Control-Theoretic Models of Feedforward in Manual Control

Frank M. Drop

Cite this publication as

Frank M. Drop, Control-Theoretic Models of Feedforward in Manual Control (2016), Logos Verlag, Berlin, ISBN: 9783832593810

5
accesses

Description / Abstract

Understanding how humans control a vehicle (cars, aircraft, bicycles, etc.) enables engineers to design faster, safer, more comfortable, more energy efficient, more versatile, and thus better vehicles. In a typical control task, the Human Controller (HC) gives control inputs to a vehicle such that it follows a particular reference path (e.g., the road) accurately. The HC is simultaneously required to attenuate the effect of disturbances (e.g., turbulence) perturbing the intended path of the vehicle. To do so, the HC can use a control organization that resembles a closed-loop feedback controller, a feedforward controller, or a combination of both. Previous research has shown that a purely closed-loop feedback control organization is observed only in specific control tasks, that do not resemble realistic control tasks, in which the information presented to the human is very limited. In realistic tasks, a feedforward control strategy is to be expected; yet, almost all previously available HC models describe the human as a pure feedback controller lacking the important feedforward response. Therefore, the goal of the research described in this thesis was to obtain a fundamental understanding of feedforward in human manual control. First, a novel system identification method was developed, which was necessary to identify human control dynamics in control tasks involving realistic reference signals. Second, the novel identification method was used to investigate three important aspects of feedforward through human-in-the-loop experiments which resulted in a control-theoretical model of feedforward in manual control. The central element of the feedforward model is the inverse of the vehicle dynamics, equal to the theoretically ideal feedforward dynamics. However, it was also found that the HC is not able to apply a feedforward response with these ideal dynamics, and that limitations in the perception, cognition, and action loop need to be modeled by additional model elements: a gain, a time delay, and a low-pass filter. Overall, the thesis demonstrated that feedforward is indeed an essential part of human manual control behavior and should be accounted for in many human-machine applications.

Table of content

  • BEGINN
  • 1 Introduction
  • 1.1 Skill, rule, knowledge based behavior
  • 1.2 Cybernetic approach
  • 1.3 Empirical evidence for feedforward in manual control
  • 1.4 Human modeling and identification
  • 1.5 Goal and approach
  • 1.6 Outline of the thesis
  • 2 Identification of the feedforward component with predictable target signals
  • 2.1 Introduction
  • 2.2 Background
  • 2.3 Control Behavior Models and Simulations
  • 2.4 Experiment
  • 2.5 Results
  • 2.6 Discussion
  • 2.7 Conclusions
  • 3 Feedforward control behavior during a lateral reposition task
  • 3.1 Introduction
  • 3.2 ADS-33 Lateral reposition task
  • 3.3 Model of pilot control dynamics
  • 3.4 Performance simulations
  • 3.5 Identification
  • 3.6 Experiment
  • 3.7 Results
  • 3.8 Discussion
  • 3.9 Conclusions
  • 4 Constraints in identification of multi-loop feedforward models
  • 4.1 Introduction
  • 4.2 Control Task and HC Model
  • 4.3 Identification methods
  • 4.4 Computer Simulations
  • 4.5 Results
  • 4.6 Conclusions
  • 5 Objective model selection for identifying the feedforward response
  • 5.1 Introduction
  • 5.2 Identification Problem and Approach
  • 5.3 ARX Identification and Model Selection
  • 5.4 Model Selection Criterion Tuning
  • 5.5 Example Identification Problem
  • 5.6 Results I: Tuning the Model Selection Criterion
  • 5.7 Results II: Analysis of Ybest-Yhyp Similarity
  • 5.8 Discussion
  • 5.9 Conclusions
  • 6 Effects of target signal shape and system dynamics on feedforward
  • 6.1 Introduction
  • 6.2 Control task
  • 6.3 HC Model
  • 6.4 Performance simulations
  • 6.5 Experiment
  • 6.6 Experiment results
  • 6.7 Discussion
  • 6.8 Conclusions
  • 7 The predictability of a target signal affects manual feedforward control
  • 7.1 Introduction
  • 7.2 Signal Predictability
  • 7.3 HC Model and Simulations
  • 7.4 Experiment
  • 7.5 Results and discussion
  • 7.6 Conclusions
  • 8 Simultaneous use of feedforward, error feedback, and output feedback
  • 8.1 Introduction
  • 8.2 Control Task
  • 8.3 HC models
  • 8.4 Offline HC model simulations
  • 8.5 System identification and parameter estimation
  • 8.6 Experiment method
  • 8.7 Results
  • 8.8 Discussion
  • 8.9 Conclusion
  • 9 Discussion and recommendations
  • 9.1 Exploring the presence of feedforward in manual control tasks
  • 9.2 Development of an identification procedure for feedforward in manual control tasks
  • 9.3 Investigating three important aspects of feedforward in manual control tasks
  • 9.4 Human modeling and identification
  • 9.5 A fundamental understanding of feedforward in manual control
  • 10 Conclusions
  • 10.1 Exploring the presence of feedforward in manual control tasks
  • 10.2 Development of an identification procedure for feedforward in manual control tasks
  • 10.3 Investigating three important aspects of feedforward in manual control tasks
  • 10.4 General conclusions

More of this series

    Related titles

      More of this author(s)