Fast Gaussian Process based Model Predictive Control with Uncertainty Propagation

Truong X. Nghiem, Trong Doan Nguyen, Viet Anh Le

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Gaussian Process based Model Predictive Control (GP-MPC), where the system model is learned from data by a Gaussian Process (GP) statistical model, has gained increasing interests in the control community. This is due to the modeling flexibility of GPs and their ability to provide probabilistic estimates of prediction uncertainty, which can be used to assess and guarantee the performance or safety of a control system. However, GP-MPC optimization problems are typically non-convex and highly demanding, and scales poorly with the model size, causing unsatisfactory solving performance, even with state-of-the-art solvers. These drawbacks hinder the application of GP-MPC in large-scale systems and in real-time control. Our previous work has developed a new concept, linearized Gaussian Process (linGP), and a linGP-based Sequential Convex Programming (linGP-SCP) algorithm that can accelerate solving GP-MPC problems significantly. However, the algorithm ignored uncertainty propagation in its multi-step GP predictions, resulting in over-confident predictions and an over-optimistic controller. This paper completes linGP-SCP by incorporating uncertainty propagation into GP-MPC and overcoming the computational challenge of uncertainty propagation to maintain the scalability and good performance of the overall algorithm. The improved algorithm is validated in two numerical examples, including a real-time control example of swinging up a single-arm pendulum.

Original languageEnglish (US)
Title of host publication2019 57th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1052-1059
Number of pages8
ISBN (Electronic)9781728131511
DOIs
StatePublished - Sep 2019
Event57th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2019 - Monticello, United States
Duration: Sep 24 2019Sep 27 2019

Publication series

Name2019 57th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2019

Conference

Conference57th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2019
Country/TerritoryUnited States
CityMonticello
Period9/24/199/27/19

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Hardware and Architecture
  • Safety, Risk, Reliability and Quality
  • Control and Optimization

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