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A Fuzzy Controller Based on Improved Ant Colony Algorithm for Parallel Automatic Parking

Zheng Guoqiang, Liang Zhao


Fuzzy controller was often used to solve the nonlinear and time-varying problem of the automatic parking. Considering the optimization problem of the traditional fuzzy controller, a method of multi-colony evolvement ant colony algorithm based on idle ant effect was proposed. The algorithm adopted multi-colony parallel to improve the data initialization, path construction and pheromone update. The method guaranteed the completeness of the membership function and made the fuzzy parameters with higher precision. In the paper, reference path based on Bezier curve have been used to generate the parking path, and both traditional controller and the designed controller were used to track the path. The experimental results showed that, comparing with the traditional fuzzy controller, the designed controller can improve the stability problem with less error and faster response speed.


Fuzzy controllers, automatic parking, ant colony algorithm, Bezier curve.

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