On the Optimality and Convergence Properties of the Iterative Learning Model Predictive Controller
Author:
Affiliation:
1. California Institute of Technology, South Pasadena, CA, USA
2. Automatic Control Laboratory, École polytechnique fédérale de Lausanne (EPFL), Lausanne, Switzerland
Funder
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
RISK project Risk Aware Data-Driven Demand Response
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Computer Science Applications,Control and Systems Engineering
Link
http://xplorestaging.ieee.org/ielx7/9/10002258/09705072.pdf?arnumber=9705072
Reference18 articles.
1. Biased aggregation, rollout, and enhanced policy improvement for reinforcement learning;bertsekas;Labortory for Information and Decision Systems Reportv,2018
2. Linear Least-Squares algorithms for temporal difference learning
3. Learning to predict by the methods of temporal differences
4. Controller design and value function approximation for nonlinear dynamical systems
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