Research On Finite Control-Set Model Predictive Control For Active Front-End Converters

With the soaring demand for energy sources,the quality of the electrical energy has received increasing attention in recent years.It has become a popular research topic by employing the power electronic equipment in order to realize high-quality electrical energy conversion.Active front-end converters(AFEs)are commonly used as an interface between grid and electronic equipments.In this sense,its control performance will directly affect the quality of electrical energy conversion.Therefore,considering the high-performance control of the AFEs is of great practical significance.The main contributions of this dissertation are summarized as follows:1)The conventional finite control set model predictive control(FCS-MPC)method has a large amount of calculation effort,which will result in the time delay of control command.To solve this,two simplified FCS-MPC strategies for AFEs are presented to reduce the online calculation effort based on deadbeat predictive control and Lyapunov principle,respectively.In the proposed methods,a sector distribution method based on space vector modulation(SVM)technique is introduced into the controller design.Thus,since the proposed strategy avoids exhaustive explorations for testing all feasible voltage vectors,the optimizing efficiency can be improved.2)Due to the fact that the inductor manufacturing tolerance,temperature,operating point,etc.,make the actual inductance value different from the rated value.This will deteriorate the control performance of system,and trigger instability issues for the conventional FCS-MPC method.To solve this,an online parameter identification technique based on model reference adaptive system(MRAS)estimation theory is proposed by introducing the FCS-MPC scheme for AFEs.Thus,the proposed controller can mitigate the performance degradation caused by the model parameter mismatch.3)In traditional FCS-MPC method,the use of proportional integral(PI)controller will result in the integrator windup phenomenon.This will affect the dynamic performance of the control system.Meanwhile,a main problem of the traditional PI controller is its sensitivity to the system uncertainties.To solve this,a novel control strategy for AFEs is presented by combining the proposed FCS-MPC method with a dynamic references design concept.This strategy avoids the using of external PI controller without any integrator windup phenomenon.Furthermore,the number of predicted voltage vectors can be reduced by using the simplified FCS-MPC method,and the dynamic performance can be improved.4)In the traditional FCS-MPC method,the high switching frequency will account for unnecessary energy loss from power semiconductors,which directly affect efficiency.In order to solve this issue,a low(FFCS-MPC)method for AFEs is proposed.In the proposed method,a hysteresis switching frequency fuzzy FCS-MPC technique is employed,and a fuzzy logic control is introduced.By using the proposed FFCS-MPC scheme,the switching frequency can be reduced,and the system dynamic performance can be enhanced while remaining computationally feasible.5)In the conventional FCS-MPC method,the selection of the weighting factor is a difficult task.To solve this,a simplified multi-objective-optimization-based FCS-MPC method for AFEs is proposed.More specifically,by using the multi-objective ranking method and the multi-objective fuzzy-decision-making(MOFDM)method,the selection of weighting factors can be avoided,and the online calculation burden can be reduced.