Linear Parameter Varying Control of Induction Motors

The subject of this thesis is the development of linear parameter varying (LPV) controllers and observers for control of induction motors. The induction motor is one of the most common machines in industrial applications. Being a highly nonlinear system, it poses challenging control problems for high performance applications. This thesis demonstrates how LPV control theory provides a systematic way to achieve good performance for these problems. The main contributions of this thesis are the application of the LPV control theory to induction motor control as well as various contributions to the field of LPV control theory itself. Within the last decade the theoretical background for control of LPV systems has been developed. LPV systems constitute a large class of nonlinear systems with a special structure allowing for a systematic approach to controller design. Based on a widely used model of the induction motor and the well-known rotor flux-oriented control scheme, it is demonstrated how LPV methods can be applied to several subproblems in induction motor control. The current equations of the induction motor have a particular structure, which allows them to be written on a complex form. It is shown that for an LPV system with this structure, the optimal controller will also possess this structure. This knowledge can be employed to improve the numerics of the controller synthesis and to reduce the computational burden in the implementation. Viewing the rotational speed as an external parameter, the current equations of the induction motor constitute an LPV system. This is used to design an LPV flux observer. The result is an observer with good performance and very little tuning needed.

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