Abstract
An AI system of optimal control and design of drip irrigation systems is proposed. This AI system is based on simulation of the water transport process described by Richards-Klute equation. Using the Kirchhoff transformation the original nonlinear problem is reduced to a linear problem of optimal control of non-stationary moisture transport in an unsaturated soil providing the desirable water content. For minimization of a cost functional a variational algorithm is used. Also, the finite-difference method is used to solve direct and conjugate problems. The optimization is achieved by minimizing the mean square deviation of the moisture content from the target distribution at a given moment in time. The chapter describes the optimization of drip irrigation system with buried sources in a dry soil. Results demonstrate high accuracy and effectiveness of the method. The purpose of the chapter is to describe an AI system for optimal control and design of drip irrigation system based on modern mathematical methods. The novelty of the proposed approach is that it is the first attempt to optimize drip irrigation system using the linearization via the Kirchhoff transformation. The contribution of the chapter is that it describes the effectiveness of the holistic AI approach to the design and control of drip irrigation systems for sustainable agriculture and environment. The scope of the future work it to introduce the impulse control in time and optimization the pipe functioning in the scale of an irrigation module at whole.
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Klyushin, D., Tymoshenko, A. (2021). Optimization of Drip Irrigation Systems Using Artificial Intelligence Methods for Sustainable Agriculture and Environment. In: Hassanien, A., Bhatnagar, R., Darwish, A. (eds) Artificial Intelligence for Sustainable Development: Theory, Practice and Future Applications. Studies in Computational Intelligence, vol 912. Springer, Cham. https://doi.org/10.1007/978-3-030-51920-9_1
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