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The concept of uncertainty is posed in almost any complex system includingparallel robots as an outstanding instance of dynamical robotics systems. Assuggested by the name, uncertainty, is some missing information that is beyondthe knowledge of human thus we may tend to handle it properly to minimize theside-effects through the control process.  Type-II fuzzy logic has shown its superiority over traditional fuzzy logicwhen dealing with uncertainty. Type-II fuzzy logic controllers are howevernewer and more promising approaches that have been recently applied to variousfields due to their significant contribution especially when noise (as animportant instance of uncertainty) emerges. During the design of Type-I fuzzylogic systems, we presume that we are almost certain about the fuzzy membershipfunctions which is not true in many cases. Thus T2FLS as a more realisticapproach dealing with practical applications might have a lot to offer. Type-IIfuzzy 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 numberbut rather is itself a type-I linguistic term. In this thesis the effects ofuncertainty in dynamic control of a parallel robot is considered. Morespecifically, it is intended to incorporate the Type-II Fuzzy Logic paradigminto a model based controller, the so-called computed torque control method,and apply the result to a 3 degrees of freedom parallel manipulator.  ...

A New Type-II Fuzzy Logic Based Controller for Non-linear Dynamical Systems with Application to a 3-PSP Parallel Robot