Algorithm of heavy-loaded platform positioning with application of fuzzy logic

• Autorzy: Lisowski E. , Filo G.
• Języki publikacji: EN

Abstrakty

EN

This paper presents a fuzzy logic algorithm applied to control position of heavy-loaded platform. The work was realized for PAnDa project and refers to development of anti-proton detector in Darmstadt, Germany. Electromagnet of the detector has total mass of about 360 tons. It is placed on a mobile platform. Besides the horizontal movement, the platform must have ability of vertical positioning with high accuracy using hydraulic system with cylinders and proportional control valves. In this work a fuzzy logic controller (FLC) was used in order to operate the control valves. Model of investigated system as well as model of a FLC unit have been built in Matlab environment. Initial simulations were made in order to obtain optimal control algorithm and adjust the FLC parameters. Further investigations confirmed system operation with assumption of non-uniform load of individual cylinders, when number of cylinders is 4 and 6. Results indicate, that using of FLC unit allows to obtain required positioning accuracy even for non-uniform load.

Słowa kluczowe

EN

fuzzy logic; hydraulic system; positioning; control

• Wydawca: Wydawnictwo Politechniki Poznańskiej
• Czasopismo: Foundations of Computing and Decision Sciences
• Rocznik: 2011
• Tom: Vol. 36, No. 3-4
• Strony: 259--274
• Opis fizyczny: Bibliogr. 8 poz.

Twórcy

autor

Lisowski E.

autor

Filo G.

• Cracow University of Technology, Faculty of Mechanical Engineering, Institute of Applied Informatics,

Bibliografia

• [1] Driankov D., Hellendoorn H., Reinfrank M.: Wprowadzenie do sterowania rozmytego, WNT Warszawa 1996.
• [2] Filo G.: Modelling of fuzzy logic control system using the Matlab Simulink program, Czasopismo Techniczne, z. 2-M/2010, Kraków 2010.
• [3] Lisowski E., Filo G.: Pozycjonowanie ładunku podnośnikami hydraulicznymi z regulatorami w logice rozmytej, Hydraulika i Pneumatyka, nr 1/2010.
• [4] Marciniak A.: Fuzzy Approach to Combining Parallel Experts Response, Fuzzy control: theory and practice, Heidelberg: Physica-Verlag, 2000.
• [5] Nermend M., Nermend K.: Zastosowanie teorii zbiorów przybliżonych do modelowania zachowań konsumentów, Problemy Społeczeństwa Informacyjnego, tom II, monografia, praca pod redakcją naukową prof. US dr hab. Agnieszki Szewczyk, Szczecin, 2007.
• [6] Piegat A.: Fuzzy Modeling and Control, Springer-Heidelberg, New York, 2001.
• [7] Piegat A.: Modelowanie i sterowanie rozmyte, EXIT, Warszawa 2009.
• [8] Yager R.R., Nguyen H., Sugeno M., Tong R.: Theoretical Aspects of Fuzzy Control, John Wiley & Sons: New York, 1995.