OPERATION OF INDUSTERIAL ROBOT USING FUZZY LOGIC

Abstract

In Recent years, fuzzy control has grown in popularity, its use has been proposed in applications that extend beyond those which it is sought to replace human operators. Fuzzy control is now often considered for applications in which human operators have never been used, e.g. servomechanism. In such applications, it is the facility of fuzzy systems to act as function approximates. However, the issue arises of how to design nonlinear fuzzy control laws. Many fuzzy controllers have been constructed, instead of systematically designed, case by case using the trial-and-error method guided by designers experience on fuzzy control. This approach may be adequate for simple problems. However, for more complex systems such as industrial robot there is an urgent need for fonnal desih'll methods of fuzzy controllers. Fuzzy model reference adaptive control and other adaptive fuzzy control approaches seek to address this issue . The main advantage of the FMRAC is that it implements an adjustable nonlinear mapping between inputs and outputs. Despite the many advantages of the fuzzy model reference adaptive control (FMRAC) algorithm, several drawbacks do exist : The FMRAC design procedure tends to be very