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A fuzzy Actor-Critic reinforcement learning network
Information Sciences: an International Journal
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Information Sciences: an International Journal
An adaptive neuro-fuzzy system for efficient implementations
Information Sciences: an International Journal
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Expert Systems with Applications: An International Journal
Assessment of uncertainty in the projective tree test using an ANFIS learning approach
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Dynamic control model of BOF steelmaking process based on ANFIS and robust relevance vector machine
Expert Systems with Applications: An International Journal
MICAI'12 Proceedings of the 11th Mexican international conference on Advances in Computational Intelligence - Volume Part II
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Stepping motors are widely used in robotics and in the numerical control of machine tools where they have to perform high-precision positioning operations. However, the variations of the mechanical configuration of the drive, which are common to these two applications, can lead to a loss of synchronism for high stepping rates. Moreover, the classical open-loop speed control is weak and a closed-loop control becomes necessary. In this paper, fuzzy logic is applied to control the speed of a stepping motor drive with feedback. A neuro-fuzzy hybrid approach is used to design the fuzzy rule base of the intelligent system for control. In particular, we used the ANFIS methodology to build a Sugeno fuzzy model for controlling the stepping motor drive. An advanced test bed is used in order to evaluate the tracking properties and the robustness capacities of the fuzzy logic controller.