Cell Mapping Based Fuzzy Control of Car Parking

Tea-Quin Kim
Ming-Chuan Leu, Missouri University of Science and Technology

This document has been relocated to http://scholarsmine.mst.edu/mec_aereng_facwork/3411

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This paper describes the development of a near-optimal fuzzy controller for maneuvering a car in a parking lot. To generate the rules of the fuzzy controller, a cell mapping method is utilized to systematically generate near-optimal trajectories for all possible initial states in the parking lot. Based on the input-output relations of these trajectories, which represent the states and controls of the corresponding cells, a set of fuzzy rules are generated automatically. In order to result in a small number of fuzzy rules from the large amount of numerical information generated by cell mapping, grouping of trajectories is proposed and each rule applies to the cells in one group. This reduces substantially the number of rules in the fuzzy controller compared with establishing the rules directly using the control data of individual cells