Determining human control intent using inverse LQR solutions

M. Cody Priess, Jongeun Choi, Clark Radcliffe

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

3 Citations (Scopus)

Abstract

In this paper, we have developed a method for determining the control intention in human subjects during a prescribed motion task. Our method is based on the solution to the inverse LQR problem, which can be stated as: does a given controller K describe the solution to a time-invariant LQR problem, and if so, what weights Q and R produce K as the optimal solution? We describe an efficient Linear Matrix Inequality (LMI) method for determining a solution to the general case of this inverse LQR problem when both the weighting matrices Q and R are unknown. Additionally, we propose a gradient-based, leastsquares minimization method that can be applied to approximate a solution in cases when the LMIs are infeasible. We develop a model for an upright seated-balance task which will be suitable for identification of human control intent once experimental data is available.

Original languageEnglish
Title of host publicationAerial Vehicles; Aerospace Control; Alternative Energy; Automotive Control Systems; Battery Systems; Beams and Flexible Structures; Biologically-Inspired Control and its Applications;
PublisherAmerican Society of Mechanical Engineers (ASME)
ISBN (Print)9780791856123
DOIs
Publication statusPublished - 2013 Jan 1
EventASME 2013 Dynamic Systems and Control Conference, DSCC 2013 - Palo Alto, CA, United States
Duration: 2013 Oct 212013 Oct 23

Publication series

NameASME 2013 Dynamic Systems and Control Conference, DSCC 2013
Volume1

Other

OtherASME 2013 Dynamic Systems and Control Conference, DSCC 2013
CountryUnited States
CityPalo Alto, CA
Period13/10/2113/10/23

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All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering

Cite this

Priess, M. C., Choi, J., & Radcliffe, C. (2013). Determining human control intent using inverse LQR solutions. In Aerial Vehicles; Aerospace Control; Alternative Energy; Automotive Control Systems; Battery Systems; Beams and Flexible Structures; Biologically-Inspired Control and its Applications; [V001T07A003] (ASME 2013 Dynamic Systems and Control Conference, DSCC 2013; Vol. 1). American Society of Mechanical Engineers (ASME). https://doi.org/10.1115/DSCC2013-3874