phdindustrialengineering

Lecture: Man‐machine Systems

Enrico M. Staderini

More appropriately, but less understandable by the neophyte, this course might be named “Control theory for humans”. Indeed, most of the science work to study human movement was (is) made with the eighteenth‐century approach of describing nature instead of understanding it. It is the aim of this course that of inferring the operating strategies that the human being is implementing to control its body or to control any external artificial machine operated by its body. This course goes beyond biomechanics in the sense that we will be concerned about how the body controls its behaviour in space to optimize movements or to optimize the behaviour of a machine operated by the human.

The finalscope will be that of quantifying the mechanical performances of a human being based on the identification of the control function the human is implementing to control its movement. Although neurophysiologists have a clear understanding of the sites in the human nervous system which are responsible for the control strategy of movement, we will not enter into physiological or anatomical aspects as the human control system will be considered, from the engineering point of view, as a simple black box whose input‐output control function will be the focus of our concern.

This is absolutely not a pure academical research, indeed important applications will result like understanding why a certain athlete is better than another, how to optimise training in sport or to optimize rehabilitation in disabled people, how to stage movements’ impairment until (maybe) shading a new light on Parkinson disease.

The course requires a good preliminary knowledge of mathematics at bachelor level.

This is a short list of topics:

Preliminary recall of control theory concepts

  • Oriented abstract system (description and state)
  • Laplace transform, gain, poles, zeros, delays
  • Feedback and stability concepts

Control theory applied to human movement

  • The human controller in static and dynamic performance
  • Perception, attention, forecasting and motion
  • Natural feedback vs. artificial feedback also known as biofeedback
  • The effects of speed and delay

Identification methods

  • System parameters identification from input‐output signals
  • The residue problem
  • The effect of noise (internal and external)
  • Stability of the man‐machine system
  • Applications
    • Case of the car driving, case of the mouse controller, case of the joystick controller
    • Self‐stabilizing controllers
    • Application to neurological diseases of motor behaviour
    • Application to sport gestures in normal people