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

Author(s):

Timon Achtnich
Conference/Journal:

Master Thesis, HS12 (10119)
Abstract:

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.

Year:

2013
Type of Publication:

(12)Diploma/Master Thesis
Supervisor:

A. Domahidi

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