LMI control design for nonlinear vapor compression cycle systems

Bin Li, Neera Jain, Andrew G. Alleyne

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

To effectively control vapor compression cycle (VCC) systems whose dynamics are highly nonlinear, it is necessary to develop plant models and control laws for different operating regions. This paper presents a first-principles modeling framework that captures four operation modes over the operating envelope to construct an invariant-order switched system. To synthesize a multi-input multi-output (MIMO) control system, the Linear Quadratic Regulator (LQR) technique is framed as a control optimization problem with Linear Matrix Inequality (LMI) constraints which can be simultaneously solved for the set of considered linear systems. Stability and performance characteristics of the controlled system are guaranteed using a common quadratic Lyapunov function. Simulation results in a case study show that the LMI-based controller can maintain system operation at optimal set-points with mode switching over a wide operating envelope.

Original languageEnglish (US)
Title of host publicationASME 2012 5th Annual Dynamic Systems and Control Conference Joint with the JSME 2012 11th Motion and Vibration Conference, DSCC 2012-MOVIC 2012
Pages711-718
Number of pages8
DOIs
StatePublished - Dec 1 2012
EventASME 2012 5th Annual Dynamic Systems and Control Conference Joint with the JSME 2012 11th Motion and Vibration Conference, DSCC 2012-MOVIC 2012 - Fort Lauderdale, FL, United States
Duration: Oct 17 2012Oct 19 2012

Publication series

NameASME 2012 5th Annual Dynamic Systems and Control Conference Joint with the JSME 2012 11th Motion and Vibration Conference, DSCC 2012-MOVIC 2012
Volume2

Other

OtherASME 2012 5th Annual Dynamic Systems and Control Conference Joint with the JSME 2012 11th Motion and Vibration Conference, DSCC 2012-MOVIC 2012
CountryUnited States
CityFort Lauderdale, FL
Period10/17/1210/19/12

ASJC Scopus subject areas

  • Control and Systems Engineering

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