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Swinging Up and Stabilization Control of the Furuta Pendulum using Model Predictive Path Integral Control

  • This paper presents the swinging up and stabilization control of a Furuta pendulum using the recently published nonlinear Model Predictive Path Integral (MPPI) approach. This algorithm is based on a path integral over stochastic trajectories and can be parallelized easily. The controller parameters are tuned offline regarding the nonlinear system dynamics and simulations. Constraints in terms of state and input are taken into account in the cost function. The presented approach sequentially computes an optimal control sequence that minimizes this optimal control problem online. The control strategy has been tested in full-scale experiments using a pendulum prototype. The investigated MPPI controller has demonstrated excellent performance in simulation for the swinging up and stabilizing task. In order to also achieve outstanding performance in a real-world experiment using a controller with limited computing power, a linear quadratic controller (LQR) is designed for the stabilization task. In this paper, the determination of the controller parameters for the MPPI algorithm is described in detail. Further, a discussion treats the advantages of the nonlinear MPPI control.

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Author:Hannes HomburgerORCiD, Stefan WirtensohnORCiD, Johannes ReuterORCiD
Parent Title (English):Proceedings of the 30th Mediterranean Conference on Control and Automation (MED), 28. June - 1. July 2022, Vouliagmeni, Greece
Document Type:Conference Proceeding
Year of Publication:2022
Release Date:2022/09/20
First Page:7
Last Page:12
Volltext für Angehörige der Hochschule Konstanz via Datenbank IEEE Xplore abrufbar.
Institutes:Institut für Systemdynamik - ISD
Relevance:Keine peer reviewed Publikation (Wissenschaftlicher Artikel und Aufsatz, Proceeding, Artikel in Tagungsband)
Open Access?:Nein
Licence (English):License LogoLizenzbedingungen IEEE