Model predictive control and its application in agriculture: A review

Agriculture plays a decisive role in the survival of humankind. The efficient and precise regulation of agriculture will ensure the welfare of people throughout the world. However, difficult and urgent agricultural challenges persist, and traditional agricultural production regulation methods are time consuming and laborious. Moreover, the application of intelligent algorithms to modern agricultural production requires the support of a database, which can be complex and difficult to use in practice and requires a large amount of computing. Fortunately, model predictive control (MPC) methods can achieve highly accurate control operations with moderate complexity and can also allow for rolling optimization in a limited time domain, which improves precision. Despite being a process control method that originated in industry, MPC is highly suited for application in agriculture because it can effectively address nonlinear and large time-delay systems. The aim of this review is to introduce MPC and describe its current application in agriculture. In this review, the development of MPC and various improved MPC schemes are described. The development of MPC is divided into three stages. In addition, applications and new technologies associated with MPC in irrigation systems, agricultural machinery, agricultural production, product processing and greenhouses are analyzed. Smart agriculture will have a promising future because of the implementation of MPC technologies derived from successful industrial applications. Finally, challenges and future perspectives of MPC technology use in agriculture are summarized and forecasted.