Abstract
The fuzzy logic controller is widely used in different areas due to the unique simplicity and different abilities as it has such a good response to complex and high-order systems. In addition, it is apparent that the fuzzy controller parameters and Membership Function (MF) selection has a vital role in the quality of the controller performance improvement. Due to the existence of several dimensions for fuzzy parameter determination, one of the best solutions is intelligent algorithms, which are often used in last years. Accordingly, this paper aims at doing a comprehensive survey among different methods of fuzzy parameters optimization in robotic systems. The reviewed articles have shown due to the need for a lower amount of computational burden and time limitations of robotic systems, the preferred MFs in robotic applications are the first-order ones.
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