Finite horizon robust synthesis using integral quadratic constraints

Abstract

We present a robust synthesis algorithm for uncertain linear time‐varying (LTV) systems on finite horizons. The uncertain system is described as an interconnection of a known LTV system and a perturbation. The input–output behavior of the perturbation is specified by time‐domain Integral Quadratic Constraints (IQCs). The objective is to synthesize a controller to minimize the worst‐case performance. This leads to a nonconvex optimization. The proposed approach alternates between an LTV synthesis step and an IQC analysis step. Both induced and terminal Euclidean norm penalties on output are considered for finite horizon performance. The proposed algorithm ensures that the robust performance is nonincreasing at each iteration step. The effectiveness of this method is demonstrated using numerical examples.

Document Details

Document Type
Pub Defense Publication
Publication Date
Feb 11, 2021
Source ID
10.1002/rnc.5431

Entities

People

  • Jyot Buch
  • Peter Seiler

Organizations

  • Office of Naval Research
  • University of Michigan
  • University of Minnesota

Tags

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Mathematical Modeling and Probability Theory.
  • Operations Research

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms