CN111682791B - Two-stage finite set model prediction control method - Google Patents

Two-stage finite set model prediction control method Download PDF

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CN111682791B
CN111682791B CN202010581607.9A CN202010581607A CN111682791B CN 111682791 B CN111682791 B CN 111682791B CN 202010581607 A CN202010581607 A CN 202010581607A CN 111682791 B CN111682791 B CN 111682791B
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CN111682791A (en
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王宇
王贵峰
朱拓基
王远
买迪尼古力·阿不都赛米
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Jiangsu Normal University
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02M—APPARATUS FOR CONVERSION BETWEEN AC AND AC, BETWEEN AC AND DC, OR BETWEEN DC AND DC, AND FOR USE WITH MAINS OR SIMILAR POWER SUPPLY SYSTEMS; CONVERSION OF DC OR AC INPUT POWER INTO SURGE OUTPUT POWER; CONTROL OR REGULATION THEREOF
    • H02M7/00—Conversion of ac power input into dc power output; Conversion of dc power input into ac power output
    • H02M7/42—Conversion of dc power input into ac power output without possibility of reversal
    • H02M7/44—Conversion of dc power input into ac power output without possibility of reversal by static converters
    • H02M7/48—Conversion of dc power input into ac power output without possibility of reversal by static converters using discharge tubes with control electrode or semiconductor devices with control electrode
    • H02M7/483—Converters with outputs that each can have more than two voltages levels
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02M—APPARATUS FOR CONVERSION BETWEEN AC AND AC, BETWEEN AC AND DC, OR BETWEEN DC AND DC, AND FOR USE WITH MAINS OR SIMILAR POWER SUPPLY SYSTEMS; CONVERSION OF DC OR AC INPUT POWER INTO SURGE OUTPUT POWER; CONTROL OR REGULATION THEREOF
    • H02M1/00—Details of apparatus for conversion
    • H02M1/0048—Circuits or arrangements for reducing losses
    • H02M1/0054—Transistor switching losses
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B70/00—Technologies for an efficient end-user side electric power management and consumption
    • Y02B70/10—Technologies improving the efficiency by using switched-mode power supplies [SMPS], i.e. efficient power electronics conversion e.g. power factor correction or reduction of losses in power supplies or efficient standby modes

Abstract

The invention provides a two-segment finite set model prediction control method, which comprises the steps of firstly, selecting a first vector of a prediction period as a second switching vector acted by an upper period, and reducing switching loss without switching at the initial moment of each sampling period, namely, each sampling period acts on two switching vectors but only has one switching; secondly, respectively calculating corresponding action time when the first switching vector and all effective switching vectors are combined differently according to the principle that the action time of the switching vector is in inverse proportion to the action error; and finally, according to the action time corresponding to different switch combinations, performing two-stage current output prediction, and selecting a group of switch combinations with the best current following performance as the final output of the system, thereby determining the second switch vector of the prediction period and the action time corresponding to the two vectors respectively.

Description

Two-stage finite set model prediction control method
Technical Field
The invention belongs to the technical field of two-level inverter control, and particularly relates to a two-section type finite set model prediction control method.
Background
The FCS-MPC (finite control set model predictive control) technology has the advantages of intuitive modeling, simple control, realization of multi-target optimization control, no PWM (pulse width modulation) modulator, no PI (proportional-integral) parameter adjustment and the like, and has become the main research direction of the inverter control strategy. The traditional single vector FCS-MPC method selects an optimal switching vector based on the principle of minimum current tracking error, the selected optimal switching vector acts on an inverter at the beginning moment of the next control period and acts on a complete period, and therefore the traditional single vector model predictive control method has the defects of high harmonic distortion rate, large current ripple and the like. Therefore, the invention provides a two-stage finite set model prediction control method.
Disclosure of Invention
The purpose of the invention is as follows: the invention provides a two-stage finite set model prediction control method, which aims to solve the problems of high harmonic distortion rate, large current ripple and the like when a traditional single vector FCS-MPC acts on a two-level inverter.
The core of the two-segment finite set model prediction control method provided by the invention is to provide a method for determining two switch vectors in each control period by the two-segment finite set model prediction control and a corresponding method for calculating the action time: (1) the second switching vector selected in the K-1 period is used as the first switching vector in the K +1 period, so that switching is guaranteed to be performed at most once in one sampling period, switching loss of two-stage finite set model predictive control is reduced, and switching loss is guaranteed to be basically equivalent to that of a traditional single vector method on the premise of improving current control performance. (2) The second switching vector is selected from all effective vectors of the inverter, and corresponding action time of the first switching vector and all effective switching vectors in different combinations is respectively calculated according to the principle that the action time of the switching vector is in inverse proportion to the action error; and then, according to the action time corresponding to different switch combinations, respectively carrying out two-section type current output prediction, and selecting the switch combination which enables the evaluation function value to be minimum, namely selecting a group of switch combinations with the best current following performance as the final output of the system, thereby determining the selection of a second switch vector and the action time corresponding to the two vectors respectively.
The technical scheme is as follows: in order to achieve the purpose, the invention discloses a two-stage finite set model prediction control method, which comprises the following steps:
(1) for tkSampling the output current of the inverter at any time to obtain the actual current value [ iα(tk),iβ(tk)]The subscripts alpha and beta refer to the two-phase stationary coordinate system alpha-beta coordinate system, iα(tk) Is the actual value of the K period starting time of the alpha coordinate axis iβ(tk) For the actual value of the K period starting time of a beta coordinate axis, two switching vectors selected in the K-1 period act on an inverter in the K period, and the first vector acts on t1(K) Time, second vector contribution t2(K) Time, performing control delay compensation, and calculating compensated t according to the prediction modelk+1Predicting a current value at a moment;
(2) applying the K period to a second switching vector S of the inverter2(K) First switching vector S selected as the period K +11(K +1) and calculating the vector action over the control period TsAn inverter output current error value;
(3) performing a full period T on all the active vectors of two levelssThe prediction operation of (2) calculating action error according to the evaluation function, and calculating action time t respectively when the first switching vector is combined with all effective vectors of the inverter according to the principle that the action time is in inverse proportion to the action error1(i),t2(i),i＝1,2.....8，t1(i) The action time of the first switching vector when the first switching vector of the K +1 period is combined with all effective vectors of the inverter, t2(i) The action time corresponding to each effective vector is the action time when the first switching vector in the K +1 period is combined with all effective vectors of the inverter;
(4) according to the action time t corresponding to different switch combinations obtained in the step (3)1(i),t2(i) I 1,2.. 8, a prediction operation is first performed on a first switching vector in a K +1 cycle, and the first switching vector is acted on by t1(i) Time, obtaining a predicted value of output current at the action ending moment; secondly, the first switching vector acts on t in the period of K +11(i) The predicted current value at the end time is taken as an initial value, and the inverter effective vector acts on t according to different combinations of the first vector and the inverter effective vector in the step (3)2(i) Calculating to obtain the predicted value of the output current at the end moment of the K +1 period, realizing two-stage model prediction control, obtaining the error value of the output current according to the evaluation function, selecting a group of switch combinations with the best current following performance, namely the minimum error value as two switch vectors to be acted on by the K +1 period, wherein the effective vector in the combination is the second switch vector S of the K +1 period2(K +1) outputting a second switching vector of the K +1 period and action time corresponding to the two switching vectors in the switching combination respectively;
(5) the process is repeated for the next control cycle.
Further, the method of the step (1) is specifically as follows:
(1.1) to tkSampling the output current of the inverter at any time to obtain the actual current value [ iα(tk),iβ(tk)]The subscripts alpha and beta refer to the two-phase stationary coordinate system alpha-beta coordinate system, iα(tk) Is the actual value of the K period starting time of the alpha coordinate axis iβ(tk) Is the actual value of the K period starting time of the beta coordinate axis; two switching vectors selected in the period of K-1 are applied to the inverter, and the first vector is applied to t1(K) Time, second vector contribution t2(K) Time of which S1(K)＝(S1a(K),S1b(K),S1c(K))，S2(K)＝(S2a(K),S2b(K),S2c(K) K denotes the kth period, subscript 1 denotes the first switching vector of the K period, subscript 2 denotes the second switching vector of the K period, subscripts a, b, c denote the three-phase bridge arm of the inverter, S1a(K)，S1b(K)，S1c(K) Respectively a phase a, a phase b, a phase c of the K period2a(K)，S2b(K)，S2c(K) Second switching vectors of a phase, b phase and c phase of the K period are respectively;
(1.2) time delay compensation, applying the first switching vector S of the K period according to a two-level inverter system prediction model1(K) Acting on the inverter to calculate the vector action t1(K) Predicted value of current i after time1(t1) Wherein i is1(t1)＝[i1α(t1),i1β(t1)]；
(1.3) applying a second switching vector S2(K) And with i1(t1) As a second switching vector, the actual value of the current prediction calculation is output to obtain S2(K) Action t2(K) T after timek+1Time current prediction value
Figure BDA0002552509770000031
The FCS-MPC system with the two-level inverter having the resistance-inductance load comprises a first switching vector output current calculation prediction model:
Figure BDA0002552509770000032
the second switching vector output current calculation prediction model:
Figure BDA0002552509770000033
in the formula (I), the compound is shown in the specification,
Figure BDA0002552509770000034
r, L is the resistance and inductance of the load, E is half the DC side voltage, the superscript p indicates the model prediction value,
Figure BDA0002552509770000035
is tk+1The time alpha axis predicts the current value,
Figure BDA0002552509770000036
is tk+1Prediction of current value, i, on the axis of time beta1α(t1) Acting on the first switching vector t for the K period1(K) Predicted value of current of alpha coordinate axis after time, i1β(t1) Acting on the first switching vector t for the K period1(K) Predicted value of beta coordinate axis current after time, t1(K) Time of action of the first vector, t2(K) For the first vector action time, I is the cell matrix.
Further, the method of the step (2) is specifically as follows: second switching vector S to which K periods are applied2(K)＝(S2a(K),S2b(K),S2c(K) As the first switching vector S of the K +1 cycle1(K+1)＝(S1a(K+1),S1b(K+1),S1c(K +1)), and calculates the vector action over the control period TsRear inverter output current i0And an output current error value g0Wherein i0＝[i0α,i0β]；
Output current prediction model:
Figure BDA0002552509770000037
in the formula (I), the compound is shown in the specification,
Figure BDA0002552509770000038
r, L is the resistance and inductance of the load, E is half of the DC side voltage, TsI is a unit matrix;
calculating an output current error:
Figure BDA0002552509770000039
wherein the indices are given reference values,
Figure BDA0002552509770000041
a current reference value is given for the alpha-beta coordinate system,
Figure BDA0002552509770000042
acting the first switching vector for the K +1 period on the entire control period TsAfter tk+2The time alpha axis predicts the current value,
Figure BDA0002552509770000043
acting the first switching vector for the K +1 period on the entire control period TsAfter tk+2The time β coordinate axis predicts the current value.
Further, the method of the step (3) is specifically as follows:
(4.1) complete period T is carried out on all the effective vectors of two levelssAccording to the evaluation function, calculating the action error value g of all effective switching vectors of the inverter i1,2.. 8, the evaluation function is as follows:
Figure BDA0002552509770000044
wherein the indices are given reference values,
Figure BDA0002552509770000045
a current reference value is given for the alpha-beta coordinate system,
Figure BDA0002552509770000046
acting the entire control period T on the K +1 period effective vectorsAfter tk+2The time alpha axis predicts the current value,
Figure BDA0002552509770000047
acting the entire control period T on the K +1 period effective vectorsAfter tk+2Predicting a current value by a coordinate axis of time beta;
(4.2) calculating the action time t corresponding to different combinations of the first switching vector and the effective vector according to the principle that the action time is in inverse proportion to the action error1(i),t2(i) 1,2.. 8, the calculation formula is as follows:
Figure BDA0002552509770000048
in the formula, TSTo control the period, g0For the current error value at the first switching vector action of each control cycle, giApplying an error value, t, to the active vector of a two-level inverter1(i),t2(i) Two vector action times, respectively.
Further, the method of the step (4) is specifically as follows:
(5.1) according to the action time t respectively corresponding to the two vectors in different switch combinations and combinations obtained in the step (3)1(i),t2(i) I 1,2.. 8, a prediction operation is first performed on a first switching vector in a prediction period, and the first switching vector is applied to t1(i) Time to obtain predicted value i of output current at action end time1(t1(i) Wherein i) are1(t1(i))＝[i1α(t1(i)),i1β(t1(i))]；
The first switching vector output current calculation prediction model:
Figure BDA0002552509770000049
in the formula (I), the compound is shown in the specification,
Figure BDA00025525097700000410
r, L is the resistance and inductance of the load, E is half of the DC side voltage, t1(i) For the first vector action time, I is the cell matrix.
(5.2) acting on t with the first switching vector of the prediction cycle1(i) Predicted end time current value i1(t1(i) ) applying a second switching vector in different combinations in step (3) as a starting value and applying t2(i) Time, calculating the predicted value of the output current in the K +1 period, and realizing two-section type model prediction control;
the second switching vector output current calculation prediction model:
Figure BDA0002552509770000051
in the formula (I), the compound is shown in the specification,
Figure BDA0002552509770000052
r, L is the resistance and inductance of the load, E is half of the DC side voltage, t2(i) Is the second vector action time, I is the cell matrix;
(5.3) calculating an output current error value, wherein the error calculation formula is as follows:
Figure BDA0002552509770000053
wherein the indices are given reference values,
Figure BDA0002552509770000054
a current reference value is given for the alpha-beta coordinate system,
Figure BDA0002552509770000055
predicting the end time t of the K +1 period for the two-segment model under the alpha-beta coordinate systemk+2Outputting a current predicted value at any moment;
selecting a group of switch combinations with best current following performance, namely, the smallest error value as two switch vectors to be acted on in the K +1 period according to the formula (9), wherein the effective vector in the combination is the second switch vector S in the K +1 period2(K +1), outputting the second switching vector of the K +1 period and the action time corresponding to the two switching vectors in the switching combination.
Has the advantages that: compared with the prior art, the technical scheme of the invention has the following beneficial technical effects:
(1) the method realizes that one control period acts on two switching vectors but only has one switching at most, thereby reducing the switching loss of two-segment type finite set model prediction control.
(2) The current following performance is improved, the harmonic distortion rate of the output current of the two-level inverter is reduced, and the output current ripple is reduced.
Drawings
FIG. 1 is a flow chart of a two-stage finite set model predictive control method;
FIG. 2 is a schematic diagram of a two-stage finite set model predictive control method;
FIG. 3 is an effect diagram of a two-stage finite set model prediction control method.
Detailed Description
The invention is further explained by a two-stage FCS-MPC control of a two-level inverter with a resistive load, which comprises the following steps:
a two-stage finite set model prediction control method comprises the following steps:
(1) for tkSampling the output current of the inverter at any time to obtain the actual current value [ iα(tk),iβ(tk)]The subscripts alpha and beta refer to the two-phase stationary coordinate system alpha-beta coordinate system, iα(tk) Is the actual value of the K period starting time of the alpha coordinate axis iβ(tk) Is beta coordinate axis K cyclesThe actual value of the starting time of the period is that two switching vectors selected in the K-1 period act on the inverter in the K period, and the first vector acts on t1(K) Time, second vector contribution t2(K) Time, performing control delay compensation, and calculating compensated t according to the prediction modelk+1Predicting a current value at a moment;
(2) applying the K period to a second switching vector S of the inverter2(K) First switching vector S selected as the period K +11(K +1) and calculating the vector action over the control period TsAn inverter output current error value;
(3) performing a full period T on all the active vectors of two levelssThe prediction operation of (2) calculating action error according to the evaluation function, and calculating action time t respectively when the first switching vector is combined with all effective vectors of the inverter according to the principle that the action time is in inverse proportion to the action error1(i),t2(i),i＝1,2.....8，t1(i) The action time of the first switching vector when the first switching vector of the K +1 period is combined with all effective vectors of the inverter, t2(i) The action time corresponding to each effective vector is the action time when the first switching vector in the K +1 period is combined with all effective vectors of the inverter;
(4) according to the action time t corresponding to different switch combinations obtained in the step (3)1(i),t2(i) I 1,2.. 8, a prediction operation is first performed on a first switching vector in a K +1 cycle, and the first switching vector is acted on by t1(i) Time, obtaining a predicted value of output current at the action ending moment; secondly, the first switching vector acts on t in the period of K +11(i) The predicted current value at the end time is taken as an initial value, and the inverter effective vector acts on t according to different combinations of the first vector and the inverter effective vector in the step (3)2(i) Calculating to obtain the predicted value of the output current at the end moment of the K +1 period, realizing two-stage model prediction control, obtaining the error value of the output current according to the evaluation function, selecting a group of switch combinations with the best current following performance, namely the minimum error value as two switch vectors to be acted on by the K +1 period, wherein the effective vector in the combination is the second switch vector S of the K +1 period2(K+1) Outputting a second switching vector of the K +1 period and action time corresponding to the two switching vectors in the switching combination respectively;
(5) the process is repeated for the next control cycle.
Further, the method of the step (1) is specifically as follows:
(1.1) to tkSampling the output current of the inverter at any time to obtain the actual current value [ iα(tk),iβ(tk)]The subscripts alpha and beta refer to the two-phase stationary coordinate system alpha-beta coordinate system, iα(tk) Is the actual value of the K period starting time of the alpha coordinate axis iβ(tk) Is the actual value of the K period starting time of the beta coordinate axis; two switching vectors selected in the period of K-1 are applied to the inverter, and the first vector is applied to t1(K) Time, second vector contribution t2(K) Time of which S1(K)＝(S1a(K),S1b(K),S1c(K))，S2(K)＝(S2a(K),S2b(K),S2c(K) K denotes the kth period, subscript 1 denotes the first switching vector of the K period, subscript 2 denotes the second switching vector of the K period, subscripts a, b, c denote the three-phase bridge arm of the inverter, S1a(K)，S1b(K)，S1c(K) Respectively a phase a, a phase b, a phase c of the K period2a(K)，S2b(K)，S2c(K) Second switching vectors of a phase, b phase and c phase of the K period are respectively;
(1.2) time delay compensation, applying the first switching vector S of the K period according to a two-level inverter system prediction model1(K) Acting on the inverter to calculate the vector action t1(K) Predicted value of current i after time1(t1) Wherein i is1(t1)＝[i1α(t1),i1β(t1)]；
(1.3) applying a second switching vector S2(K) And with i1(t1) As a second switching vector, the actual value of the current prediction calculation is output to obtain S2(K) Action t2(K) T after timek+1Time current prediction value
Figure BDA0002552509770000071
The FCS-MPC system with the two-level inverter having the resistance-inductance load comprises a first switching vector output current calculation prediction model:
Figure BDA0002552509770000072
the second switching vector output current calculation prediction model:
Figure BDA0002552509770000073
in the formula (I), the compound is shown in the specification,
Figure BDA0002552509770000074
r, L is the resistance and inductance of the load, E is half the DC side voltage, the superscript p indicates the model prediction value,
Figure BDA0002552509770000076
is tk+1The time alpha axis predicts the current value,
Figure BDA0002552509770000075
is tk+1Prediction of current value, i, on the axis of time beta1α(t1) Acting on the first switching vector t for the K period1(K) Predicted value of current of alpha coordinate axis after time, i1β(t1) Acting on the first switching vector t for the K period1(K) Predicted value of beta coordinate axis current after time, t1(K) Time of action of the first vector, t2(K) For the first vector action time, I is the cell matrix.
Further, the method of the step (2) is specifically as follows: second switching vector S to which K periods are applied2(K)＝(S2a(K),S2b(K),S2c(K) As the first switching vector S of the K +1 cycle1(K+1)＝(S1a(K+1),S1b(K+1),S1c(K +1)), and calculating the vector contributionThe whole control period TsRear inverter output current i0And an output current error value g0Wherein i0＝[i0α,i0β]；
Output current prediction model:
Figure BDA0002552509770000081
in the formula (I), the compound is shown in the specification,
Figure BDA0002552509770000082
r, L is the resistance and inductance of the load, E is half of the DC side voltage, TsI is a unit matrix;
calculating an output current error:
Figure BDA0002552509770000083
wherein the indices are given reference values,
Figure BDA0002552509770000084
a current reference value is given for the alpha-beta coordinate system,
Figure BDA0002552509770000085
acting the first switching vector for the K +1 period on the entire control period TsAfter tk+2The time alpha axis predicts the current value,
Figure BDA0002552509770000086
acting the first switching vector for the K +1 period on the entire control period TsAfter tk+2The time β coordinate axis predicts the current value.
Further, the method of the step (3) is specifically as follows:
(4.1) complete period T is carried out on all the effective vectors of two levelssAccording to the evaluation function, calculating the action error value g of all effective switching vectors of the inverter i1,2.. 8, evaluationThe cost function is as follows:
Figure BDA0002552509770000087
wherein the indices are given reference values,
Figure BDA0002552509770000088
a current reference value is given for the alpha-beta coordinate system,
Figure BDA0002552509770000089
acting the entire control period T on the K +1 period effective vectorsAfter tk+2The time alpha axis predicts the current value,
Figure BDA00025525097700000810
acting the entire control period T on the K +1 period effective vectorsAfter tk+2Predicting a current value by a coordinate axis of time beta;
(4.2) calculating the action time t corresponding to different combinations of the first switching vector and the effective vector according to the principle that the action time is in inverse proportion to the action error1(i),t2(i) 1,2.. 8, the calculation formula is as follows:
Figure BDA00025525097700000811
in the formula, TSTo control the period, g0For the current error value at the first switching vector action of each control cycle, giApplying an error value, t, to the active vector of a two-level inverter1(i),t2(i) Two vector action times, respectively.
Further, the method of the step (4) is specifically as follows:
(5.1) according to the action time t respectively corresponding to the two vectors in different switch combinations and combinations obtained in the step (3)1(i),t2(i) I 1,2.. 8, a prediction operation is first performed on a first switching vector in a prediction period, and the first switching vector is applied to t1(i)Time to obtain predicted value i of output current at action end time1(t1(i) Wherein i) are1(t1(i))＝[i1α(t1(i)),i1β(t1(i))]；
The first switching vector output current calculation prediction model:
Figure BDA0002552509770000091
in the formula (I), the compound is shown in the specification,
Figure BDA0002552509770000092
r, L is the resistance and inductance of the load, E is half of the DC side voltage, t1(i) For the first vector action time, I is the cell matrix.
(5.2) acting on t with the first switching vector of the prediction cycle1(i) Predicted end time current value i1(t1(i) ) applying a second switching vector in different combinations in step (3) as a starting value and applying t2(i) Time, calculating the predicted value of the output current in the K +1 period, and realizing two-section type model prediction control;
the second switching vector output current calculation prediction model:
Figure BDA0002552509770000093
in the formula (I), the compound is shown in the specification,
Figure BDA0002552509770000094
r, L is the resistance and inductance of the load, E is half of the DC side voltage, t2(i) Is the second vector action time, I is the cell matrix;
(5.3) calculating an output current error value, wherein the error calculation formula is as follows:
Figure BDA0002552509770000095
wherein the indices are given reference values,
Figure BDA0002552509770000096
a current reference value is given for the alpha-beta coordinate system,
Figure BDA0002552509770000097
predicting the end time t of the K +1 period for the two-segment model under the alpha-beta coordinate systemk+2Outputting a current predicted value at any moment;
selecting a group of switch combinations with best current following performance, namely, the smallest error value as two switch vectors to be acted on in the K +1 period according to the formula (9), wherein the effective vector in the combination is the second switch vector S in the K +1 period2(K +1), outputting the second switching vector of the K +1 period and the action time corresponding to the two switching vectors in the switching combination.
FIG. 1 is a flow chart of a two-stage FCS-MPC control method. FIG. 2 is a schematic diagram of a two-stage FCS-MPC. Fig. 3 shows the application effect of two-stage finite set model prediction control in a two-level inverter, (a) shows the output current waveform of the two-level inverter; (b) outputting a voltage waveform for the two-level inverter; (c) for the harmonic analysis of the output current waveform, it can be known from the figure that the two-segment finite set model predictive control can effectively reduce the harmonic distortion rate.

Claims (5)

1. A two-stage finite set model prediction control method is characterized by comprising the following steps:
(1) for tkSampling the output current of the inverter at any time to obtain the actual current value [ iα(tk),iβ(tk)]The subscripts alpha and beta refer to the two-phase stationary coordinate system alpha-beta coordinate system, iα(tk) Is the actual value of the K period starting time of the alpha coordinate axis iβ(tk) For the actual value of the K period starting time of a beta coordinate axis, two switching vectors selected in the K-1 period act on an inverter in the K period, and the first vector acts on t1(K) Time, second vector contribution t2(K) Time, performing control delay compensation, and calculating compensated t according to the prediction modelk+1Predicting a current value at a moment;
(2) applying the K period to a second switching vector S of the inverter2(K) First switching vector S selected as the period K +11(K +1) and calculating the vector action over the control period TsAn inverter output current error value;
(3) performing a full period T on all the active vectors of two levelssThe prediction operation of (2) calculating action error according to the evaluation function, and calculating action time t respectively when the first switching vector is combined with all effective vectors of the inverter according to the principle that the action time is in inverse proportion to the action error1(i),t2(i),i＝1,2.....8，t1(i) The action time of the first switching vector when the first switching vector of the K +1 period is combined with all effective vectors of the inverter, t2(i) The action time corresponding to each effective vector is the action time when the first switching vector in the K +1 period is combined with all effective vectors of the inverter;
(4) according to the action time t corresponding to different switch combinations obtained in the step (3)1(i),t2(i) I 1,2.. 8, a prediction operation is first performed on a first switching vector in a K +1 cycle, and the first switching vector is acted on by t1(i) Time, obtaining a predicted value of output current at the action ending moment; secondly, the first switching vector acts on t in the period of K +11(i) The predicted current value at the end time is taken as an initial value, and the inverter effective vector acts on t according to different combinations of the first vector and the inverter effective vector in the step (3)2(i) Calculating to obtain the predicted value of the output current at the end moment of the K +1 period, realizing two-stage model prediction control, obtaining the error value of the output current according to the evaluation function, selecting a group of switch combinations with the best current following performance, namely the minimum error value as two switch vectors to be acted on by the K +1 period, wherein the effective vector in the combination is the second switch vector S of the K +1 period2(K +1) outputting a second switching vector of the K +1 period and action time corresponding to the two switching vectors in the switching combination respectively;
(5) the process is repeated for the next control cycle.
2. The two-stage finite set model predictive control method according to claim 1, wherein the method of step (1) is as follows:
(1.1) to tkSampling the output current of the inverter at any time to obtain the actual current value [ iα(tk),iβ(tk)]The subscripts alpha and beta refer to the two-phase stationary coordinate system alpha-beta coordinate system, iα(tk) Is the actual value of the K period starting time of the alpha coordinate axis iβ(tk) Is the actual value of the K period starting time of the beta coordinate axis; two switching vectors selected in the period of K-1 are applied to the inverter, and the first vector is applied to t1(K) Time, second vector contribution t2(K) Time of which S1(K)＝(S1a(K),S1b(K),S1c(K))，S2(K)＝(S2a(K),S2b(K),S2c(K) K denotes the kth period, subscript 1 denotes the first switching vector of the K period, subscript 2 denotes the second switching vector of the K period, subscripts a, b, c denote the three-phase bridge arm of the inverter, S1a(K)，S1b(K)，S1c(K) Respectively a phase a, a phase b, a phase c of the K period2a(K)，S2b(K)，S2c(K) Second switching vectors of a phase, b phase and c phase of the K period are respectively;
(1.2) time delay compensation, applying the first switching vector S of the K period according to a two-level inverter system prediction model1(K) Acting on the inverter to calculate the vector action t1(K) Predicted value of current i after time1(t1) Wherein i is1(t1)＝[i1α(t1),i1β(t1)]；
(1.3) applying a second switching vector S2(K) And with i1(t1) As a second switching vector, the actual value of the current prediction calculation is output to obtain S2(K) Action t2(K) T after timek+1Time current prediction value
Figure FDA0003204066150000021
The FCS-MPC system with the resistive-inductive load of the two-level inverter comprises a first switching vector output current calculation prediction model:
Figure FDA0003204066150000022
the second switching vector output current calculation prediction model:
Figure FDA0003204066150000023
in the formula (I), the compound is shown in the specification,
Figure FDA0003204066150000024
r, L is the resistance and inductance of the load, E is half the DC side voltage, the superscript p indicates the model prediction value,
Figure FDA0003204066150000025
is tk+1The time alpha axis predicts the current value,
Figure FDA0003204066150000026
is tk+1Prediction of current value, i, on the axis of time beta1α(t1) Acting on the first switching vector t for the K period1(K) Predicted value of current of alpha coordinate axis after time, i1β(t1) Acting on the first switching vector t for the K period1(K) Predicted value of beta coordinate axis current after time, t1(K) Time of action of the first vector, t2(K) For the first vector action time, I is the cell matrix.
3. The two-stage finite set model predictive control method according to claim 1, wherein the method of step (2) is specifically as follows: second switching vector S to which K periods are applied2(K)＝(S2a(K),S2b(K),S2c(K) As the first switching vector S of the K +1 cycle1(K+1)＝(S1a(K+1),S1b(K+1),S1c(K +1)), and calculates the vector action over the control period TsRear inverter output current i0And an output current error value g0Wherein i0＝[i0α,i0β]；
Output current prediction model:
Figure FDA0003204066150000031
in the formula (I), the compound is shown in the specification,
Figure FDA0003204066150000032
r, L is the resistance and inductance of the load, E is half of the DC side voltage, TsFor the control period, I is the cell matrix;
calculating an output current error:
Figure FDA0003204066150000033
wherein the indices are given reference values,
Figure FDA0003204066150000034
a current reference value is given for the alpha-beta coordinate system,
Figure FDA0003204066150000035
acting the first switching vector for the K +1 period on the entire control period TsAfter tk+2The time alpha axis predicts the current value,
Figure FDA0003204066150000036
acting the first switching vector for the K +1 period on the entire control period TsAfter tk+2The time β coordinate axis predicts the current value.
4. The two-stage finite set model predictive control method according to claim 1, wherein the method of step (3) is as follows:
(4.1) complete period T is carried out on all the effective vectors of two levelssAccording to the evaluation function, calculating the action error value g of all effective switching vectors of the inverteri1,2.. 8, the evaluation function is as follows:
Figure FDA0003204066150000037
wherein the indices are given reference values,
Figure FDA0003204066150000038
a current reference value is given for the alpha-beta coordinate system,
Figure FDA0003204066150000039
acting the entire control period T on the K +1 period effective vectorsAfter tk+2The time alpha axis predicts the current value,
Figure FDA00032040661500000310
acting the entire control period T on the K +1 period effective vectorsAfter tk+2Predicting a current value by a coordinate axis of time beta;
(4.2) calculating the action time t corresponding to different combinations of the first switching vector and the effective vector according to the principle that the action time is in inverse proportion to the action error1(i),t2(i) 1,2.. 8, the calculation formula is as follows:
Figure FDA00032040661500000311
in the formula, TSTo control the period, g0For the current error value at the first switching vector action of each control cycle, giApplying an error value, t, to the active vector of a two-level inverter1(i),t2(i) Two vector action times, respectively.
5. The two-stage finite set model predictive control method according to claim 4, wherein the method of step (4) is as follows:
(5.1) according to the action time t respectively corresponding to the two vectors in different switch combinations and combinations obtained in the step (3)1(i),t2(i) I 1,2.. 8, a prediction operation is first performed on a first switching vector in a prediction period, and the first switching vector is applied to t1(i) Time to obtain predicted value i of output current at action end time1(t1(i) Wherein i) are1(t1(i))＝[i1α(t1(i)),i1β(t1(i))]；
The first switching vector output current calculation prediction model:
Figure FDA0003204066150000041
in the formula (I), the compound is shown in the specification,
Figure FDA0003204066150000042
r, L is the resistance and inductance of the load, E is half of the DC side voltage, t1(i) Is the first vector action time, I is the cell matrix;
(5.2) acting on t with the first switching vector of the prediction cycle1(i) Predicted end time current value i1(t1(i) ) applying a second switching vector in different combinations in step (3) as a starting value and applying t2(i) Time, calculating the predicted value of the output current in the K +1 period, and realizing two-section type model prediction control;
the second switching vector output current calculation prediction model:
Figure FDA0003204066150000043
in the formula (I), the compound is shown in the specification,
Figure FDA0003204066150000044
r, L is the resistance and inductance of the load, E is half of the DC side voltage, t2(i) Is the second vector action time, I is the cell matrix;
(5.3) calculating an output current error value, wherein the error calculation formula is as follows:
Figure FDA0003204066150000045
wherein the indices are given reference values,
Figure FDA0003204066150000046
a current reference value is given for the alpha-beta coordinate system,
Figure FDA0003204066150000047
predicting the end time t of the K +1 period for the two-segment model under the alpha-beta coordinate systemk+2Outputting a current predicted value at any moment;
selecting a group of switch combinations with best current following performance, namely, the smallest error value as two switch vectors to be acted on in the K +1 period according to the formula (9), wherein the effective vector in the combination is the second switch vector S in the K +1 period2(K +1), outputting the second switching vector of the K +1 period and the action time corresponding to the two switching vectors in the switching combination.
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Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8737103B2 (en) * 2010-01-25 2014-05-27 Abb Research Ltd Method and controller for controlling an electrical converter configured for generating an AC current for at least two phases
CN104242768A (en) * 2014-09-11 2014-12-24 天津大学 Finite control set model predictive control method for multi-motor control system
CN106712555A (en) * 2017-01-19 2017-05-24 江苏师范大学 Common-mode voltage satisfactory decision-based FCS-MPC (Finite Control Set Model Predictive Control) method
CN106972735A (en) * 2017-01-19 2017-07-21 江苏师范大学 A kind of new FCS MPC low switching frequency control methods
CN110601627A (en) * 2019-07-11 2019-12-20 天津理工大学 FCS-MPDTC control system and method for expanding voltage space vector output of PMSM
CN111277156A (en) * 2020-03-16 2020-06-12 江苏师范大学 Multi-level inverter FCS-MPC control method without weight factors

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105391271B (en) * 2015-11-01 2019-05-14 华南理工大学 Low frequency rapid finite collection model predictive control method applied to power electronic system
US10651654B2 (en) * 2017-11-07 2020-05-12 State Grid Corporation Of China Model predictive controller for autonomous hybrid microgrids
CN108667389B (en) * 2018-04-02 2020-06-09 江苏大学 Virtual voltage vector model-based prediction fault-tolerant control method

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8737103B2 (en) * 2010-01-25 2014-05-27 Abb Research Ltd Method and controller for controlling an electrical converter configured for generating an AC current for at least two phases
CN104242768A (en) * 2014-09-11 2014-12-24 天津大学 Finite control set model predictive control method for multi-motor control system
CN106712555A (en) * 2017-01-19 2017-05-24 江苏师范大学 Common-mode voltage satisfactory decision-based FCS-MPC (Finite Control Set Model Predictive Control) method
CN106972735A (en) * 2017-01-19 2017-07-21 江苏师范大学 A kind of new FCS MPC low switching frequency control methods
CN110601627A (en) * 2019-07-11 2019-12-20 天津理工大学 FCS-MPDTC control system and method for expanding voltage space vector output of PMSM
CN111277156A (en) * 2020-03-16 2020-06-12 江苏师范大学 Multi-level inverter FCS-MPC control method without weight factors

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
Finite Control Set Model Predictive Control of;Ozan Gulbudak;et al;《2016 IEEE Applied Power Electronics Conference and Exposition (APEC)》;20160512;第3248-3254页 *

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