Experimentally robustness improvement of DC motor speed control optimization by H-infinity of mixed-sensitivity synthesis

Speed control of DC motor needs excellent robustness to guarantee its function to work properly against uncertainty and disturbance. The uncertainty may occur because of mechatronic component degradation, sensor noise, and environmental effect. Overload and accident have the possibility to be a significant disturbance. The performance of the DC motor is related to its stability and accuracy, which becomes a robust control goal. Robustness is an essential criterion for DC motor applications, from electronic household appliances to electric vehicles. This research aims to improve the robustness of DC motor speed control by H-infinity optimization of mixed-sensitivity synthesis technique to deal with uncertainty and disturbance. Comparison of theoretical modeling of mechatronics principle and experimental identification model is used for finding the best plant model to be processed by mixed-sensitivity synthesis. The proposed controller’s singular values are successfully dropped significantly twice due to robustness improvement from the experimental data. The optimization controller design is robustly stable due to loaded mass as disturbance assessment. The robustness performance improves significantly because the proposed plan has better overshoot errors and smother signal. In addition, the Lyapunov stability assessment on eigenvalues and graphical method proves that the proposed controller design is asymptotically stable. Although the proposed design has significant higher order, it can easily improve DC motor speed control through personal computer (PC)-based control. The calculation of mixed-sensitivity H-infinity control is proven scientifically in this work for the DC motor plant experiment.