  The concept of uncertainty is posed in almost any complex system including
parallel robots as an outstanding instance of dynamical robotics systems. As
suggested by the name, uncertainty, is some missing information that is beyond
the knowledge of human thus we may tend to handle it properly to minimize the
side-effects through the control process.
  Type-II fuzzy logic has shown its superiority over traditional fuzzy logic
when dealing with uncertainty. Type-II fuzzy logic controllers are however
newer and more promising approaches that have been recently applied to various
fields due to their significant contribution especially when noise (as an
important instance of uncertainty) emerges. During the design of Type-I fuzzy
logic systems, we presume that we are almost certain about the fuzzy membership
functions which is not true in many cases. Thus T2FLS as a more realistic
approach dealing with practical applications might have a lot to offer. Type-II
fuzzy logic takes into account a higher level of uncertainty, in other words,
the membership grade for a type-II fuzzy variable is no longer a crisp number
but rather is itself a type-I linguistic term. In this thesis the effects of
uncertainty in dynamic control of a parallel robot is considered. More
specifically, it is intended to incorporate the Type-II Fuzzy Logic paradigm
into a model based controller, the so-called computed torque control method,
and apply the result to a 3 degrees of freedom parallel manipulator.
  ...
