Hierarchical fuzzy logic systems are increasingly used in modelling and control applications. Their ability to cope with uncertainty inherent in complex systems makes them an attractive method for solving complex, uncertain, and dynamic systems. Hierarchical fuzzy logic systems are developed based on the individualistic systems. Such systems are unable to face the challenge of interaction that might be necessary between different fuzzy logic systems in hierarchical fuzzy logic systems for solving complex problems. This talk will investigate and report current and intelligent design and development of hierarchical fuzzy logic systems in multi-robot control and navigation. Several structured approaches to design and development of hierarchical fuzzy logic systems are explained. Design and development of hierarchical fuzzy logic systems and determination of the number of layers in a hierarchical fuzzy logic system are considered. The advantages and disadvantages of using hierarchical fuzzy logic systems for robotic control are also considered. The use of evolutionary algorithms in design and development of hierarchical fuzzy logic systems are discussed. The application of evolutionary learning to control of a simulated multi-robot system using hierarchical fuzzy logic systems are considered and simulation results are presented.
30 Nov 2019
5th International Symposium on Innovation in Information and Communication Technology