Sampled control design for linear parameter varying (LPV) systems

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Supervisor:
Dr. Harmati István
Department of Control Engineering and Information Technology

Modeling a nonlinear system in LPV form is very useful for analysis and control synthesis, because the

linear structure makes it possible to formulate the problems as numerically tractable, convex

optimization tasks. When the LPV model is generated from a real, physical system it is naturally

obtained in continuous time. On the other hand, the controller designed for the system has to be

constructed in discrete time in order that it can be implemented on a digital computer. The design of

a discrete time parameter varying controller to a continuous LPV model requires to perform a

discretization (sampling) step at some point of the design process. This can be done either at the

controller side, i.e. a continuous controller is designed and it is discretized, or at the plant side, i.e. the

LPV model is discretized first and then a controller is constructed to a discrete (sampled) model. The

aim of this MSc work is to implement the two approaches with different discretization methods,

compare them in different aspects (computational complexity, required sampling time, control

performance achieved, etc.) and characterize for each the problem setup that the corresponding

approach can solve the best.

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