Human performance Human Adaptive Mechatronics HAM Manual control system Simple tracking operation Computer-based experiment Simple tracking task Point-to-point operation Human skill Helicopter test rig Hardware-based experiment Model-based approach Non-model approach
An interest in developing the intelligent machine system that works in conjunction with
human has been growing rapidly in recent years. A number of studies were conducted to
shed light on how to design an interactive, adaptive and assistive machine system to
serve a wide range of purposes including commonly seen ones like training,
manufacturing and rehabilitation. In the year 2003, Human Adaptive Mechatronics
(HAM) was proposed to resolve these issues. According to past research, the focus is
predominantly on evaluation of human skill rather than human performance and that is
the reason why intensive training and selection of suitable human subjects for those
experiments were required. As a result, the pattern and state of control motion are of
critical concern for these works.
In this research, a focus on human skill is shifted to human performance instead due to
its proneness to negligence and lack of reflection on actual work quality. Human
performance or Human Performance Index (HPI) is defined to consist of speed and
accuracy characteristics according to a well-renowned speed-accuracy trade-off or
Fitts’ Law. Speed and accuracy characteristics are collectively referred to as speed and
accuracy criteria with corresponding contributors referred to as speed and accuracy
variables respectively. This research aims at proving a validity of the HPI concept for
the systems with different architecture or the one with and without hardware elements.
A direct use of system output logged from the operating field is considered the main
method of HPI computation, which is referred to as a non-model approach in this thesis.
To ensure the validity of these results, they are compared against a model-based
approach based on System Identification theory. Its name is due to being involved with
a derivation of mathematical equation for human operator and extraction of
performance variables. Certain steps are required to match the processing outlined in
that of non-model approach. Some human operators with complicated output patterns
are inaccurately derived and explained by the ARX models.
A Doctoral Thesis. Submitted in partial fulfillment of the requirements for the award of Doctor of Philosophy of Loughborough University.