Abstract

In this paper, the single input rule modules (SIRMs) dynamically connected fuzzy inference model is employed to design a path following controller for a unicycle wheeled mobile robot(WMR).The SIRMs model is mainly used to reduce the number of fuzzy inference rules and consequently reduce the processing time of the conventional Fuzzy Logic Control (FLC) schemes. The adopted path following strategy uses two control unites working in parallel to drive the WMR to follow a path composed of a succession of discrete waypoints. The first unit is a heading controller charged of generatingthe angular velocity command and thesecond one is a linear velocity controller charged of the generation the speed control signal.For the headingcontroller, all input variables are assigned with two fuzzy inference modules: a SIRM and a dynamic importancedegree (DID). The structure of the SIRMs based linear velocitycontrolunitwas modified to simplify the designand to fulfill the requirements of the path following strategy. It contains two SIRM modules andonecommonDID. To ensure the stability of the WMR'smotion, the SIRMs and the DIDs in the two control units were designedin such a manner that the control of the robot's orientationgets higher priority over the control of the WMRspeed. The use of the SIRM fuzzy inference model allows the online automatic adjustment of priority orders of thedifferent control actions. No optimizationof the controller parameters is required since thatall base values areset to 0 and all the breadthsare set to 1 for the DID modules. This means that all the input items play equal rolesin the control of the WMR.The structure of the proposedpath following controller is simple and the inferencerules are intuitively understandable because they are inspired from the knowledge of a human expert. Numericalsimulations conducted in the MATLABenvironment show that the proposed SIRMs based controller outperforms apath followingcontroller that uses the conventional FLC scheme.

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