Akademik Veri Yönetim Sistemi
JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GAZI UNIVERSITY, cilt.40, sa.1, ss.219-236, 2024 (SCI-Expanded)
Purpose: The aim of this study is to achieve desired control performance for a gimbal system under model parameter change and disturbances. Theory and Methods: In this study, PI control, Self-Tuning PI control, Integral Action LQR (IA-LQR) and Relay Sliding Mode Control Based on the Input-Output Model (RSMC-IO) structures are used as speedcontrollers of a gimbal system Results: The PI controller has high performance on the known system model. Its performance decreases when the model parameters change. When the results obtained from both simulation and application of the self-tuning PI controller are analyzed, it is seen that when the system parameters change, the RLS method estimates the changed model parameters and updates the PI controller parameters according to the new system parameters. The controller performance decreases until the RLS method converges sufficiently to the new parameters. IA-LQR maintains its performance against model parameter changes both in simulation and in practice. It is observed that the IA-LQR structure has a system response without overshoot in simulation, but in practice it overshoots by 30%. It is seen that the RSMC-IO structure has a similar response to the specified underlying transfer function response both in simulation and in real system implementation. One of the biggest advantages of this control structure is that it can be used without the need to know the system model, based only on relative degree information, and it can react instantaneously to changes in model parameter changes. Conclusion: The RSMC-IO can react instantaneously to parameter changes and maintains its performance. However, in order to increase the performance of the self-tuning PI controller, the parameters should converge sufficiently. Therefore, it can be said that the RSMC-IO structure is more advantageous against model parameter changes