A hybrid current controller for linear reciprocating vapor compressors

Zhengyu Lin, Jiabin Wang, David Howe

Research output: Chapter in Book/Published conference outputConference publication


Direct-drive linear reciprocating compressors offer numerous advantages over conventional counterparts which are usually driven by a rotary induction motor via crank shaft However, to ensure efficient and reliable operation under all conditions, it is essential that the motor current of the linear compressor follows a sinusoidal command profile with a frequency which matches the system resonant frequency. This paper describes a hybrid current controller for the linear compressors. It comprises a conventional proportional-integral (PI) controller, and a B-spline neural network compensator which is trained on-line and in real-time in order to minimize the current tracking error under all conditions with uncertain disturbances. It has been shown that the hybrid current controller has a superior steady-state and transient performance over the conventional carrier based PI controller. The performance of the proposed hybrid controller has been demonstrated by extensive simulations and experiments. It has also been shown that the linear compressor operates stably under the current feedback control and the piston stroke can be adjusted by varying the amplitude of the current command.
Original languageEnglish
Title of host publicationConference record of the 2007 IEEE industry applications conference forty-second IAS annual meeting
Number of pages7
ISBN (Electronic)978-1-4244-1260-0
ISBN (Print)978-1-4244-1259-4
Publication statusPublished - 23 Sep 2007
Event42nd Industry Applications Society annual meeting - New Orleans, LA , United States
Duration: 23 Sep 200727 Sep 2007

Publication series

NameIAS Annual Meeting. Conference Record - Industry Applications Society
ISSN (Print)0197-2618


Meeting42nd Industry Applications Society annual meeting
Country/TerritoryUnited States
CityNew Orleans, LA


  • linear compressor
  • current control
  • hybrid controller
  • B-spline neural network


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