• Title of article

    Sensitivity Analysis of an Optimal Control Problem in Greenhouse Climate Management

  • Author/Authors

    E.J Van Henten، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2003
  • Pages
    10
  • From page
    355
  • To page
    364
  • Abstract
    Optimal control systems are based on a performance measure to be optimised and a model description of the dynamic process to be controlled. When on-line implementation is considered, the performance of optimally controlled processes will depend on the accuracy of the model description used. Sensitivity analysis offers insight into the impact of uncertainty in the model parameters on the performance of the optimally controlled process. Additionally, sensitivity analysis may reveal the mechanisms underlying optimal process operation. This paper describes the methodology and results of a sensitivity analysis of an optimal control problem in greenhouse climate management. The methodology used, is based on variational arguments and requires a single solution of the optimal control problem, resulting in a computationally efficient technique. The example considered deals with economic optimal greenhouse climate management during the cultivation of a lettuce crop. The sensitivity analysis produced valuable insight into the performance sensitivity and operation of the controlled process. Both the model description of crop growth and production as well as the outside climate conditions have a strong impact on the performance. Humidity control plays a dominant role in economic optimal greenhouse climate management, emphasising the need for an accurate description of humidity effects on crop growth and production, either in terms of quantitative models or time-varying constraints on the humidity level in the greenhouse. Finally, the study revealed that the dynamic response times in the greenhouse climate are not limiting factors for economic optimal greenhouse climate control.
  • Journal title
    Biosystems Engineering
  • Serial Year
    2003
  • Journal title
    Biosystems Engineering
  • Record number

    1266077