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Optimal Control of Magnetic Bearings for Ultra-high Speed Electrical Motors


Timon Achtnich

Master Thesis, HS12 (10119)

This master's thesis investigates the implementation of model predictive control (MPC) for active magnetic bearings (AMB) in simulation. In the application considered, the AMBs are used in ultrahigh- speed electrical motors with rotational speeds up to 500'000 rpm, suitable for next-generation reaction wheels, for example. Two MPC formulations were proposed, and the performance compared to the state-of-the-art controller. Results show that MPC can reject higher disturbances for a longer period of time, as it produces control responses with less ohmic losses. One of the formulations can achieve a reduction of these losses by 88% in steady state. The resulting MPC optimization problem must be solved within a short sampling period. The solvers Forces and FiOrdOs are used for this task, and optimizations are applied to exploit the problem structure. A speedup of 4.5 was achieved with Forces. The optimizations were implemented directly in the code generator, which makes them also available to other users. FiOrdOs has been optimized with platform-dependent instructions, yielding a speedup of factor 2. With this achievement, the simpler of the two MPC optimization problems can be solved within 52 microseconds on an embedded platform, which shows the real-time feasibility of the proposed formulation.


Type of Publication:

(12)Diploma/Master Thesis

A. Domahidi

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% Autogenerated BibTeX entry
@PhdThesis { Xxx:2013:IFA_4378
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