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Model‐Free Adaptive Control Method Applied to Vibration Reduction of a Flexible Crane as MIMO System
Author(s) -
Pham Hoang Anh,
Söffker Dirk
Publication year - 2019
Publication title -
pamm
Language(s) - English
Resource type - Journals
ISSN - 1617-7061
DOI - 10.1002/pamm.201900145
Subject(s) - control theory (sociology) , multivariable calculus , mimo , control engineering , controller (irrigation) , reduction (mathematics) , nonlinear system , adaptive control , computer science , vibration , tracking error , control system , engineering , control (management) , mathematics , artificial intelligence , channel (broadcasting) , physics , geometry , computer network , agronomy , electrical engineering , quantum mechanics , biology
Abstract Model‐free adaptive control (MFAC) approaches are able to be used when system models are not available and some task‐ or system‐specific conditions are fulfilled. This avoids to require exact mathematical models with respect to consideration of modeling errors even in the case of nonlinear systems to be controlled. The control strategy denoted as model‐free when for controller design only the available system data is used. In this contribution based on the knowledge of MFAC, an extension of the existing approach is presented and applied to unknown multivariable systems. The main control idea is that an estimation of real‐time system parameters which represent system dynamical variations is realized by using only inputs and outputs. A novel control algorithm is derived by minimizing both output tracking error and its derivative. The designed controller is applied to a flexible crane, representing a class of MIMO systems. The simulation results demonstrate that the vibrations of a crane system could be reduced significantly.