Abstract
The electromagnetic levitation (EML) system serves as a key subsystem in maglev trains for the purpose of levitation. It is highly dynamic, open-loop unstable, and safety-critical. The expense of establishing an accurate model out of the Maglev train, in addition to the varying operating conditions, results in an imperfectly known model in engineering practice. Thus high-performance levitation control, w.r.t. an imperfectly known model, is of considerable practical interest. Motivated by such an observation, this article investigates real-time levitation performance optimization of the EML system, with an imperfectly known model. The EML system is first modeled and an equivalent demonstration benchmark is developed. Then, the structure for levitation performance optimization is presented on top of the coprime factorization technique. Furthermore, the real-time levitation performance optimization algorithm is developed, utilizing only the input and output data. In the end, the proposed methods are validated on the benchmark.
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