Generalized Predictive Control applied to the DFIG power control using state-space model and voltage constraints

•Proposed Generalized Predictive Control is formulated.•Dual Primal Interior Point Algorithm is used to minimize the cost function.•A tuning method based on pole curves (Similar to root locus) and bode diagram is proposed.•The proposed controller is ported to a Digital Signal Processor, and experimental results are presented to endorse the theory. This paper proposes a Generalized Predictive Control (GPC) for a Doubly Fed Induction Generation (DFIG) applied to wind energy systems. The present controller uses state-space formulation as the prediction model. Additionally, the vector control strategy was used to control stator active and reactive power, and voltage constraints are added due to the computed voltage can exceed the rated value. Furthermore was proposed a methodology to choose GPC parameters based on its analogue closed-loop transfer function. Finally, the predictive controller with constraints is ported to a Digital Signal Processor (DSP) in a test bench, and experimental results are obtained to endorse the proposed theory.