A hybrid model predictive controller for path planning and path following

Kun Zhang, Jonathan Sprinkle, Ricardo G. Sanfelice

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

8 Scopus citations

Abstract

The use of nonlinear model-predictive methods for path planning and following has the advantage of concurrently solving problems of obstacle avoidance, feasible trajectory selection, and trajectory following, while obeying constraints 011 control inputs and state values. However, such approaches are computationally intensive, and may not be guaranteed to return a result in bounded time when performing a non- convex optimization. This problem is an interesting application to cyber-physical systems due to their reliance 011 computation to carry out complex control. The computa-tional burden can be addressed through model reduction, at a cost of potential (bounded) model error over the prediction horizon. In this paper we introduce a metric called uncontrollable divergence, and discuss how the selection of the model to use for the predictive controller can be addressed by evaluating this metric, which reveals the divergence between predicted and true states caused by return time and model mismatch. A map of uncontrollable divergence plotted over the state space gives the criterion to judge where reduced models can be tolerated when high update rate is preferred (e.g. at high speed and small steering angles), and where high-fidelity models are required to avoid obstacles or make tighter curves (e.g. at large steering angles). With this metric, we design a hybrid controller that switches at runtime between predictive controllers in which respective models are deployed.

Original languageEnglish (US)
Title of host publicationACM/IEEE 6th International Conference on Cyber-Physical Systems, ICCPS 2015
PublisherAssociation for Computing Machinery, Inc
Pages139-148
Number of pages10
ISBN (Print)9781450334556
DOIs
Publication statusPublished - Apr 14 2015
Event6th ACM/IEEE International Conference on Cyber-Physical Systems, ICCPS 2015 - Seattle, United States
Duration: Apr 14 2015Apr 16 2015

Other

Other6th ACM/IEEE International Conference on Cyber-Physical Systems, ICCPS 2015
CountryUnited States
CitySeattle
Period4/14/154/16/15

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Keywords

  • Hybrid control
  • Model error evaluation
  • MPC

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture

Cite this

Zhang, K., Sprinkle, J., & Sanfelice, R. G. (2015). A hybrid model predictive controller for path planning and path following. In ACM/IEEE 6th International Conference on Cyber-Physical Systems, ICCPS 2015 (pp. 139-148). Association for Computing Machinery, Inc. https://doi.org/10.1145/2735960.2735966