Adaptive Control of a Permanent Magnet Synchronous Motor for a Robotic Arm under Variable Load

Sammanfattning: The implementation of automated systems in manufacturing industries increases efficiency, precision, and safety by reducing human intervention, errors, and waste. Variable loads can cause several problems for automation systems. One of the most significant challenges is maintaining the stability and precision of the production process despite changing load conditions. These variable loads can lead to unstable systems or failures, causing an increase in errors, reduced efficiency, and lower product quality. It is essential to design control systems that can adapt to changing load conditions and maintain stable and precise operation under all circumstances. To address this problem, this thesis presents an adaptive controller based on load identification and gain scheduling, to replace the standard FOC consisting of regular PI-controllers. The load estimator is used to estimate the external load with relatively small RMSD values, while the ain scheduler adjusts the controller gains based on the estimated load. Other controllers are also explored, such as an angular velocity error-based adaptive controller. The results shows that both proposed controllers perform better than the standard controller when the system is subject to variable external loads, however, the load estimator paired with the gain scheduled PI-controller performs best.