Dynamic modelling and control of a two-axis gimbal system with model reference adaptive control

Barlas, Ömer Faruk
Providing high-speed and uninterrupted communication has become primary demands of today. Out of the coverage area, it is needed to establish a communication path with the satellites in space. Thus, gimbal systems were developed, that direct the antennas to the satellites with desired position accuracy. Application areas and performance criteria determine the design specifications of gimbal systems. In this study, the gimbal system assembled to the naval platform and used in the orientation and stabilization of a antenna was discussed. In this thesis, a detailed mathematical model was obtained by expressing kinematic relations with Denavit-Hartenberg convention and dynamic relations with Newton-Euler method of a statically-balanced but dynamically-unbalanced two-axis gimbal system. Therefore, a nonlinear equation of motion was obtained, and the system was linearized and expressed in state space representation. According to the system identification tests on physical system, it was realized that the linearized system model has differences due to the modeling uncertainties and the structural flexibility of the mechanical system. The model reference adaptive control (MRAC) method was used by considering these differences in the control system design. Additionally, the control system was developed using the full-state feedback control method that was used both for comparison of the controllers and as reference model in the MRAC method. Further to these control methods, cascaded PI control method, being frequently used in the industry, was developed using a straightforward gimbal model and compared with other methods. Finally, experiments and simulation studies were carried out and the results were examined and discussed.
Citation Formats
Ö. F. Barlas, “Dynamic modelling and control of a two-axis gimbal system with model reference adaptive control,” M.S. - Master of Science, Middle East Technical University, 2023.