Author ORCID Identifier
Date Available
2-2-2020
Year of Publication
2019
Degree Name
Doctor of Philosophy (PhD)
Document Type
Doctoral Dissertation
College
Engineering
Department/School/Program
Mechanical Engineering
First Advisor
Dr. Jesse B. Hoagg
Abstract
Humans learn to interact with many complex physical systems. For example, humans learn to fly aircraft, operate drones, and drive automobiles. We present results from human-in-the-loop (HITL) experiments, where human subjects interact with dynamic systems while performing command-following tasks multiple times over a one-week period. We use a new subsystem identification (SSID) algorithm to estimate the control strategies (feedforward, feedforward delay, feedback, and feedback delay) that human subjects use during their trials. We use experimental and SSID results to examine the effects of system characteristics (e.g., system zeros, relative degree, system order, phase lag, time delay), reference command, and command-following objectives on humans command-following performance and on the control strategies that the humans learn. Results suggest that nonminimum-phase zeros, relative degree, phase lag, and time delay tend to make dynamic systems difficult for human to control. Subjects can generalize their control strategies from one task to another and use prediction of the reference command to improve their command-following performance. However, this dissertation also provides evidence that humans can learn to improve performance without prediction.
This dissertation also presents a new SSID algorithm to model the control strategies that human subjects use in HITL experiments where they interact with dynamic systems. This SSID algorithm uses a two-candidate-pool multi-convex-optimization approach to identify feedback-and-feedforward subsystems with time delay that are interconnected in closed loop with a known subsystem. This SSID method is used to analyze the human control behavior in the HITL experiments discussed above.
Digital Object Identifier (DOI)
https://doi.org/10.13023/etd.2019.344
Funding Information
National Science Foundation (award number: CMMI-1405257), Kentucky Science and Engineering Foundation, and Ford Motor Company.
Recommended Citation
Seyyedmousavi, Seyyedalireza, "THE EFFECTS OF SYSTEM CHARACTERISTICS, REFERENCE COMMAND, AND COMMAND-FOLLOWING OBJECTIVES ON HUMAN-IN-THE-LOOP CONTROL BEHAVIOR" (2019). Theses and Dissertations--Mechanical Engineering. 140.
https://uknowledge.uky.edu/me_etds/140
