Hierarchical Fuzzy Controllers with Reduced Rule-Base

Abstract

A waypoint, navigation controller and corresponding controlling methods are described, where the controller functions as a multiple input-multiple output, e.g., nonlinear angular velocity and linear speed controller for a land vessel such as a skid-steer vehicle. The controller and the controlling methods may be based on a fuzzy logic controller (alternatively referred to as “fuzzy controller”). The membership functions of the fuzzy controller may employ a trapezoidal structure with a symmetric rule-base. In addition, a Hierarchical Rule-Base Reduction (HRBR) is incorporated into the controller so as to select only the rules most influential on state errors by selecting inputs/outputs, determining the most globally influential inputs, and generating a hierarchy relating inputs via a Fuzzy Relations Control Strategy (FRCS). This disclosure is further directed to a fuzzy logic controller with Hierarchical Rule-Base Reduction (HRBR) and implemented as neural network and training of such a fuzzy logic controller via reinforcement learning based on an ANFIS actor.

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