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Controller Parameters Tuning Based on Transfer Matrix Method for Multibody Systems
Author(s) -
Hendy Hossam,
Rui Xiaoting,
Zhou Qinbo,
Khalil Mostafa
Publication year - 2014
Publication title -
advances in mechanical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.318
H-Index - 40
ISSN - 1687-8132
DOI - 10.1155/2014/957684
Subject(s) - control theory (sociology) , multibody system , control engineering , controller (irrigation) , stability (learning theory) , transfer function , computer science , transfer matrix , pid controller , control system , state vector , matrix (chemical analysis) , suspension (topology) , engineering , control (management) , mathematics , artificial intelligence , materials science , temperature control , composite material , biology , quantum mechanics , machine learning , homotopy , agronomy , computer vision , physics , pure mathematics , electrical engineering , classical mechanics
Transfer matrix method for multibody systems (MS-TMM) is a rife method to multi-rigid-flexible-body systems dynamics model deduction due to that there are no needs to establish the global dynamics equations of the system. Its basic idea is transferring a state vector between the body input(s) and output(s); this idea is close to the linear theories in control analysis and design. In this paper, three controllers’ parameters tuning techniques for the proposed system model using MS-TMM are utilized; one technique is applied to get the stability regions via the frequency response of MS-TMM derived model. Another technique considers a classical PID controller design through the analysis of step input response of the system, and the last technique can be applied in both time and frequency domains if the model has a known mathematical model. A car suspension system is considered to represent modeling and tuning problems. In-depth study of MS-TMM with control techniques and defining the controllers’ parameters stability regions provide an opportunity to formulate a relationship between MS-TMM and control design for novel control applications due to the powerful strength of MS-TMM dealing with more complex problems of the controlled multibody systems.

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