-Recently, the demand of maglev systems in the manufacturing industry for LCD and OLED display panels, which are required to be very clean and possess vacuum systems, has been increasing due to their characteristics such as being non-contact, noise free and eco-friendly. However, it is still a challenge to simultaneously control both the propulsion and levitation for their interactive effect difficult to be exactly measured. In this paper, we proposed a new tuning method for controlling the magnetic levitation force robustly against the levitation disturbance caused by a propulsion system, based on LQ servo optimal control. The disturbance torque of the LSM propulsion system is calculated through FEM analysis in such a way that the LQ servo controller is determined in order to minimize the effect of the disturbance. The robust performance of the proposed LQ servo control method for the in-track type magnetic levitation systems is demonstrated via simulations and experiments.
-This paper proposed a new real-time parameter tracking algorithm. Unlike the convenience algorithms, the proposed real-time parameter tracking algorithm can estimate parameters through three-phase voltage and electric current without coordination transformation, and does not need information on magnetic flux. Therefore, it can estimate parameters regardless of the change according to operation point and cross-saturation effect. In addition, as the quasi-real-time parameter tracking technique can estimate parameters through the four fundamental arithmetic operations instead of complicated algorithms such as numerical value analysis technique and observer design, it can be applied to low-performance DSP. In this paper, a new real-time parameter tracking algorithm is derived from three phase equation. The validity and usefulness of the proposed inductance estimation technique is verified by simulation and experimental results.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.