Intelligent Algorithms for the Automation of Complex Biotechnical Objects

Abstract

Traditional automation systems implement the simplest stabilization algorithms that do not provide high energy and resource efficiency. Since information about the state of the biological component of the control object and the forecast of natural disturbances are not taken into account, the solutions to the problem of energy-efficient control of biotechnological objects is presented in this chapter. The modern intelligent algorithms for processing control object information and applying the results are considered. Appropriate control strategies allow maximizing the production profit of the poultry houses and greenhouses. The intelligent control system that takes into account the forecast of temperature changes is described and its use is shown (for example, poultry farms). The problem of an adequate analysis of the beginning one temperature image change to another is solved; use an intelligent pattern recognition system based on probabilistic neural networks is proposed. The functional diagram of the intelligent temperature control system in the poultry farms is given. The option of developing an intelligent control system for an industrial greenhouse is shown. It allows taking into account the forecast results of the external disturbances (temperature and solar radiation intensity). Such a control system is used to formulate control strategies for greenhouse complexes, which significantly reduce energy costs in the vegetable production.