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Model Structure Adaptation: A Gradient-Based Approach

[+] Author Affiliations
William G. La Cava, Kourosh Danai

University of Massachusetts Amherst, Amherst, MA

Paper No. DSCC2015-9658, pp. V001T01A001; 10 pages
doi:10.1115/DSCC2015-9658
From:
  • ASME 2015 Dynamic Systems and Control Conference
  • Volume 1: Adaptive and Intelligent Systems Control; Advances in Control Design Methods; Advances in Non-Linear and Optimal Control; Advances in Robotics; Advances in Wind Energy Systems; Aerospace Applications; Aerospace Power Optimization; Assistive Robotics; Automotive 2: Hybrid Electric Vehicles; Automotive 3: Internal Combustion Engines; Automotive Engine Control; Battery Management; Bio Engineering Applications; Biomed and Neural Systems; Connected Vehicles; Control of Robotic Systems
  • Columbus, Ohio, USA, October 28–30, 2015
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-5724-3
  • Copyright © 2015 by ASME

abstract

A gradient-based method of symbolic adaptation is introduced for a class of continuous dynamic models. The proposed Model Structure Adaptation Method (MSAM) starts with the first-principles model of the system and adapts its structure after adjusting its individual components in symbolic form. A key contribution of this work is its introduction of the model’s parameter sensitivity as the measure of symbolic changes to the model. This measure, which is essential to defining the structural sensitivity of the model, not only accommodates algebraic evaluation of candidate models in lieu of more computationally expensive simulation-based evaluation, but also makes possible the implementation of gradient-based optimization in symbolic adaptation. The applicability of the proposed method is evaluated in application to several models which demonstrate its potential utility.

Copyright © 2015 by ASME

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