CN108306505A - A kind of compound adaptive model forecast Control Algorithm of Boost - Google Patents
A kind of compound adaptive model forecast Control Algorithm of Boost Download PDFInfo
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Classifications
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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
- H02M3/00—Conversion of dc power input into dc power output
- H02M3/02—Conversion of dc power input into dc power output without intermediate conversion into ac
- H02M3/04—Conversion of dc power input into dc power output without intermediate conversion into ac by static converters
- H02M3/10—Conversion of dc power input into dc power output without intermediate conversion into ac by static converters using discharge tubes with control electrode or semiconductor devices with control electrode
- H02M3/145—Conversion of dc power input into dc power output without intermediate conversion into ac by static converters using discharge tubes with control electrode or semiconductor devices with control electrode using devices of a triode or transistor type requiring continuous application of a control signal
- H02M3/155—Conversion of dc power input into dc power output without intermediate conversion into ac by static converters using discharge tubes with control electrode or semiconductor devices with control electrode using devices of a triode or transistor type requiring continuous application of a control signal using semiconductor devices only
- H02M3/156—Conversion of dc power input into dc power output without intermediate conversion into ac by static converters using discharge tubes with control electrode or semiconductor devices with control electrode using devices of a triode or transistor type requiring continuous application of a control signal using semiconductor devices only with automatic control of output voltage or current, e.g. switching regulators
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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
- H02M1/00—Details of apparatus for conversion
- H02M1/0003—Details of control, feedback or regulation circuits
- H02M1/0012—Control circuits using digital or numerical techniques
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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
- H02M1/00—Details of apparatus for conversion
- H02M1/0003—Details of control, feedback or regulation circuits
- H02M1/0016—Control circuits providing compensation of output voltage deviations using feedforward of disturbance parameters
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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
- H02M1/00—Details of apparatus for conversion
- H02M1/0003—Details of control, feedback or regulation circuits
- H02M1/0025—Arrangements for modifying reference values, feedback values or error values in the control loop of a converter
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- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Dc-Dc Converters (AREA)
Abstract
The present invention proposes a kind of compound adaptive model forecast Control Algorithm of Boost, including：According to equivalent circuit of the Boost under different on off states, continuous model is established, and by continuous model discretization, obtain the discrete model of Boost；Discrete model based on Boost designs Luenberger observer, obtains the observation of inductive resistance and load resistance using circuit output voltage and inductive current as quantity of state；The controller for establishing Boost, the outer shroud using PI controllers and based on the feed-forward compensator of discrete model as controller；Using Model Predictive Control as inner ring；Square composition cost function of the difference of inductive current predicted value in the inductive current reference value and inner ring that are generated based on outer shroud；Optimized switching state is selected by minimizing cost function.The present invention obtains the tracing control that optimal on off state realizes electric current and voltage by the prediction result of the more different on off states of cost function, to rapidly restore to stablize from disturbance.
Description
Technical Field
The invention belongs to the field of control of power electronic converters, and particularly relates to a composite self-adaptive model prediction control method of a Boost converter.
Background
With the improvement and improvement of semiconductor devices and computer technologies, power electronic technologies have been rapidly developed. The Boost converter is used as an important component of the power electronic converter, has the advantages of simple structure, capability of flexibly realizing Boost control on input voltage and the like, and is widely applied to the fields of direct current motor transmission, hybrid vehicles, photovoltaic power generation and the like. Obtaining an expected stable output voltage by generating a corresponding switching signal is an important target for Boost converter control, and good dynamic response is also an important index of control effect. In recent years, control-oriented modeling and model-based control are rapidly developed, and in practical application, model mismatching caused by parameter uncertainty and load disturbance can affect the control effect.
According to the structure of a closed-loop system, the control of a Boost converter mainly comprises two types, namely a multivariable design method and a cascade control strategy. The basic cascade control is the control design of the inner ring and the outer ring of the system based on PI control, which can meet the basic control requirements, but is difficult to meet the dynamic and static control performance of the system when the system parameters change. On the basis of the cascade Control, many studies have been made to obtain better Control performance by changing an inner loop controller, such as dead-beat Control, sliding mode Control, and Model Predictive Control (MPC). The model predictive control is an optimization control strategy based on a model, has the characteristics of quick dynamic performance and strong robustness, and can intuitively and effectively realize the tracking control of the converter aiming at the switching characteristic of the execution unit compared with sliding mode control and an intelligent algorithm.
Kim et al (Kim, look-Kyon, et al. A stabilizing model predictive control for a dc/dc boost controller [ J ], IEEE Transactions on control Systems Technology,2014,22(5):2016-2023.) use model predictive control as an inner loop controller for cascade control, showing a better control effect compared to the cascade control of the conventional PI structure, but whose dynamic response time is influenced to some extent by the PI controller of the outer loop. In addition, when the Boost converter is controlled by applying model predictive control, a certain steady-state error exists between an output value and a reference value as a result of the structure of the model is not accurate enough.
Disclosure of Invention
The invention provides a composite self-adaptive model prediction control method of a Boost converter, aiming at the influence of parameter uncertainty and load disturbance on the control effect of the Boost converter, in particular to the influence on the dynamic control performance of a system.
The technical scheme adopted by the invention for solving the technical problems is as follows:
a composite adaptive model prediction control method of a Boost converter comprises the following steps:
1) establishing a Continuous model under an inductive Current Continuous Mode (CCM) according to an equivalent circuit structure corresponding to the Boost converter when the working states of the semiconductor switch units are different, and obtaining a discrete model of the Boost converter by utilizing a first-order forward Euler approximation;
2) taking circuit output voltage and inductive current as state quantities, designing a Longbeige observer, observing parameter deviation in a circuit, continuously correcting a model prediction control model and a model in a model-based feedforward compensator according to the deviation value, mainly correcting an inductive resistor and a load resistor, further realizing accurate voltage tracking control, and improving the response of a system to parameter change;
3) the method comprises the steps of establishing a controller of a Boost converter by utilizing a basic structure of cascade control, wherein PI control and a model-based feedforward compensator are adopted as an outer ring, namely a voltage control ring, of the controller, the function of the voltage control ring is to generate a reference value of inductive current according to an error value between reference voltage and output voltage, model prediction control is adopted as an inner ring, namely a current control ring, and tracking control over the output voltage is indirectly realized by tracking the inductive current.
The feedforward compensator is introduced mainly to improve the dynamic response process of the system, and the PI controller is used for eliminating steady-state errors caused by inaccurate model structures. In addition, when the Model Predictive controller of the inner ring is designed, according to the characteristic that the switching state of the Boost converter is limited, a Finite Control set Model Predictive Control FCS-MPC (Finite Control-Model Predictive Control) is adopted, and the prediction results of different switching states are compared through a value function to obtain the optimal switching state so as to realize current tracking Control.
The invention has the following beneficial effects:
(1) compared with the traditional PI MPC (Model Predictive Control), the invention introduces a Model-based feedforward compensator on the basis of the PI controller, has a faster dynamic response process, adopts a cascade Control strategy by the controller, takes the PI Control as a voltage Control loop, and can achieve the purpose of eliminating the steady-state error compared with the Control only by the MPC;
(2) according to the method, the observer reflects the parameter change of the system and corrects the model according to the change of the observer, so that the influence of inaccurate system parameters and load interference on the control effect can be reduced, the change condition of the parameters can be observed, the dynamic response of the system during the parameter change is improved, and a faster response process is realized;
(3) if the gain of the PI link of the invention is set to 0, i.e. the PI Control of a voltage Control loop is removed, the controller structure is transformed into an adaptive Model Predictive Control (UOFOMC), but compared with the invention, the PI link is added on the basis of the UOFC, so that the dependence of the UOFC on an accurate circuit Model can be reduced, and accurate voltage output can be obtained.
The present invention will be described in further detail with reference to the drawings and embodiments, but the method for the composite adaptive model predictive control of the Boost converter according to the present invention is not limited to the embodiments.
Drawings
FIG. 1 is a schematic diagram of a Boost converter and its equivalent circuit, in which FIG. 1(a) is a complete circuit diagram, and FIGS. 1(b) and (c) are switching devices S, respectively1An equivalent circuit at turn-on and turn-off;
FIG. 2 is a functional block diagram of a control method of the present invention;
FIG. 3 is a flowchart of a program used in the control method of the present invention;
FIG. 4 is a simulation result of the output of the present invention when the output reference voltage changes, wherein FIGS. 4(a) and (b) are the changes of the output voltage and the inductor current, respectively, and FIGS. 4(c) and (d) are the observation results of the load resistance and the inductor resistance, respectively;
FIG. 5 is a simulation result of the output of the present invention when the load resistance changes, wherein FIGS. 5(a) and (b) output the change of the voltage and the inductive current, respectively, and FIGS. 5(c) and (d) are the observation results of the load resistance and the inductive resistance, respectively;
fig. 6 is a simulation (experiment) output of the present invention when the inductor resistance changes, wherein fig. 6(a) and (b) output the change of the voltage and the inductor current, respectively, and fig. 6(c) and (d) are the observation results of the load resistance and the inductor resistance, respectively.
Detailed Description
The following detailed description of embodiments of the invention refers to the accompanying drawings.
The invention provides a composite self-adaptive model prediction control method of a Boost converter, which comprises the following steps:
1) and establishing a Boost converter model. According to a schematic diagram of a Boost converter shown in fig. 1(a), combining equivalent circuits in different switching states in fig. 1(b) and (c), discretizing a continuous model by using first-order forward Euler approximation, and establishing a discrete model of the Boost converter:
wherein R isLAn inductive resistance representing an equivalent circuit; t issRepresenting the sampling period of the equivalent circuit; l represents the inductance of the equivalent circuit; vinRepresents an input voltage of the equivalent circuit; vdA diode drop representing an equivalent circuit; r represents a load resistance of the equivalent circuit; c represents the capacitance of the equivalent circuit; i (k) represents the inductor current of the kth sample; i (k +1) represents the inductor current of the (k +1) th sampling; u. ofo(k) Represents the output voltage of the kth sample; u. ofo(k +1) represents the output voltage of the (k +1) th sampling; s (k) e 0,1 represents the switching state of the circuit at the kth sampling period.
For simplicity of calculation, let Y equal to 1/R and use Y simultaneously0And RL0Respectively, by defining deviations DeltaY and DeltaRLFormula (1) may be rewritten as follows:
in combination with the actual condition, Δ R in the formulaL(k+1)＝ΔRL(k) And Δ Y (k +1) ═ Δ Y (k) indicates that the variables are both changing slowly.
2) And (4) designing a Longbeige observer.
On the basis of the formula (2), letIt can be simplified as:
therefore, the observer based on the Roeberg structure can be obtained:
wherein,represents the observed value of the corresponding parameter,representing an error between the observed value and the true value of the corresponding parameter; l1～l8Is the parameter to be solved.
By subtracting the formula (3) from the formula (4), andthe error can be obtained as follows:
according to the condition of observer convergence, the characteristic value of the matrix A is set to be 0.8, and l in the matrix is set to be2、l3、l6And l7Setting the matrix eigenvalue to be 0.8, listing a quaternary linear equation set, and solving to obtain the rest parameters l1、l4、l5And l8The value of (2) is substituted into (6) to obtain:
the deviation value of the corresponding parameter is obtained according to the formula, so that the observed value of the delta M (k) can be obtainedAnd the observed value of Δ N (k)Further obtaining observed values of the load resistance and the inductance resistance:
3) a controller of the Boost converter is established.
According to the structure of cascade control, a feedforward compensator is added on the basis of outer loop PI control, an observer is adopted to observe load resistance and inductance resistance, the load resistance and the inductance resistance in a model are corrected, and a control structure block diagram of a closed loop system is shown in figure 2.
Reference value i of the inductor current in the outer loop of the controllerrefIr produced by feedforward compensator1And ir generated by PI controller2Added according to the input-output power relation P of the circuitin＝PoutThe following can be obtained:
wherein u isrefRepresents a reference voltage;
from the above equation, two solutions can be obtained, the smaller of which is selected from the energy point of view, namely:
the discrete form is as follows:
in addition, ir generated by PI control2Expressed as:
wherein, KPRepresents a proportional gain, the value of which is 0.01; kIRepresents an integral gain, the value of which is 4;
then there is
iref(k+1)＝ir1(k+1)+ir2(k+1) (12)
Wherein iref(k +1) represents the inductor current reference value of the (k +1) th sampling;
the inner ring of the controller adopts model prediction control, and the value function is as follows:
in the formula ipredIndicates the predicted value, ipred(k +1) represents the predicted value of the inductive current of the (k +1) th sampling; according to the FCS-MPC principle, the predicted values of the next moment under different switch states are calculated by a discrete model by using the circuit parameters acquired at the current moment, and the expression is as follows:
the optimal switching state s is selected by selecting the minimum associated cost, which follows the equation:
in summary, the control procedure flow chart of the composite adaptive model predictive control method for the Boost converter provided by the present invention can be represented as the form shown in fig. 3, and the working principle of the closed loop can be divided into the following basic steps:
a. initializing a digital controller for giving initial values of variables used in the algorithm, including circuit parameters (especially load resistance and inductance resistance), PI control parameters, an observer matrix a;
b. measuring the system variables i (k) and u by sensorso(k)；
c. Estimating load resistance and inductance resistance by using an observer, and simultaneously calculating ir generated by a PI controller2；
d. The obtained observed values of the load resistance and the inductance resistance are processed through a filter, and fluctuation of an estimated value is reduced;
e. calculating ir produced by feedforward compensator1Wherein a determination is made as to whether to update the ir1；
f. Calculate irefThe value of which can be expressed as iref＝ir1+ir2；
g. Calculating the predicted output i of the next sampling period of the inductive current in different switch states by using a discrete modelpred(k+1)；
h. Evaluating a cost function for each switch state;
i. selecting a switch state that minimizes the cost function, outputting the switch state, entering the next sampling period, and repeating the above process.
In order to demonstrate the performance of the control method according to the invention, the control method provided will be briefly described below with reference to some embodiments of the invention in the accompanying drawings, which simulate the algorithm mainly by means of simulation software MATLAB/SIMULINK, the simulation parameters being shown in table 1, wherein fsRepresenting the sampling frequency.
TABLE 1
Referring to fig. 4, a waveform diagram of a control variable and an observed value when the Boost converter outputs a reference voltage change is shown, where the reference voltage changes from 20V to 27V at 1s and returns to 20V at 2s, and it can be seen from the waveform diagrams of the output voltage and the inductive current of fig. 4(a) and (b) that the adjustment time is about 0.045s at the rising stage, which shows that when the Boost converter is controlled by using the control method of the present invention, there is a faster dynamic response when the reference voltage suddenly changes.
Referring to fig. 5, which is a waveform diagram of the Boost converter when the load resistance changes, the load resistance changes from 30 Ω to 15 Ω and back to 30 Ω at 1s and 2s, respectively, according to fig. 5(a) and (b), under the control method of the present invention, the output can respond to the change of the load resistance quickly, and fig. 5(c) reflects the change process of the load resistance.
Accordingly, referring to fig. 6 showing the waveform of the output parameter of the Boost converter when the inductance resistance changes, it can be seen that the system also reacts quickly to the change when the inductance resistance changes from 0.3 Ω to 0.45 Ω at 1s, and fig. 6(d) shows the change process of the inductance resistance.
On the basis that the model is inaccurate due to parameter uncertainty and load disturbance, the observer is added to the basic structure of the PI MPC to improve adverse results caused by a circuit model, and meanwhile, in order to enable the system to have a faster dynamic response process, the model-based feedforward compensator is introduced on the basis of the PI control of the outer ring, so that the output of the Boost converter can have good dynamic performance on the basis of stability. Simulation and related experimental results show that the control method provided by the invention can realize accurate voltage tracking, has good robustness and dynamic performance, and can quickly recover stability from disturbance. In addition, due to the introduction of the observer, the changes of the circuit inductance resistance and the load resistance can be monitored in real time during the operation of the system.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (4)
1. A composite adaptive model prediction control method of a Boost converter is characterized by comprising the following steps:
step 1, establishing a continuous model under an inductive current continuous mode according to equivalent circuits of a Boost converter under different switching states, and discretizing the continuous model by utilizing first-order forward Euler to obtain a discrete model of the Boost converter;
step 2, designing a Roeberg observer by taking circuit output voltage and inductive current as state quantities based on a discrete model of a Boost converter to obtain observed values of an inductive resistor and a load resistor;
step 3, establishing a controller of the Boost converter by utilizing a basic structure of cascade control, and adopting a PI (proportional integral) controller and a feedforward compensator based on a discrete model as an outer ring of the controller; adopting model prediction control as an inner ring; forming a cost function based on the square of the difference between the reference value of the inductive current generated by the outer ring and the predicted value of the inductive current in the inner ring; selecting an optimal switch state by minimizing a cost function; wherein the reference value of the inductor current is related to the observed values of the inductor resistance and the load resistance; the predicted value of the inductor current is related to the observed value of the inductor resistance.
2. The composite adaptive model predictive control method of the Boost converter according to claim 1, characterized in that the discrete model of the Boost converter obtained in step 1 is as follows:
wherein R isLAn inductive resistance representing an equivalent circuit; t issRepresenting the sampling period of the equivalent circuit; l represents the inductance of the equivalent circuit; vinRepresents an input voltage of the equivalent circuit; vdA diode drop representing an equivalent circuit; r represents a load resistance of the equivalent circuit; c represents the capacitance of the equivalent circuit; i (k) represents the inductor current of the kth sample; i (k +1) represents the inductor current of the (k +1) th sampling; u. ofo(k) Represents the output voltage of the kth sample; u. ofo(k +1) represents the output voltage of the (k +1) th sampling; s (k) is equal to {0,1} and represents the switch state of the circuit in the k sampling period;
let Y equal to 1/R and use Y simultaneously0And RL0respectively, by defining deviations DeltaY and DeltaRLTo obtain the following formula:
wherein, in the formula, Δ RL(k+1)＝△RL(k) and △ Y (k +1) ═ △ Y (k) indicates that the variables are both changing slowly.
3. The composite adaptive model predictive control method of the Boost converter according to claim 2, wherein the step 2 specifically comprises:
order toEquation (2) is simplified to:
an observer based on a luneberg structure is thus obtained, as follows:
wherein,represents the observed value of the corresponding parameter,representing an error between the observed value and the true value of the corresponding parameter; l1～l8Is a parameter to be solved;
by subtracting the formula (3) from the formula (4), andthe error can be obtained as follows:
according to the condition of observer convergence, the characteristic value of the matrix A is set to be 0.8 to obtain a matrixTo give the following formula:
obtaining an observed value of DeltaM (k) according to the formulaobserved value of sum DeltaN (k)Further obtaining observed values of the load resistance and the inductance resistance:
4. the composite adaptive model predictive control method of the Boost converter according to claim 3, wherein the step 3 specifically comprises:
reference value i of the inductor currentrefIr produced by feedforward compensator1And ir generated by PI controller2Adding the obtained products; according to the equal input and output power of the circuit, the following results are obtained:
wherein u isrefRepresents a reference voltage;
from the above equation, two solutions can be obtained, the smaller of which is selected from the energy point of view, resulting in:
the discrete form is as follows:
ir produced by PI controller2Expressed as:
wherein, KPRepresents a proportional gain; kIRepresents the integral gain;
then there is
iref(k+1)＝ir1(k+1)+ir2(k+1) (12)
Wherein iref(k +1) represents the inductor current reference value of the (k +1) th sampling;
the inner loop adopts model prediction control, and the cost function is as follows:
wherein ipred(k +1) represents the predicted value of the inductive current of the (k +1) th sampling;
according to the FCS-MPC principle, the predicted values of the next moment in different switch states are calculated by a discrete model by utilizing circuit parameters acquired at the current moment to obtain ipredThe expression of (k +1) is as follows:
the optimal switching state s is selected by selecting the minimum associated cost, as follows:
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| CN109861565A (en) * | 2019-01-25 | 2019-06-07 | 湖南大学 | A kind of Model Reference Adaptive Control Method of two-stage type AC/DC converter |
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