State Estimation of a Crane Using Fuzzy UHF

These days overhead crane is widely used in different industries such as automobile, navigation and also transportation of tools in storerooms. In this paper, a new adaptive strategy of Kalman Filter based on Fuzzy logic in which it tunes the process noise covariance matrix Q is presented. The method proposed attempts to offset some of the assumptions made in UHF formulation and is also robust with respect to the nonlinearities in the dynamic system subjected to non-stationary noises. The matrix Q influences the Kalman gain matrix K and thus, tuning the covariance matrix in-turn amounts to tuning K, thereby improving the filter’s performance. Also this paper considers an important application the state estimation of a Crane, which dynamics are highly nonlinear and the noises affecting it are non-stationary.