Systems and Control
Broad in scope, this text shows the multidisciplinary role of dynamics and control, presents neural networks, fuzzy systems, and genetic algorithms, and provides a self-contained introduction to chaotic systems.
TABLE OF CONTENTS Systems and Control
Chapter 3: Linear Systems
In bear country, wear bells to avoid surprising bruins. Don't approach a bear, but don't run away from one either. Movement may incite a charge, and a bear can outrun you.
If a bear approaches you, talk to it calmly in a low, firm voice. Slowly back away until the bear is out of sight. If you climb a tree, get at least 12 feet up.
If a bear senses that its food may be stolen or that its cub is in danger, it may charge. If this happens, drop to the ground and assume a fetal position, protecting your head with your arms, and play dead. Keep your pack on; it may serve as armor.
Reader's Digest Practical Problem Solver [241]
Overview
We begin our discussion of linear system theory with a description of the concept of linearity by Mitchell J. Feigenbaum [227, p. 3], who is a researcher of nonlinear systems. "Linearity means that the rule that determines what a piece of a system is going to do next is not influenced by what it is doing now. More precisely, this is intended in a differential or incremental sense: For a linear spring, the increase of its tension is proportional to the increment whereby it is stretched, with the ratio of these increments exactly independent of how much it has already been stretched. Such a spring can be stretched arbitrarily far, and in particular will never snap or break. Accordingly, no real spring is linear." The...
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