Control Theory for Humans: Quantitative Approaches to Modeling and Performance

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Control Theory for Humans: Quantitative Approaches to Modeling Performance provides a tutorial introduction to behavioral applications of control theory. Control theory explores the information to which a person should be sensitive and the pattern of influence a person should exert on a dynamic system in order to achieve some goal. Topics include varieties of control theory such as classical control, optimal control, fuzzy control, adaptive control, and learning control. Also discussed are perception and decision making in dynamic contexts, and implications of control theory for how experiments can be conducted in the behavioral sciences.

This textbook should be suitable for advanced undergraduate and graduate students in the behavioral sciences, engineering, and design.

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Product Details

  • ISBN-13: 9780805822922
  • Publisher: Taylor & Francis
  • Publication date: 10/28/2002
  • Pages: 400
  • Product dimensions: 7.10 (w) x 9.90 (h) x 1.00 (d)

Table of Contents

About the Authors
1 Perception/Action: A Systems Approach 1
2 Closing the Loop 8
3 Information Theory and Fitts' Law 17
4 The Step Response: First-Order Lag 27
5 Linear Systems: Block Diagrams and Laplace Transforms 33
6 The Step Response: Second-Order System 46
7 Nonproportional Control 58
8 Interactions Between Information and Dynamic Constraints 74
9 Order of Control 87
10 Tracking 104
11 There Must Be 50 Ways to See a Sine Wave 112
12 A Qualitative Look at Fourier Analysis 120
13 The Frequency Domain: Bode Analysis 137
14 The Frequency Domain: Describing the Human Operator 158
15 Additional Adaptive Aspects of the Crossover Model 168
16 Driving Around in Circles 187
17 Continuous Tracking: Optimal Control 195
18 Estimating and Predicting the State of a Dynamic System With Lag-Like Calculations 212
19 Varieties of Variability 222
20 Lifting a Glass of Juice 239
21 Sine Wave Tracking Is Predictably Attractive 252
22 Going With the Flow: An Optical Basis for the Control of Locomotion 269
23 Fuzzy Approaches to Vehicular Control 291
24 Learning to Control Difficult Systems: Neural Nets 303
25 Some Parallels Between Decision Making and Manual Control 314
26 Designing Experiments With Control Theory in Mind 331
27 Adaptation and Design 342
App.: Interactive Demonstrations 360
Author Index 367
Subject Index 375
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