Control Theory for Humans: Quantitative Approaches to Modeling Performance

Control Theory for Humans: Quantitative Approaches to Modeling Performance

Control Theory for Humans: Quantitative Approaches to Modeling Performance

Control Theory for Humans: Quantitative Approaches to Modeling Performance

Synopsis

This textbook provides a tutorial introduction to behavioral applications of control theory. Control theory describes the information one should be sensitive to and the pattern of influence that one should exert on a dynamic system in order to achieve some goal. As such, it is applicable to various forms of dynamic behavior. The book primarily deals with manual control (e. g., moving the cursor on a computer screen, lifting an object, hitting a ball, driving a car), both as a substantive area of study and as a useful perspective for approaching control theory. It is the experience of the authors that by imagining themselves as part of a manual control system, students are better able to learn numerous concepts in this field.

Topics include varieties of control theory, such as classical, optimal, fuzzy, adaptive, and learning control, as well as perception and decision making in dynamic contexts. The authors also discuss some of the implications of control theory for how experiments can be conducted in the,behavioral sciences. In each of these areas they have provided brief essays that are intended to convey a few key concepts that will enable the reader to more easily pursue additional readings. Behavioral scientists teaching control courses will be very interested in this book.

Excerpt

This book provides a tutorial introduction to behavioral applications of control theory. It primarily deals with manual control, both as a substantive area of study and as a useful perspective for approaching control theory. It is the experience of the authors that by imagining themselves as part of a manual control system, students are better able to learn numerous concepts in this field. The intended reader is expected to have a good background in algebra and geometry and some slight familiarity with the concepts of an integral and derivative. Some familiarity with statistical regression and correlation would be helpful, but is not necessary. The text should be suitable for advanced undergraduates as well as graduate students in the behavioral sciences, engineering, and design. Topics include varieties of control theory such as classical control, optimal control, fuzzy control, adaptive control, learning control, and perception and decision making in dynamic contexts. We have additionally discussed some of the implications of control theory for how experiments can be conducted in the behavioral sciences. In each of these areas we have provided brief essays that are intended to convey a few key concepts that will enable the reader to more easily pursue additional readings should they find the topic of interest.

Although the overall text was a collaborative effort that would not have been completed otherwise, each of the authors took primary responsibility for different chapters. JF was primarily responsible for chapters 1-10, 13, 14, 17, and 22; RJ was primarily responsible for chapters 11, 12, 15, 16, 18–21, and 23–26; chapter 27 was a joint denouement.

ACKNOWLEDGMENTS

The authors are grateful to Richard W. Pew, Louis Tijerina, Hiroyuki Umemuro, and William Levison for providing comments on substantial portions of the manuscript.

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