Computer Integrated Management and Intelligent Control of Greenhouses.

  • SIGRIMIS N.
    <I>Department of Agricultural Engineering, Agricultural University of Athens</I>
  • ARVANITIS K. G.
    <I>Department of Agricultural Engineering, Agricultural University of Athens</I>
  • PASGIANOS G. D.
    <I>Department of Agricultural Engineering, Agricultural University of Athens</I>
  • FERENTINOS K. P.
    <I>Department of Agricultural Engineering, Agricultural University of Athens</I>

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Greenhouses are complex systems with many variants and many different user requirements. Modern technologies are cost effective and very powerful to meeting diverse user control and management requirements. Optimization tools are making analytical and expert methods practically applicable. The system described features generalized functions for process control, configurable to meet greenhouse control requirements. Intelligence is shared among low level control loops in the controller and high level decisions made at the central process computer. An open Knowledge Based System, in the form of tasks and subtasks, provides an elegant way of rapid program development. Fuzzy decisions and fuzzy controllers at the supervisory level can provide adaptive reference (set-point) generators, which are key elements for near-optimal greenhouse control. The system is also equipped with an on-line process optimization tool, which was built based on a modified search algorithm with accelerated learning. Each process when entered under the optimizing monitor, is performance driven, conducts real experiments on the site and uses a modified descent method to maximize performance. An adaptive system guides the selection of control parameter values on-line, in a process searching for the global minimum of the cost function. This paper presents the general features of the system, how it can be set-up to achieve specific goals and presents results of tests conducted for low, medium and high level control and supervision.

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