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Application of a multivariable adaptive control strategy to automotive air conditioning systems
Author(s) -
Shah Rajat,
P. Rasmussen Bryan,
Alleyne Andrew G.
Publication year - 2004
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.787
Subject(s) - multivariable calculus , control theory (sociology) , mimo , air conditioning , automotive industry , control engineering , adaptive control , linear quadratic regulator , engineering , system identification , state space representation , controller (irrigation) , control system , computer science , control (management) , data modeling , electronic engineering , mechanical engineering , beamforming , agronomy , software engineering , electrical engineering , algorithm , artificial intelligence , biology , aerospace engineering
This paper presents the application of a multivariable adaptive control strategy to a typical automotive air conditioning system. An experimentally validated physical model for the air conditioning (a/c) cycle is first presented and is subsequently used to choose a relevant model structure for indirect adaptive control. Recursive identification of this model structure is carried out using a multi‐input multi‐output (MIMO) parameter estimation algorithm to obtain an equivalent discrete‐time state space model of the a/c system. Linear quadratic regulator (LQR) design is implemented on the estimated model with the objectives of reference tracking and disturbance rejection. Simulation studies are presented to evaluate the advantages of using the electronic expansion valve and the air flow rate over the evaporator to control the efficiency and the capacity of a general automotive a/c unit using this adaptive control approach. The results demonstrate the efficacy of the MIMO controller and motivate further research in this area. Copyright © 2004 John Wiley & Sons, Ltd.