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Product Description
Book Description
Describes the use of optimal control and estimation in the design of robots, controlled mechanisms, and navigation and guidance systems. Covers control theory specifically for students with minimal background in probability theory. Presents optimal estimation theory as a tutorial with a direct, well-organized approach and a parallel treatment of discrete and continuous time systems. Gives practical examples and computer simulations. Provides enough mathematical rigor to put results on a firm foundation without an overwhelming amount of proofs and theorems.
Synopsis
This book is intended for use in graduate level courses in modern control theory. A background in both probability theory and the state variable representation of systems is assumed. One advantage of modern control theory is that it employs matrix algebra, which results in a simplification in notation and mathematical manipulations when dealing with multivariable systems. The book is also intended as a reference. Equations of recurring usefulness are displayed in tabular form for easy access. Many examples are used to illustrate the concepts and to impart intuition, and the reader is shown how to write simple software implementations of estimators for use on a computer.
