The magnetic levitation system is a typical system with many successful applications in practice. Due to the inherent instability and strong open-loop nonlinearity of the MLS, a controller is used to control the stabi...
The magnetic levitation system is a typical system with many successful applications in practice. Due to the inherent instability and strong open-loop nonlinearity of the MLS, a controller is used to control the stability of the magnetic levitation system. With the rapid development of embedded systems, the intelligent digital control has begun to replace conventional analog control technology creating a new approach to the control MLS. This paper proposes a hardware module for the MLS based on a digital signal processor combined with a fast acting controller to ensure system stability even with incomplete mathematical models. The simulation and experimental results are compared with the linearized feedback control law. Finally, experiments are carried out to test the practical feasibility of the proposed control laws in the MLS embedded control system. The system, with the recommended controller, well responds to the tolerances allowing for stable system working. Both simulation and test results are included in this paper to show that the fast acting suboptimal controller has the advantage of being more durable and less complicated to perform in MLS control applications.
Many important characteristics of simulation models, including queuing models, can be investigated by the use of metamodels. Problems in qualitative analysis such as analyzing model dynamics and coming to a careful un...
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Many important characteristics of simulation models, including queuing models, can be investigated by the use of metamodels. Problems in qualitative analysis such as analyzing model dynamics and coming to a careful understanding of model behavior can be dealt with this way. Metamodels can provide precise results even for quantitative analysis tasks, such as those involving the movement of dynamic model elements. This paper describes the use of a type of metamodeling to support the assessment of simulation models based on the analysis of trace files produced at the time of model execution. Because of the simple structure of these trace files, a simulation model can create them easily. The analysis and interpretation of trace files that is described here is independent of the simulation language used to create the original model. The tools presented in this article can be used for these purposes: to construct generic model structures at the metamodel level and then animate aspects of model behavior in terms of these structures; to build a graphic display indicating which dynamic model elements moved at which times between which points in the model, and in which real-time order in cases of time ties; to determine when (and if) user-specified model conditions come about; and to develop statistical information that might not have been planned for in the design of the original model. Future plans call for making these tools available in a World Wide Web environment to support assessment of simulation models.
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