An H-infinity approach is developed for the problem of nonlinear optimal control of doubly-fed reluctance machines. The dynamic model of the machines is subjected to linearization round local operating points, through Taylor series expansion and the computation of Jacobian matrices. For the linearized model an H-infinity feedback controller is designed, capable of compensating for the modelling error of the approximate linearization as well as for external perturbations affecting the machine. The computation of the feedback control gain is based on the solution of an algebraic Riccati equation that is performed at each iteration of the control algorithm. Lyapunov stability analysis for the control loop of the reluctance machine arrives at an H-infinity tracking performance criterion, and finally the asymptotic stability of the control loop is demonstrated. The excellent tracking performance of the H-infinity control method is confirmed through simulation experiments.

An H-infinity approach to optimal control of doubly-fed reluctance machines

SIANO, PIERLUIGI;
2016-01-01

Abstract

An H-infinity approach is developed for the problem of nonlinear optimal control of doubly-fed reluctance machines. The dynamic model of the machines is subjected to linearization round local operating points, through Taylor series expansion and the computation of Jacobian matrices. For the linearized model an H-infinity feedback controller is designed, capable of compensating for the modelling error of the approximate linearization as well as for external perturbations affecting the machine. The computation of the feedback control gain is based on the solution of an algebraic Riccati equation that is performed at each iteration of the control algorithm. Lyapunov stability analysis for the control loop of the reluctance machine arrives at an H-infinity tracking performance criterion, and finally the asymptotic stability of the control loop is demonstrated. The excellent tracking performance of the H-infinity control method is confirmed through simulation experiments.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4678272
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