Masters Degree Dissertations

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12504/87

Browse

Browsing Masters Degree Dissertations by Subject "Disturbance rejection"

Filter results by typing the first few letters
Now showing 1 - 1 of 1
  • Thumbnail Image
    Item
    Modeling and development of a robust vibration suppression control system for piston-type air compressors
    (Kyambogo University (Unpublished work), 2025-08) Nalubega, Jane Frances
    Piston-type air compressors are susceptible to excessive vibrations arising from periodic disturbances, which compromise energy efficiency, induce mechanical wear, and shorten equipment lifespan. Conventional control approaches often lack the robustness required for real-time vibration suppression. This research focuses on the modelling and development of a Disturbance Observer-Based (DOB) control system to actively mitigate such vibrations. A comprehensive dynamic model of the compressor system was formulated, integrating both motor and mechanical dynamics. Based on this model, a DOB control algorithm was designed to estimate and compensate for external disturbances in real time. The control strategy was implemented and evaluated in MATLAB/Simulink through simulation studies under varying disturbance profiles. Simulation results indicated that the DOB-based controller significantly outperformed the traditional feedback control method. Specifically, the proposed controller achieved a 57% reduction in overshoot, decreased the settling time from 0.20 seconds to 0.08 seconds, and demonstrated superior disturbance rejection under both square wave and sinusoidal excitation signals. Additionally, it maintained accurate reference tracking and stable operation under load variability. These results validate the effectiveness of the proposed DOB-based control framework in enhancing the performance, reliability, and operational stability of piston-type air compressors. The developed methodology provides a viable foundation for further experimental validation and real-time industrial deployment.