Mitigate Uncertainty in Space Control Systems Through Computational Optimal Control
Abstract
How to mitigate uncertainty in optimal control framework is a problem of great practical importance, especially in space control area. On one hand, stringent performance and complex nonlinearities of space systems demand the use of optimal control. On the other, uncertainty in any control systems is ubiquitous. It degrades performance of optimal control, and can potentially cause failure in control systems. Recently, a new framework, Riemann-Stieltjes (RS) optimal control, has been proposed to explicitly address uncertain in optimal control setting. In the proposed research, we will explore RS optimal control framework to mitigate the uncertainty in space control systems. We will conduct research on the following topics: 1) analyzing modeling issues in Riemann-Stieltjes optimal control, especially on handling different objectives in constrained problems; 2) developing computational algorithms to improve the efficiency for problems with higher dimensional uncertainty, and conducting research to analyze the performance of the developed algorithms; 3) investigating feedback implementation for optimal control of uncertain systems; 4) testing the results on space control applications. The proposed research will improve control performance of spacecraft, and enrich scientific missions of satellites; thus benefits general public. Moreover, the outcome of the proposed work is portable to other control systems. The algorithms developed in this project provide engineers with new ways to solve uncertain optimal control problems in challenging engineering applications, for example, motion planning of autonomous vehicles, an area with many industry applications and interests. The research work also enhances high education by engaging graduate students into interdisciplinary training on modeling, computational mathematics, and engineering implementations.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Aug 08, 2016
- Source ID
- N002441510048
Entities
People
- Qi Gong
Organizations
- United States Air Force
- University of California, Santa Cruz