivity curve for the smallest mesh size). Conclusion. Although the most efficient mesh size for roach was 26 mm, its use in the Szczecin Lagoon is limited by impact on perch. All the studied mesh sizes prevented catches of undersized roach, while mesh sizes from 28 mm prevented catches of undersized perch (MLL = 17 cm TL). The authors concluded that the current 30 mm minimum mesh size is likely effective at preventing the harvest of undersized perch and roach.

A new approach to nonlinear modelling of dynamic systems based on fuzzy rules

63%

Bartczuk Ł. , Przybył A. , Cpałka K.

2016

tom Vol. 26, no. 3

603--621

For many practical weakly nonlinear systems we have their approximated linear model. Its parameters are known or can be determined by one of typical identification procedures. The model obtained using these methods well describes the main features of the system’s dynamics. However, usually it has a low accuracy, which can be a result of the omission of many secondary phenomena in its description. In this paper we propose a new approach to the modelling of weakly nonlinear dynamic systems. In this approach we assume that the model of the weakly nonlinear system is composed of two parts: a linear term and a separate nonlinear correction term. The elements of the correction term are described by fuzzy rules which are designed in such a way as to minimize the inaccuracy resulting from the use of an approximate linear model. This gives us very rich possibilities for exploring and interpreting the operation of the modelled system. An important advantage of the proposed approach is a set of new interpretability criteria of the knowledge represented by fuzzy rules. Taking them into account in the process of automatic model selection allows us to reach a compromise between the accuracy of modelling and the readability of fuzzy rules.