The knowledge-based control of autonomous vehicles is based on a collection of rules, rather than an analytical controller. Each rule in the controller prescribes the control for a specific situation. An experimental method of control-rule derivation is described. A two-stage identification process is used. First, the structure of the mobile robot is determined and the state variables are defined. Then the fuzzy relations that are essential for the derivation of optimal control rules are found by experimentation. A minimum-time fuzzy control algorithm for mobile robot position control and an efficient fuzzy inferencing method are included.
|Original language||English (US)|
|Title of host publication||Unknown Host Publication Title|
|Publisher||IEEE Computer Society|
|Number of pages||6|
|State||Published - Jan 1 1987|
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