D. Koshkin<\/p>\n
Introduction<\/strong>. Multiple interrelated parameters are controlled and managed in modern greenhouse process automation systems for getting a high crop at low energy consumption. This problem is usually solved by using an integrated control system that takes into account the impact of greenhouse microclimate on product output. The study of greenhouse control systems is usually divided into hierarchical levels by the time scale or by the performance criterion of subsystems. Key words: greenhouse, mathematical model, yield management<\/p>\n
\n<\/strong>The purpose of the study <\/strong>is to develop a structure of computerized crop control system of a greenhouse; to investigate the feasibility and advisability of the time scale decomposition of crop control systems and greenhouse mathematical models.
\nMain result.<\/strong> Significantly simplified mathematical model explains the contradiction of greenhouse crop control system. Thus, the growth of biomass increases with increasing temperature and light intensity, on the other hand, the heating and the lighting requires energy consumption.
\nTraditional greenhouse crop control systems are based on the knowledge and the experience of the grower. The grower is guided by the type of plants, their state and the stage of growth. He determines the greenhouse microclimate parameters that are set as objectives for climate control system.
\nThe proposed computerized crop control system uses an intelligent control subsystem with a hierarchical structure. There are two levels in the crop control system: field level and intelligent control level. The mathematical model of a greenhouse microclimate with temperature and humidity control is used in intelligent crop control subsystem. The model is based on mass and energy conservation laws.
\nTime scale decomposition of crop control system generates two loops or hierarchical levels. The outer loop is a “slow” crop control subsystem, and the internal loop is a “fast” microclimate control subsystem. The outer loop solves the problem of optimal control in the days and weeks scale. It uses parameters of harvest state, weather forecast, prospective of the crop cost change. This calculation is made on a regular basis (depending on the plant type), such as once a week, or by the availability of the necessary information. Set points or trajectories, calculated in an outer loop of the system, are used in an internal loop with short-term weather forecast. They allow solving the “fast” subtask of controlling the greenhouse microclimate dynamics. This “fast” subtasks must be optimized only for the time interval\\, during which an actuators change the greenhouse microclimate. This interval has an hour scale or even less than one in practice.
\nConclusions<\/strong>: 1. The decomposition of a greenhouse crop control system into two subsystems, depending on the response time of the system, is proposed in order to solve the problem of the growing process optimization. The first “slow” subsystem deals with the crop growing, and the second “fast” \u2013 with the greenhouse microclimate. 2. The relationship of the upper and lower levels of the control system is proposed to produce the form of trajectories of the subsystem. Tracking of them provides an optimal greenhouse control process.<\/p>\n