Agricultural cybernetics

Authors: Huang, Yanbo; ZHANG, QIN - Washington State University

Submitted to: Springer Nature Applied Sciences
Publication Type: Book / Chapter
Publication Acceptance Date: 7/26/2021
Publication Date: 8/31/2021
Citation: Huang, Y., Zhang, Q. 2021. Agricultural cybernetics. Springer Nature Applied Sciences. https://doi.org/10.1007/978-3-030-72102-2.
DOI: https://doi.org/10.1007/978-3-030-72102-2

Interpretive Summary: Cybernetics is a theory Dr. Norbert Wiener created in 1948 about the control and communication issues in the animal and the machine systems. Since then this theory has been studied and used in creating new disciplines of science and engineering. With development and applications of control and communication methods in agricultural fields a scientist from USDA ARS Crop Production Systems Research Unit at Stoneville, Mississippi, and a professor from Washington State University have written this book to, the first time, systematically introduce the concepts and methods of Cybernetics that can be used to solve problems in agriculture. This book includes 8 chapters. It is for scientists, engineers and students working or being interested in applications of information technology in agriculture with the background of advanced mathematics, statistics and system modeling, optimization and control.

Technical Abstract: Cybernetics provides a theoretical base for managing the performance of a complicated system using control theory, and Agricultural Cybernetics (AC) provides a systematic tool for creating and optimizing management strategies to effectively control agricultural production systems through utilizing the intrinsic feedback information-exchanging mechanisms. This book presents a first formation of the AC theory for the readers to acquire preliminary knowledge of this theory with being aware of the immature nature of this theory. This book includes 8 chapters: • Chapter 1 introduced the concepts of Cybernetics, and provided an overview of the evolution of Cybernetics, from Wiener’s Cybernetics to Tsien’s Engineering Cybernetics to various cybernetic variants and Cybernetics in special fields, then AC of this book with the background of modern agricultural technologies from precision agriculture (PA) to smart agriculture. In the chapter, the technologies from PA to smart agriculture were discussed and focused on evaluation to provide a perspective on the advancement of the technologies. On this foundation, AC was introduced for interpreting the mechanism and providing methodology for problem solving in control and communication in agricultural production systems. • Chapter 2 introduced some key mathematical and statistical concepts, assumptions, methods and applications which are critical to cybernetic system development. The readers are assumed to have basic knowledge of linear algebra, calculus and statistics. This chapter also introduced the representations of cybernetic systems, especially transfer function representation for system modeling, communication and control. This chapter did not intend to cover all needed. Some other advanced ones were be covered to follow the discussions of system modeling and control in later chapters. • Chapter 3 considered agricultural production as a complex large system and decomposed crop production into a series of production and management systems with optimal performance of each system to maximize the profit for the entire crop production. With studies of system responses and dynamics with uncertainties a windowed, multi-stage, adaptive control scheme of crop production was proposed. • Chapter 4 introduced various modeling paradigms for system modeling and discussed their implications to PA. On the basis, crop growth control scheme along with crop phenology was proposed and controllable and observable variables were identified for the systems. • Chapter 5 introduced control theory and approaches for agricultural production systems from classic control to modern control, from optimal control to process control, from model-based control to model-free control, and control from data-driven machine learning, neuro-fuzzy and adaptive control. • Chapter 6 discussed control issues of PA operation and introduced control schemes accordingly. Control of PA and control of industrial systems was compared to understand this AC control application. On this basis a general structure of agricultural cybernetic system for crop production control was specified. A repertoire was suggested with a number of approaches as components for the fundamental difference of AC from traditional control theory. • Chapter 7 described bigdata analytics and a complete big data analytical platform for PA and further introduced approaches to knowledge learning from data. Data driven machine learning and deep learning were focused on and some further topics were discussed for potential development in the next decade. • Chapter 8, as the last chapter of the book, provided an overall summary of the book to discuss what Cybernetics will bring to agriculture. From the point of view AC various agricultural systems are characterized. AC is featured with a number of contemporary system ideas. In conclusion smart agriculture is projecte