Download Chemical Optimization Algorithm for Fuzzy Controller Design by Leslie Astudillo, Patricia Melin, Oscar Castillo (auth.) PDF

By Leslie Astudillo, Patricia Melin, Oscar Castillo (auth.)

In this publication, a unique optimization procedure encouraged via a paradigm from nature is brought. The chemical reactions are used as a paradigm to suggest an optimization strategy that simulates those average techniques. The proposed set of rules is defined intimately after which a suite of ordinary advanced benchmark services is used to judge the functionality of the set of rules. Simulation effects express that the proposed optimization set of rules can outperform different equipment in a collection of benchmark functions.

This chemical response optimization paradigm is additionally utilized to unravel the monitoring challenge for the dynamic version of a unicycle cellular robotic via integrating a kinematic and a torque controller in line with fuzzy good judgment conception. desktop simulations are awarded confirming that this optimization paradigm is ready to outperform different optimization strategies utilized to this actual robotic application.

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C. -H. -C. Lin, Trajectory tracking control of a laser-guided wheeled mobile robot, in Proceedings of the IEEE International Conference on Control Applications. V. Ulyanov, S. S. Ulyanov, K. V. G. Rizzotto, Soft computing for the intelligent robust control of a robotic unicycle with a new physical measure for mechanical controllability, soft computing, vol. 2. R. L. Lewis, Control of a non holonomic mobile robot using neural networks. IEEE Trans. T. H. Sheen, Heuristic fuzzy-neural network and its application to reactive navigation of a mobile robot.

3092E-08). 1). 10 shows the parameters used for the simulations of case 1. 89855. 13 shows the resulted input membership functions found by the proposed optimization algorithm for the linear and angular velocity errors. 14 shows the resulted output membership functions found by the proposed optimization algorithm for the left and right torques. 11 shows the values of the input/output membership functions for the Type-1 FLC found by the chemical reaction algorithm. 15 shows the obtained trajectory of the best result for Case 1.

Astudillo, O. Castillo, L. Aguilar, Intelligent control for a perturbed autonomous wheeled mobile robot: a type-2 fuzzy logic approach. R. Martinez, O. Castillo, L. Aguilar, Optimization of type-2 fuzzy logic controllers for a perturbed autonomous wheeled mobile robot using genetic algorithms. Inf. Sci. O. Castillo, R. Martinez-Marroquin, P. Melin, J. Soria, Comparative study of bio-inspired algorithms applied to the optimization of type-1 and type-2 fuzzy controllers for an autonomous mobile robot.

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