Paper Info
Title
Approximately Optimal Controllers for Quantitative Two-Phase Reach-Avoid Problems on Nonlinear Systems
Abstract
The present work deals with quantitative two-phase reach-avoid problems on nonlinear control systems. This class of optimal control problem requires the plant's state to visit two (rather than one) target sets in succession while minimizing a prescribed cost functional. As we illustrate, the naive approach, which subdivides the problem into the two evident classical reach-avoid tasks, usually does not result in an optimal solution. In contrast, we prove that an optimal controller is obtained by consecutively solving two special quantitative reach-avoid problems. In addition, we present a fully-automated method based on Symbolic Optimal Control to practically synthesize for the considered problem class approximately optimal controllers for sampled-data nonlinear plants. Experimental results on parcel delivery and on an aircraft routing mission confirm the practicality of our method.
Year
DOI
Venue
2020
10.1109/CDC42340.2020.9304048
2020 59th IEEE Conference on Decision and Control (CDC)
Keywords
DocType
ISSN
quantitative two-phase reach-avoid problems,nonlinear systems,nonlinear control systems,quantitative reach-avoid problems,symbolic optimal control,sampled-data nonlinear plants,reach-avoid tasks,target sets,prescribed cost functional,fully-automated method,parcel delivery,aircraft routing mission
Conference
0743-1546
ISBN
Citations 
PageRank 
978-1-7281-7448-8
0
0.34
References 
Authors
0
2
Name
Order
Citations
PageRank
Weber Alexander100.34
Knoll Alexander200.34