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Low Complexity Model Predictive Control in Power Electronics and Power Systems

Author(s):

T. Geyer
Conference/Journal:

Abstract:

This thesis focuses on Model Predictive Control (MPC) of discrete-time linear hybrid systems. Hybrid systems contain continuous and discrete valued components, and are located at the intersection between the fields of control theory and computer science. The first part of the thesis is devoted to theory and algorithms. For a given polyhedral piecewise affine system, we solve the problem of deriving an equivalent representation that is minimal in the number of polyhedra by using the notion of hyperplane arrangement and Boolean minimization. Moreover, we propose an algorithm that efficiently enumerates all feasible modes of a composition of hybrid systems. This allows the evaluation of the complexity of the composition, the efficient translation of the model into a piecewise affine representation (starting from a high-level textual description), the reduction of the computational burden of optimal control schemes by pruning infeasible modes, and the evaluation of well-posedness. In the second part of the thesis, we consider three applications. For the Direct Torque Control (DTC) problem of two-level and three-level inverters driving three-phase induction motors, we propose hybrid models and MPC schemes tailored to the DTC problem. These schemes do not require any tuning, are applicable to any drive, are of low complexity, and most importantly allow for improving the control performance (switching frequency) by up to 50 per cent with respect to the industrial state-of-the-art. For fixed frequency switch-mode DC-DC converters, we derive an optimal state-feedback control law that guarantees stability for the whole state-space and rejects gross disturbances in the input voltage and the load resistance. Last, we tackle the emergency voltage control problem in power systems using MPC and a hybrid modelling approach.

Year:

2005
Type of Publication:

(03)Ph.D. Thesis
Supervisor:



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% Autogenerated BibTeX entry
@PhDThesis { Xxx:2005:IFA_2124,
    author={T. Geyer},
    title={{Low Complexity Model Predictive Control in Power
	  Electronics and Power Systems}},
    school={},
    year={2005},
    address={},
    month=mar,
    url={http://control.ee.ethz.ch/index.cgi?page=publications;action=details;id=2124}
}
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