Finally, fuzzy modeling and control methods are combined in the book, to create adaptive fuzzy controllers, ending with an example of an obstacle-avoidance controller for an autonomous vehicle using modus ponendo tollens logic.
"synopsis" may belong to another edition of this title.
A fuzzy control system is a control system based on fuzzy logic, which is a mathematical system that makes decisions using human reasoning processes. This book presents an introductory-level exposure to two of the principal uses for fuzzy logic—identification and control. Drawn from the author's lectures presented in a graduate-level course over the past decade, this volume serves as a holistically suitable single text for a fuzzy control course, compiling the information often found in several different books on the subject into one.
Starting with explanations of fuzzy logic, fuzzy control, and adaptive fuzzy control, the book introduces the concept of expert knowledge, which is the basis for much of fuzzy control. From there, the author covers:
Basic concepts of fuzzy sets such as membership functions, universe of discourse, linguistic variables, linguistic values, support, a-cut, and convexity
Both Mamdani and Takagi-Sugeno fuzzy systems, showing how an effective controller can be designed for many complex nonlinear systems without mathematical models or knowledge of control theory while also suggesting several approaches to modeling of complex engineering systems with unknown models
How PID controllers can be made fuzzy and why this is useful
Position-form and incremental-form fuzzy controllers
How nonlinear systems can be modeled as fuzzy systems in several forms
How fuzzy tracking control and model reference control can be realized for nonlinear systems using parallel distributed techniques
The estimation of nonlinear systems using the batch least squares, recursive least squares, and gradient methods
The creation of direct and indirect adaptive fuzzy controllers
Also included are many examples, exercises, and computer program listings, all class-tested. Fuzzy Control and Identification is intended for seniors and first-year graduate students, and is suitable for any engineering department. No knowledge specific to any particular branch of engineering is required, and no knowledge of electrical, chemical, or mechanical systems is necessary to read and understand the material.
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Book Description Condition: New. A fuzzy control system is a control system based on fuzzy logic, which is a mathematical system that analyzes analog input values in terms of logical variables that take on continuous values between 0 and 1. This text provides a broad introduction to fuzzy control and identification, covering both Mamdani and Takagi-Sugeno fuzzy systems. Num Pages: 232 pages, Illustrations. BIC Classification: TJFM. Category: (P) Professional & Vocational. Dimension: 245 x 164 x 17. Weight in Grams: 488. . 2010. 1st Edition. Hardcover. . . . . Seller Inventory # V9780470542774
Book Description Gebunden. Condition: New. John H. Lilly, PhD, is a professor in the Speed School of Engineering at the University of Louisville. His research interests are nonlinear and adaptive control, fuzzy identification and control, positive/negative fuzzy systems, pneumatic muscle actuators, . Seller Inventory # 446912874