Navigation and collision avoidance are major areas of research in mobile robotics that involve varying degrees of uncertainty. In general, the problem consists of achieving sensor based motion control of a mobile robo...
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Navigation and collision avoidance are major areas of research in mobile robotics that involve varying degrees of uncertainty. In general, the problem consists of achieving sensor based motion control of a mobile robot among obstacles in structured and/or unstructured environments with collision-free motion as the proirity. A fuzzy logic based intelligent control strategy has been developed here to computationally implement the approximate reasoning necessary for handling the uncertainty inherent in the collision avoidance problem.< >
This paper proposes two simple adaptive control schemes of robot manipulators. The first one is the state feedback control which consists of feedforward from the desired position trajectory, PD feedback from the actua...
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A comparative study of a classical expert system and an adaptive fuzzy expert control system for an inverted pendulum is presented. Specifically, three controllers are compared: constant gain, expert controller, and a...
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A comparative study of a classical expert system and an adaptive fuzzy expert control system for an inverted pendulum is presented. Specifically, three controllers are compared: constant gain, expert controller, and an adaptive fuzzy expert controller. The comparative study was done by means of computer simulation through the Matlab and Togai InfraLogic's Fuzzy-C software programs. It is seen that the fuzzy expert controller provides much better performance than the regular expert system.< >
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