Journal of Intelligent and Robotic Systems
Computer Vision Using Fuzzy Logic for Robot Manipulator
RSCTC '00 Revised Papers from the Second International Conference on Rough Sets and Current Trends in Computing
Design and tuning of importance-based fuzzy logic controller for a flexible-link manipulator
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Fuzzy Controller for Robot Manipulators
IFSA '07 Proceedings of the 12th international Fuzzy Systems Association world congress on Foundations of Fuzzy Logic and Soft Computing
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
An advanced FMRL controller for FACTS devices to enhance dynamic performance of power systems
International Journal of Automation and Computing
Fuzzy model reference control with adaptation of input fuzzy sets
Knowledge-Based Systems
Fuzzy Control of a Helio-Crane
Journal of Intelligent and Robotic Systems
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There are two main drawbacks in fuzzy control: 1) the design of fuzzy controllers is usually performed in an ad hoc manner where it is often difficult to choose some of the controller parameters; and 2) the fuzzy controller constructed for the nominal plant may later perform inadequately if significant and unpredictable plant parameter variations occur. In this paper we illustrate these two problems on a two-link flexible robot testbed by: 1) developing, implementing, and evaluating a fuzzy controller for the robotic mechanism, and 2) illustrating that payload variations can have negative effects on the performance of a well designed fuzzy control system. Next, we show how to develop and implement a fuzzy model reference learning controller for the flexible robot and illustrate that it can automatically synthesize a rule-base for a fuzzy controller that will achieve comparable performance to the case where it was manually constructed, and automatically tune the fuzzy controller so that it can adapt to variations in the payload