Application of a multivariable adaptive control strategy to automotive air conditioning systems

Rajat Shah, Bryan P. Rasmussen, Andrew G. Alleyne

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)199-221
Number of pages23
JournalInternational Journal of Adaptive Control and Signal Processing
Issue number2
StatePublished - Mar 2004
Externally publishedYes


  • Air conditioning
  • Multivariable adaptive control
  • State space control

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Signal Processing
  • Electrical and Electronic Engineering


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