Reliable and Optimal Coordination of Networked Systems and Action-Based Space Trajectory Generation/Estimation
Abstract
We highlight several areas we have been working on and the results obtained so far. 1)Stochastic adaptive optimization: Optimization methods are essential and have been usedextensively in a broad spectrum of applications. Most existing literature on optimizationalgorithms does not consider systems that involve unknown system parameters. This paperstudies a class of stochastic adaptive optimization problems in which identification ofunknown parameters and search for the optimal solutions must be performed simultaneously.Due to a fundamental conflict between parameter identifiability and optimality in suchproblems, we introduce a method of adding stochastic dither signals into the system, whichprovides a sufficient excitation for estimating the unknown parameters, leading to convergentadaptive optimization algorithms. Joint identification and optimization algorithms aredeveloped and their simultaneous convergence properties of parameter estimation andoptimization variable updates are proved.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 29, 2021
- Accession Number
- AD1153236
Entities
People
- William M. McEneaney
Organizations
- University of California, San Diego