外文翻譯--農(nóng)業(yè)大棚溫室智能化自動(dòng)控制-展示頁(yè)
2024-11-14 08:06本頁(yè)面
【正文】 shown and described Keywords Agriculture Hierarchical systems Process control Optimization methods Yield optimization 1 Introduction Modern agriculture is nowadays subject to regulations in terms of quality and environmental impact and thus it is a field where the application of automatic control techniques has increased a lot during the last few years The greenhouse production agrosystem is a plex of physical chemical and biological processes taking place simultaneously reacting with different response times and patterns to environmental factors and characterized by many interactions Challa van Straten 1993 which must be controlled in order to obtain the best results for the grower Crop growth is the most important process and is mainly influenced by surrounding environmental climatic variables Photosynthetically Active Radiation PAR temperature humidity and CO2 concentration of the inside air the amount of water and fertilizers supplied by irrigation pests and diseases and culture labors such as pruning and pesticide treatments among others A greenhouse is ideal for crop growing since it constitutes a closed environment in which climatic and Fertilizer irrigation variables can be controlled Climate and Fertilizer irrigation are two independent systems with different control problems and objectives Empirically the water and nutrient requirements of the different crop species are known and in fact the first automated systems were those that control these variables On the other hand the market price fluctuations and the environment rules to improve the wateruse efficiency or reduce the fertilizer residues in the soil such as the nitrate contents are other aspects to be taken into account Therefore the optimal production process in a greenhouse agrosystem may be summarized as the problem to reaching the following objectives an optimal crop growth a bigger production with a better quality reduction of the associate costs mainly fuel electricity and fertilizers reduction of residues mainly pesticides and ions in soil and the improvement of the water use efficiency Many approaches have already been applied to this problem for instance dealing with the management of greenhouse climate in the optimal control field eg Challa and van 2 MO optimization in crop production An MO optimization problem can be defined as finding a vector of decision variables which satisfies constraints and optimizes a vector whose elements represent objective functions The problems characterized by peting measures of performance or objectives are considered as MO optimization problems where n objectives Ji p in the vector of variables p∈ P are simultaneously minimized or imized The problem often has no optimal solution that simultaneously optimize all objectives but it has a set of suboptimal or nondominated alternative solutions known as a Pareto optimal set where a promise solution may be selected from that set by a decision process Different criteria such as physical yield crop quality product quality timing of the production process or production costs and risks can be formulated within greenhouse crop management These criteria will often give rise to controversial climate and 肥料灌溉 requirements which have to be solved explicitly or implicitly at the socalled tactical level where the grower has to make decisions about several conflicting objectives The solution of this MO optimization process p∈ P is the optimal diurnal and nocturnal present and future reference trajectories of temperature Xta and electrical conductivity XEC for the rest of the crop cycle That is where is a vector of the inside air temperature along the optimization intervals and is a vector of the electrical conductivity EC along the optimization intervals Notice that the plants grow under the influence of the PAR radiation diurnal conditions performing the photosynthesis process Furthermore the temperature influences the speed of sugar production by photosynthesis and thus radiation and temperature have to be in balance in the way that a higher radiation level corresponds to a higher temperature So under diurnal conditions it is necessary to maintain the temperature at a high level In nocturnal conditions the plants are not active the crop does not grow so it is not necessary to maintain such a high temperature For this reason two temperature setpoints are usually considered diurnal and nocturnal It is necessary to highlight that although the process optimization is presented in continuous time it is solved in discrete time intervals for an optimization horizon Nf k this horizon is variable and represents the remaining intervals until the end of the agricultural season Thus the solution vectors and are obtained as where k is the current discrete time instant Notice that for the proposed optimizatio
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