Enhancing Gimbal Stabilization Using DMP and Kalman Filter: A Low-Cost Approach with MPU6050 Sensor - Crisnapati, Padma Nyoman; Maneetham, Dechrit; Thwe, Yamin; Aung, Myo Min (International Conference on Cybe and IT Service Management (Online), 2023)
This research explores the application of a 3Degree of Freedom (DOF) gimbal system that utilizes input from the MPU6050 sensor for gimbal stabilization. Maintaining precision and stability in gimbals is of utmost importance, making them a compelling subject in automation controlled by modern controllers. This study involves the implementation of both the Digital Motion Processor (DMP) and Kalman Filter to control gimbal stability, and their performance is compared through simulations. The results demonstrate the superiority of the DMP algorithm, achieving an accuracy rate of 99.3% with an average error of 0.7096, outperforming the Kalman filter, which achieved an accuracy rate of 67.65% with an error of 33.35. The mechanical design of the stabilizer involved manual construction using cardboard and subsequent 3D printing, resulting in a functional system capable of smooth movement. In summary, this study confirms the effectiveness of the DMP algorithm in enhancing sensor data stability and accuracy, thus laying the foundation for low-cost, precise gimbal stabilizer systems.