Authors - Udayamoorthy Venkateshkumar Abstract - This paper focus on dual axis solar panel tracking system using Brushless Direct Current motor (BLDC), in which rotor position estimation along azimuthal angle and elevation angle is predicted using incremental en coder. The physical kinematics and dynamics parameters which are non-linear in nature is converted to linear form and processed in conventional estimated kalman filter (EKF) algorithm. The physical process noise covariance value Qk and measured noise covariance value Rk is estimated from conventional EKF predicted value, using sliding window method. Smoothing factor λ is used for quick convergence and tuning factor to estimate the process noise covariance. The simulation is performed using Python and results shows rotor position es timation along azimuthal angle is improved by 50% and 55% along elevation angle. Dual axis estimation error convergence during dynamic tracking along azimuthal angle is reduced by 66% and along elevation angle is reduced by 70% when compared to conventional EKF algorithm.
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