International Journal of Systems, Control and Communications
Fuzzy logic design of self-tuning switching power supply
Expert Systems with Applications: An International Journal
Adaptive neural network controller for the flush material belt weigh feeder
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Optimal fuzzy control system using the cross-entropy method. A case study of a drilling process
Information Sciences: an International Journal
Information Sciences: an International Journal
Survey paper: A survey on industrial applications of fuzzy control
Computers in Industry
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An industrial weigh belt feeder is used to transport solid materials into a manufacturing process at a constant feedrate. It exhibits nonlinear behavior because of motor friction, saturation, and quantization noise in the sensors, which makes standard autotuning methods difficult to implement. The paper proposes and experimentally demonstrates two types of fuzzy logic controllers for an industrial weigh belt feeder. The first type is a PI-like fuzzy logic controller (FLC). A gain scheduled PI-like FLC and a self-tuning PI-like FLC are presented. For the gain scheduled PI-like FLC the output scaling factor of the controller is gain scheduled with the change of setpoint. For the self-tuning PI-like FLC, the output scaling factor of the controller is modified online by an updating factor whose value is determined by a rule base with the error and change of error of the controlled variable as the inputs. A fuzzy PI controller is also presented, where the proportional and integral gains are tuned online based on fuzzy inference rules. Experimental results show the effectiveness of the proposed fuzzy logic controllers. A performance comparison of the three controllers is also given.