Optimize the motion model of overhead crane with accurate estimate the equation of variables state by using Unscented Kalman Filter

چکیده مقاله

In the most dynamical systems, usually all measurement data disturbed by noises, therefore refining and estimating the state variable has attracted the attention of many control engineers in the past few decades. Nowadays, Because of increased use of overhead crane in industry, assess to this crane models is significant. The aim of this article refining and estimate over head crane state variables with noises in order to better control of crane and reduce the cable oscillation in the end and optimize the final approach time. To evaluate the performance of unscented kalman filter (UKF), optimization the state variables dipped in noise by using genetic algorithm in both cases without use of filter and applying filter is our target in this article. And finally we assess the robustness of system by drawing PDF1, CDF2 diagrams.

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