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Robust Autonomous Guidance: An Internal Model Approach (Advances in Industrial Control)

Robust Autonomous Guidance: An Internal Model Approach (Advances in Industrial Control)

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Authors: Alberto Isidori, Lorenzo Marconi, Andrea Serrani
Publisher: Springer
Category: Book

List Price: $119.00
Buy New: $88.72
You Save: $30.28 (25%)



New (17) from $88.72

Sales Rank: 1183975

Media: Hardcover
Edition: 1
Number Of Items: 1
Pages: 229
Shipping Weight (lbs): 1.1
Dimensions (in): 9.3 x 6.2 x 0.6

ISBN: 1852336951
Dewey Decimal Number: 629.836
EAN: 9781852336950
ASIN: 1852336951

Publication Date: September 2, 2003
Availability: Usually ships in 1-2 business days

Also Available In:

  • Kindle Edition - Robust Autonomous Guidance: An Internal Model Approach (Advances in Industrial Control)
  • Digital - Robust Autonomous Guidance: An Internal Model Approach (Advances in Industrial Control)

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Product Description

A typical plant control system will be subject to the undesirable influence of exogenous commands and disturbances. In order to track and reject these Professor Isidori and his co-authors have designed a feedback control system based on embedding a model of these disturbances within the controller itself - the so-called "internal model".

Beginning with a review of the fundamental principles of internal-model-based feedback control design, Robust Autonomous Guidance moves on to expound recent enhancements to such designs and then to their implementation in systems operating under conditions of great uncertainty.

The three case studies presented: attitude control of a low-Earth-orbit satellite and the landing of fixed- and rotary-winged aircraft on a ship involve control systems coping with a high degree of nonlinear behaviour. The key issues addressed in each case study are the design of an adaptive internal model for the specific tracking task and of stabilizing control capable of steering the tracking error to zero while keeping all internal states bounded for any arbitrarily large but bounded envelope of initial data and uncertain parameters. Nested saturated controls form the basis of novel tools for asymptotic analysis and design.

Robust Autonomous Guidance will be of great interest to academic and industrial researchers working with nonlinear control systems and to engineers involved in the design of aerospatial guidance systems. It will also be a useful reference for graduate students working with non-linear systems.



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