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{ "item_title" : "Safe Adaptive Control", "item_author" : [" Margareta Stefanovic", "Michael G. Safonov "], "item_description" : "Safe Adaptive Control gives a formal and complete algorithm for assuring the stability of a switched control system when at least one of the available candidate controllers is stabilizing. The possibility of having an unstable switched system even in the presence of a stabilizing candidate controller is demonstrated by referring to several well-known adaptive control approaches, where the system goes unstable when a large mismatch between the unknown plant and the available models exists (plant-model mismatch instability). Sufficient conditions for this possibility to be avoided are formulated, and a recipe to be followed by the control system designer to guarantee stability and desired performance is provided. The problem is placed in a standard optimization setting. Unlike the finite controller sets considered elsewhere, the candidate controller set is allowed to be continuously parametrized so that it can deal with plants with a very large range of uncertainties.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/1/84/996/452/1849964521_b.jpg", "price_data" : { "retail_price" : "109.99", "online_price" : "109.99", "our_price" : "109.99", "club_price" : "109.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Safe Adaptive Control|Margareta Stefanovic

Safe Adaptive Control : Data-Driven Stability Analysis and Robust Synthesis

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Overview

Safe Adaptive Control gives a formal and complete algorithm for assuring the stability of a switched control system when at least one of the available candidate controllers is stabilizing. The possibility of having an unstable switched system even in the presence of a stabilizing candidate controller is demonstrated by referring to several well-known adaptive control approaches, where the system goes unstable when a large mismatch between the unknown plant and the available models exists ("plant-model mismatch instability"). Sufficient conditions for this possibility to be avoided are formulated, and a "recipe" to be followed by the control system designer to guarantee stability and desired performance is provided. The problem is placed in a standard optimization setting. Unlike the finite controller sets considered elsewhere, the candidate controller set is allowed to be continuously parametrized so that it can deal with plants with a very large range of uncertainties.

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Details

  • ISBN-13: 9781849964524
  • ISBN-10: 1849964521
  • Publisher: Springer
  • Publish Date: February 2011
  • Dimensions: 9 x 6.1 x 0.4 inches
  • Shipping Weight: 0.5 pounds
  • Page Count: 148

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