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Fuzzy Controller Tuning Using Bioegeography-Based Optimization

Fuzzy Controller Tuning Using Bioegeography-Based Optimization. Dan Simon Cleveland State University. Assuming sum-normal triangular MFs, there are five parameters for each input, and five parameters for each ouput Inputs: c  [5, 3], w i  [0, 3]

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Fuzzy Controller Tuning Using Bioegeography-Based Optimization

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  1. Fuzzy Controller Tuning Using Bioegeography-Based Optimization Dan SimonCleveland State University

  2. Assuming sum-normal triangular MFs, there are five parameters for each input, and five parameters for each ouput Inputs: c [5, 3], wi  [0, 3] Output: c [0.5, 0.2], wi  [0, 0.3] c w1 w2 w3 w4

  3. BBO(@CruiseControl); Example BBO run

  4. >> VehicleControl; ? paramBBOSave.txt Error = 0.0017093 (Gradient descent error = 0.0056923 unconstrained, 0.0065893 constrained) Retrieve data from a plot: axs = get(gcf, 'Children'); pos = get(axs(1), 'Children'); Y = get(pos, 'YData');

  5. PlotMem('paramBBOSave.txt', 2, [5 5], 1, 5)

  6. Future Work • Optimize other MF shapes with BBO • Optimize fuzzy rule base • Optimize S-norm, T-norm, defuzzification method, and number of MFs • Optimize fuzzy cruise controller for additional operating conditions, or under noisy conditions

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