Temat: fuzzy steering - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Modelowanie i sterowanie rozmyte aparatem udojowym
Modeling and fuzzy steering of the milking apparatus
Autorzy:: Juszka, H.
Lis, S.
Tomasik, M.
Powiązania:: https://bibliotekanauki.pl/articles/239640.pdf
Data publikacji:: 2005
Wydawca:: Instytut Technologiczno-Przyrodniczy
Tematy:: dój maszynowy
krowa
sterowanie rozmyte
automatyczne sterowanie
modelowanie
machine milking
cow
fuzzy steering
modeling
automatic steering
simulation
Opis:: Przedstawiono modelowanie aparatu udojowego z zastosowanym sterowania opartego na logice rozmytej. Model aparatu udojowego oraz rozmyty model sterowania opracowano w programie MatlabŽ. Jego konstrukcja zawiera bloki funkcjonalne obliczające sygnał pulsatora, objętość komór pod strzykami, podciśnienie w tych komorach oraz natężenie strumienia powietrza przetłaczanego pomiędzy komorami podstrzykowymi a komorą mleczną kolektora pod wpływem różnicy podciśnień. Model umożliwia badanie przebiegów zmian podciśnienia w komorach podstrzykowych kubków udojowych i komorze mlecznej kolektora.
Paper presented modeling of the milking machine with application of steering based on fuzzy logic. The model of milking machine as well as the fuzzy model of steering were formulated under MATLAB 6,5Ž Simulink programme. Their construction included functional blocs computing the pulsator signal, the capacity of teat-cup chambers, vacuum pressure in these chambers as well as the intensity of air flow between teat-cup chambers and milking chamber of collector, forced by the difference in vacuum pressures. The model makes possible to investigate the courses of vacuum pressure changes in teat-cup chambers and milking chamber of the collector.
Źródło:: Problemy Inżynierii Rolniczej; 2005, R. 13, nr 4, 4; 57-64
1231-0093
Pojawia się w:: Problemy Inżynierii Rolniczej
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Aircraft docking guidance system to the gate using fuzzy logic
Autorzy:: Żurawski, P.
Grzesik, N.
Kuźma, K.
Powiązania:: https://bibliotekanauki.pl/articles/243957.pdf
Data publikacji:: 2018
Wydawca:: Instytut Techniczny Wojsk Lotniczych
Tematy:: fuzzy logic
fuzzy expert system
aircraft taxiing
aircraft steering
Opis:: The article presents the concept of automated final process of aircraft taxiing to the gate at the terminal. On the basis of an analysis of the possibilities of aircraft taxiing in civil airports, the authors attempted at optimizing this process. The main objective of the project is to reduce the taxiing time, consequently reducing fuel consumption as well as the rotation time. As a result of the work, the authors designed a controller based on fuzzy logic, which, depending on the initial parameters, calculates the set values for the execution system of aircraft control in the horizontal plane and for the taxi speed. The controller receives two input signals, which determine two output signals. The designed controller allows comprehensive and fully automated aircraft steering. The project relies on data with regard to the apron class D, suited to handle aircraft with a wingspan of up to 52 m and the characteristics of a Boeing 767-200 in speed taxiing and the maximum turn of the nose gear. The measurements of the apron have been adopted in accordance with international regulations in the ICAO DOC 9157 “Aerodrome Design Manual”. The maximum deviation of the nose gear from the centre line was assumed 2.5 m in each direction and a safe distance behind the immobile aircraft equal to 25 m. The length of the Boeing aircraft 767-200 is below 48 m, therefore the input boundary parameters are equal to +/- 2.5 m from the centre line and 80 m from the designated aircraft stand (nose gear). The article presents the project of the controller and its optimization. The authors simulated the controller operation in the package MATLAB “Simulink”. The article ends with data analysis and final conclusions.
Źródło:: Journal of KONES; 2018, 25, 3; 549-556
1231-4005
2354-0133
Pojawia się w:: Journal of KONES
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Comparison of two controllers for directional control of a hybrid electric vehicle
Autorzy:: Dash, B. K.
Subudhi, B.
Powiązania:: https://bibliotekanauki.pl/articles/229825.pdf
Data publikacji:: 2012
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: directional control
active steering
fuzzy logic control
PID control
hybrid vehicle
Opis:: Directional response of a vehicle implies changing its direction when sustaining lateral acceleration while moving on the road. From this response, the vehicle's explicit capabilities as well as its contribution to the system performance of the driver/vehicle combination are obtained. In vehicle control literature, handling is often used interchangeably with cornering, turning, or directional response. This paper focuses one aspect of the handling i.e. directional response. Two different controllers, namely a PID controller and a Fuzzy Logic Controller (FLC) for a hybrid electric vehicle (HEV) are designed in this paper to control the vehicle's steering in a smooth lane change maneuver. The performances of the aforesaid two controllers have been studied extensively in this paper. For achieving an improved path tracking and directional response, parameters of both the PID and FLC have been tuned and their performances have been compared. Further, the effect of changing the scale factors in the fuzzy logic approach to obtaining directional response is presented. To validate the above two control performances, a nonlinear simulation model of a HEV is developed and is used in simulation studies. Both the controllers track the desired directional signal efficiently. Both PID and Fuzzy controllers provide competitive performances. Although with the assumption of all parameters of the vehicle available PID controller exhibits slightly better dynamic performance but in the real-world scenario the fuzzy controller is preferred due to its robustness i.e. it does not depend on the parameters of the vehicle.
Źródło:: Archives of Control Sciences; 2012, 22, 2; 191-215
1230-2384
Pojawia się w:: Archives of Control Sciences
Dostawca treści:: Biblioteka Nauki

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