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Model reference adaptive minimum‐energy control for a mechatronic elevator system
Author(s) -
Chen KunYung
Publication year - 2016
Publication title -
optimal control applications and methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.458
H-Index - 44
eISSN - 1099-1514
pISSN - 0143-2087
DOI - 10.1002/oca.2239
Subject(s) - control theory (sociology) , reference model , particle swarm optimization , mechatronics , adaptive control , computer science , elevator , lyapunov function , control engineering , engineering , control (management) , algorithm , artificial intelligence , nonlinear system , physics , software engineering , structural engineering , quantum mechanics
Summary The mechatronic elevator system driven by a permanent magnet synchronous motor is modeled using mechanical and electrical equations. In addition, the dimensionless forms are derived for practicable movements. This paper proposes and demonstrates the reference model of a minimum‐input absolute electrical energy control scheme based on the Hamiltonian function. Furthermore, a model reference adaptive control scheme based on the Lyapunov function is proposed for tracking the reference model to achieve a robust control performance, thus combining the minimum‐energy reference model of the minimum‐input absolute electrical energy control and the robust control offered by the model reference adaptive control. The proposed model reference adaptive minimum‐energy control yields robust minimum‐energy control performance. Subsequently, the experimental parameters of the elevator system were identified through self‐learning particle swarm optimization. The experimental results demonstrate the robust minimum‐energy control performance of the proposed model reference adaptive minimum‐energy control. Copyright © 2016 John Wiley & Sons, Ltd.