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Governing Parameter Changes in Nonlinear Parameter-Dependent Optimization Problems

[+] Author Affiliations
Rohit Gupta, Ilya V. Kolmanovsky

University of Michigan, Ann Arbor, MI

Paper No. DSCC2013-3845, pp. V003T36A003; 10 pages
  • ASME 2013 Dynamic Systems and Control Conference
  • Volume 3: Nonlinear Estimation and Control; Optimization and Optimal Control; Piezoelectric Actuation and Nanoscale Control; Robotics and Manipulators; Sensing; System Identification (Estimation for Automotive Applications, Modeling, Therapeutic Control in Bio-Systems); Variable Structure/Sliding-Mode Control; Vehicles and Human Robotics; Vehicle Dynamics and Control; Vehicle Path Planning and Collision Avoidance; Vibrational and Mechanical Systems; Wind Energy Systems and Control
  • Palo Alto, California, USA, October 21–23, 2013
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-5614-7
  • Copyright © 2013 by ASME


The paper treats a class of parameter-dependent optimization/root finding problems where the minimizer or a real root need to be determined as a function of parameter. Applications of parameter-dependent optimization include spacecraft debris avoidance, adaptive control of Hybrid Electric Vehicles, engine mapping and model predictive control. In these and other problems, the parameter changes can be controlled either directly or indirectly. In this paper, the error analysis of a dynamic predictor-corrector Newton’s type algorithm is presented. Based on this analysis, an approach to govern the changes in the parameter to enable the algorithm to track the minimizer within an acceptable error bound is described. Two simulation examples are presented. In the first example the objective is to minimize the distance between points on a curve and a given set and simultaneously move as fast as possible along the given curve. In the second example we illustrate the use of this technique for aircraft flight envelope estimation. Specifically, we estimate maximum speed of an aircraft as a function of its altitude and flight path angle.

Copyright © 2013 by ASME
Topics: Optimization



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