A methodology for designing a Sugeno type Fuzzy Logic Controller (FLC) for accurate position control of a pneumatic servo system is presented. Adaptive Neuro Fuzzy Inference System technique is employed to construct a fuzzy inference system whose membership function parameters are tuned using a training data set comprising of input/output signal of the pneumatic servo system with proportional control. Hybrid backpropogation-least square algorithm is used for training of the Fuzzy Inference System (FIS). The resulting FIS optimally projected the behavior of training data set. To obtain the desired steady-state response, the fuzzy inference system is further tuned using the expert knowledge of the input/output response of the system. The system response for various reference inputs is compared quantitatively with that of the system without fuzzy logic controller, and excellent improvement in steady-state response is observed.
Design of a Fuzzy Logic Controller Using ANFIS for Accurate Position Control of a Pneumatic Servo System
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Dhami, SS, Bhasin, SS, & Mahapatra, PB. "Design of a Fuzzy Logic Controller Using ANFIS for Accurate Position Control of a Pneumatic Servo System." Proceedings of the ASME 2008 International Mechanical Engineering Congress and Exposition. Volume 5: Design, Analysis, Control and Diagnosis of Fluid Power Systems. Boston, Massachusetts, USA. October 31–November 6, 2008. pp. 89-97. ASME. https://doi.org/10.1115/IMECE2008-66940
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