# Research of Active Power Filter Modeling with Grid Impedance in Feedback Linearization and Quasi-Sliding Mode Control

Authors: Zeyu Shi; Yingpin Wang; Yunxiang Xie; Lanfang Li; Xiaogang Xu
Journal: Mathematical Problems in Engineering
 (2017)

---

## Abstract

Active power filter (APF) is the most popular device in regulating power quality issues. Currently, most literatures ignored the impact of grid impedance and assumed the load voltage is ideal, which had not described the system accurately. In addition, the controllers applied PI control; thus it is hard to improve the compensation quality. This paper establishes a precise model which consists of APF, load, and grid impedance. The Bode diagram of traditional simplified model is obviously different with complete model, which means the descriptions of the system based on the traditional simplified model are inaccurate and incomplete. And then design exact feedback linearization and quasi-sliding mode control (FBL-QSMC) is based on precise model in inner current loop. The system performances in different parameters are analyzed and dynamic performance of proposed algorithm is compared with traditional PI control algorithm. At last, simulations are taken in three cases to verify the performance of proposed control algorithm. The results proved that the proposed feedback linearization and quasi-sliding mode control algorithm has fast response and robustness; the compensation performance is superior to PI control obviously, which also means the complete modeling and proposed control algorithm are correct.


---

## Body

## 1. Introduction

Active power filter (APF) is the most popular device in harmonics compensation; it commonly consists of current filter, electronic converter, and DC-link capacitor. The APF connected to grid and compensated power quality problems [1].Recently, the interactions between grid connected devices and the grid have drawn greater attention [2]. However, most literatures established the model of isolated APF and rarely consider the impact of grid impedance [3]. Thus the descriptions of the system based on the traditional simplified model are inaccurate and incomplete. If the mathematical models of the grid impedance and the loads were contained in the APF control system, then the specific effects of each of them could be studied more accurately and completely [4].In recent decades, nonlinear control theory has made a great progress, especially feedback linearization (FBL) theory based on differential geometry. Feedback linearization control can achieve global linearization by using a certain nonlinear state transformation or feedback transformation [5]. All these methods can solve the problem of nonlinear system and obviously improve static and dynamic performance. Yet, this control method depends on an accurate mathematical model and is sensitive to system parameters [6]. There are many literatures that adopted feedback linearization in three-phase APF [7] and single-phase APF [8]. However, none of them consider the impact of grid impedance. Thus, the optimum performance of APF has not been achieved.Sliding mode control shows great robustness and fast convergence when the system is running in the sliding surface [9]. Thus, slide model control (SMC) is adopted to increase the robustness in model uncertainties and reduce disturbance responses [10]. In [11], sliding mode control has been applied to the three-phase APF and achieved a good result.This paper establishes a precise model consisting of APF, load, and grid impedance. And then it applies exact feedback linearization and quasi-sliding mode control method (FBL-QSMC) in inner current loop. At last, it analyzes the performances of proposed algorithm and compares with traditional PI control algorithm in dynamic respond and simulation.


## 2. Mathematical Model of APF with Grid Impedance

The structure diagram of LC APF with grid impedance is shown in Figure1. Because a three-phase APF system is symmetrical, the system is analyzed with its single-phase circuit [12]. The single-phase circuit diagram of an APF with current controller is shown in Figure 2.Figure 1
Structure ofLC APF with grid impedance.Figure 2
Single-phase circuit diagram ofLC APF with grid impedance.In Figure2, udc is voltage of DC-link, Cdc is capacitor of DC-link, up is output voltage of converter, i1 is output current of converter, L1/R1 is filter impedance, C is filter capacitor, ip is current of APF compensating, uL is voltage in load side, iL is load current, LL/RL is equivalent impedance of load, Ls/Rs is grid impedance, and us is grid voltage.From Figure2, there are the following equations:(1)Lsdisdt=-Rsis+us-uL,LLdiLdt=-RLiL+uL,L1di1dt=-R1i1+up-uL,CduLdt=i1-ip,where ip=iL-is.The role of inner current loop is keeping source currentis tracking with reference current is∗ and realizing system unity power factor operation. This paper applies feedback linearization in inner current loop, designed state variables are X=x1x2x3x4T=isiLi1uLT, input variable is u=up, and the output variable is Y=h(X)=x1. The following affine nonlinear equations are obtained.(2)X•=fX+gXu,Y=hX,where(3)fX=-RsLsx1-1Lsx4+usLs-RLLLx2+1LLx4-R1L1x3-1L1x41Cx1-1Cx2+1Cx3,gX=001L10.


## 3. Control System Design

### 3.1. Feedback Linearization of APF with Grid Impedance

Lemma 1.
L
f
h
(
X
) and Lgh(X) are the Lie derivatives of h(X) with respect to f(X) and g(X). If LgLfkhx=0 for all k<r-1, and LgLfr-1h(x)≠0, that means the system’s relative degree is r [8].Taking Lie derivative for (2), the following is obtained:(4)LghX=0,LgLfhX=0,LgLf2hX=-1C∗L1∗LS,LgLf3hX=RS/C∗LS2+R1/C∗L1∗LSL1.From (4), the relative degree r=3 is less than the system dimension n=4, which means the nonlinear systems are designed to be minimum phase with its zero dynamics. Because the zero dynamics are assumed to be globally stable, the state variables converge and so does the closed-loop system [13].After taken Lie derivative obtained the variables transformation, the state equations of APF with grid impedance control system altered to(5)Z=ξ1ξ2ξ3η1=hXLfhXLf2hXη1=x1-RSx1Ls-x4Ls+UsLsx1RS2LS2-1CLS+1CLSx2-x3CLS+x4RSLS2-USRSLS2+U•sLsx2.Thus,(6)x1=ξ1,x2=η1,x3=-ξ1-ξ2RSC-ξ3CLS+η1+U•SC,x4=US-RSξ1-LSξ2.There are(7)ξ•1=ξ2,ξ•2=ξ3,ξ•3=bξ,η+aξ,ηu,η•1=-RLLLη1+1LLUS-RSξ1-LSξ2.Since the state variables converge to zero due to the linear characteristics, the closed-loop trajectories can be well controlled. Furthermore, some assumption must be applied to the fourth equation of (7) [13]:(8)η•=q0,ηfort⟶∞.That is,(9)η•1=-RLLLη1+USLL.Equation (9) shows zero dynamics is bounded and exponentially stable.In (7), a(ξ,η)=LgLf2h(X) and b(ξ,η)=Lf3h(X), assuming the new input is ξ3•=ξ1•••=v, the original nonlinear state equations can be written as standard linear equation:(10)Z•=010001000Z+001v.The input transformation can be expressed as(11)u=-Lf3hX+vLgLf2hX.The equivalent control input of feedback linearization is(12)ueq=-Lf3hXLgLf2hX.In Lie derivative(13)LgLf2hX=-1CL1LS,Lf3hX=K1x1+K2x2+K3x3+K4x4+U••SLS-U•SRSLS2-USCLS2+RS2USLS3,where(14)K1=RS/CLS-RS3/LS2LS+RSCLS2,K2=-RSCLS2+RLCLLLS,K3=RSCLS2+R1CL1LS,K4=1/CL1+1/CLL+1/CLSLS-RS2LS3.Thus(15)ueq=CL1LSK1x1+K2x2+K3x3+K4x4+U••SLS-U•SRSLS2-USCLS2+RS2USLS3.


### 3.2. Quasi-Sliding Mode Controller Design

Quasi-sliding mode control (QSMC) can eliminate the chattering of sliding mode and keep stable and thus is used in widespread manner recently [14].From the above analysis it is known that this is a 3-order system, ande=x1-x1ref, thus defining the sliding surface as(16)s=c2e••+c1e•+e.In QSMC, reaching law is designed as(17)s•=-ε·sats,where (18)sats=1,sΔ,-1,s>Δs<Δs<-Δ,Δ>0.ε>0.Consider a positive augmented Lyapunov candidate as(19)V=12λs2,where λ>0 is a design parameter.The time derivative ofV is(20)V•=λss•.Substituting (16) and (17) into (20) obtains(21)V•=-λεs·sats≤0.By the Lyapunov theorem of stability and LaSalle’s invariance principle, the control system is proved to be stable.Based on (7), there are(22)s•=c2e•••+c1e••+e•=c2bx+axu-x•••1ref+c1e••+e•.Thus(23)u=ε·sats-c1e••-e•/c2+x•••1ref-bxax.The above equation can be taken as(24)u=ueq+usw,where(25)usw=ε·sats-c1e••-e•/c2+x•••1refax.There is(26)usw=-ε·sats-c1e••-e•c2+x•••1ref∗CL1LS.After designing,c1=4×10-4, c2=10-9, ε=100, Δ=10.


### 3.3. Implementation of Feedback Linearization Sliding Mode Control

The control diagram of feedback linearization quasi-sliding mode control (FBL-QSMC) is shown in Figure3. The control system consists of outer voltage loop and inner current loop. The outer voltage loop applied PI control, and the inner current loop applied FBL-QSMC control. It is necessary to remind that there are three identical inner current loops in three phases, respectively. However, there is only drawn one phase in the diagram.Figure 3
Control diagram of three-phase four-wire APF.As shown in Figure3, the source reference active current ird is equal to the sum of load’s active current iLd∗ and DC-link voltage regulating current idc∗; the reference reactive current irq and zero sequence current are equal to zero. After Park’s transformation, the reference current from dq0 coordinate transformed to abc coordinate. The reference current irabc subtracts the source current isabc which obtains the source error current eabc in abc phase, respectively. The source error current eabc applied sliding mode control obtains switching input usw and state variables in feedback linearization control obtain equivalent control input ueq and then sum up them equal to the control input signal u.


## 3.1. Feedback Linearization of APF with Grid Impedance

Lemma 1.
L
f
h
(
X
) and Lgh(X) are the Lie derivatives of h(X) with respect to f(X) and g(X). If LgLfkhx=0 for all k<r-1, and LgLfr-1h(x)≠0, that means the system’s relative degree is r [8].Taking Lie derivative for (2), the following is obtained:(4)LghX=0,LgLfhX=0,LgLf2hX=-1C∗L1∗LS,LgLf3hX=RS/C∗LS2+R1/C∗L1∗LSL1.From (4), the relative degree r=3 is less than the system dimension n=4, which means the nonlinear systems are designed to be minimum phase with its zero dynamics. Because the zero dynamics are assumed to be globally stable, the state variables converge and so does the closed-loop system [13].After taken Lie derivative obtained the variables transformation, the state equations of APF with grid impedance control system altered to(5)Z=ξ1ξ2ξ3η1=hXLfhXLf2hXη1=x1-RSx1Ls-x4Ls+UsLsx1RS2LS2-1CLS+1CLSx2-x3CLS+x4RSLS2-USRSLS2+U•sLsx2.Thus,(6)x1=ξ1,x2=η1,x3=-ξ1-ξ2RSC-ξ3CLS+η1+U•SC,x4=US-RSξ1-LSξ2.There are(7)ξ•1=ξ2,ξ•2=ξ3,ξ•3=bξ,η+aξ,ηu,η•1=-RLLLη1+1LLUS-RSξ1-LSξ2.Since the state variables converge to zero due to the linear characteristics, the closed-loop trajectories can be well controlled. Furthermore, some assumption must be applied to the fourth equation of (7) [13]:(8)η•=q0,ηfort⟶∞.That is,(9)η•1=-RLLLη1+USLL.Equation (9) shows zero dynamics is bounded and exponentially stable.In (7), a(ξ,η)=LgLf2h(X) and b(ξ,η)=Lf3h(X), assuming the new input is ξ3•=ξ1•••=v, the original nonlinear state equations can be written as standard linear equation:(10)Z•=010001000Z+001v.The input transformation can be expressed as(11)u=-Lf3hX+vLgLf2hX.The equivalent control input of feedback linearization is(12)ueq=-Lf3hXLgLf2hX.In Lie derivative(13)LgLf2hX=-1CL1LS,Lf3hX=K1x1+K2x2+K3x3+K4x4+U••SLS-U•SRSLS2-USCLS2+RS2USLS3,where(14)K1=RS/CLS-RS3/LS2LS+RSCLS2,K2=-RSCLS2+RLCLLLS,K3=RSCLS2+R1CL1LS,K4=1/CL1+1/CLL+1/CLSLS-RS2LS3.Thus(15)ueq=CL1LSK1x1+K2x2+K3x3+K4x4+U••SLS-U•SRSLS2-USCLS2+RS2USLS3.


## 3.2. Quasi-Sliding Mode Controller Design

Quasi-sliding mode control (QSMC) can eliminate the chattering of sliding mode and keep stable and thus is used in widespread manner recently [14].From the above analysis it is known that this is a 3-order system, ande=x1-x1ref, thus defining the sliding surface as(16)s=c2e••+c1e•+e.In QSMC, reaching law is designed as(17)s•=-ε·sats,where (18)sats=1,sΔ,-1,s>Δs<Δs<-Δ,Δ>0.ε>0.Consider a positive augmented Lyapunov candidate as(19)V=12λs2,where λ>0 is a design parameter.The time derivative ofV is(20)V•=λss•.Substituting (16) and (17) into (20) obtains(21)V•=-λεs·sats≤0.By the Lyapunov theorem of stability and LaSalle’s invariance principle, the control system is proved to be stable.Based on (7), there are(22)s•=c2e•••+c1e••+e•=c2bx+axu-x•••1ref+c1e••+e•.Thus(23)u=ε·sats-c1e••-e•/c2+x•••1ref-bxax.The above equation can be taken as(24)u=ueq+usw,where(25)usw=ε·sats-c1e••-e•/c2+x•••1refax.There is(26)usw=-ε·sats-c1e••-e•c2+x•••1ref∗CL1LS.After designing,c1=4×10-4, c2=10-9, ε=100, Δ=10.


## 3.3. Implementation of Feedback Linearization Sliding Mode Control

The control diagram of feedback linearization quasi-sliding mode control (FBL-QSMC) is shown in Figure3. The control system consists of outer voltage loop and inner current loop. The outer voltage loop applied PI control, and the inner current loop applied FBL-QSMC control. It is necessary to remind that there are three identical inner current loops in three phases, respectively. However, there is only drawn one phase in the diagram.Figure 3
Control diagram of three-phase four-wire APF.As shown in Figure3, the source reference active current ird is equal to the sum of load’s active current iLd∗ and DC-link voltage regulating current idc∗; the reference reactive current irq and zero sequence current are equal to zero. After Park’s transformation, the reference current from dq0 coordinate transformed to abc coordinate. The reference current irabc subtracts the source current isabc which obtains the source error current eabc in abc phase, respectively. The source error current eabc applied sliding mode control obtains switching input usw and state variables in feedback linearization control obtain equivalent control input ueq and then sum up them equal to the control input signal u.


## 4. Analysis of System Performance

The system parameters are listed in Table1.Table 1
System parameters.
Parameters
Value
RMS source voltage (Us)
380 V
Fundamental frequency (f)
50 Hz
L filter (L1/R1)
0.6 mH/0.025 Ω
C filter (C)
10μF
Grid impedance (Ls/Rs)
0.03 mH/0.5 Ω
Load equivalent impedance(LL/RL)
0.7 mH/3.6 Ω
DC-side desired voltage (Vdc)
700 V
DC-side capacitor (Cdc)
5000μF


### 4.1. Analysis of Transfer Functions

In traditional method [15], the LC filter is designed based on the transfer function of converter output voltage up to load voltage uL without load and grid impedance. The transfer function is (27)tup2uL=1L1Cs2+CR1s+1.In traditional model, it is unable to obtain the transfer relationship of converter output voltageup to source current Is. Only the relationship of converter output voltage up to converter output current I1 is obtained, in assuming the load voltage uL is constant, such that(28)tup2I1=1L1s+R1.The resonant frequencyfr is (29)fr=12πL1C.Substitute the system parametersL1 and C into (29); the resonant frequency fr = 2055 Hz.From the above equations, applying Matlab obtained the transfer functions and the Bode diagrams are shown in Figure4.Figure 4
Bode diagram of transfer functions.In Figure4, the line “up2Is” is represented transfer function of converter output voltage up to source current Is in proposed model; the line “up2uL” is represented transfer function of converter output voltage up to load voltage uL in proposed model; the line “up2I1” is represented transfer function of converter output voltage up to converter output current I1 in proposed model; the line “tup2uL” is represented transfer function of converter output voltage up to load voltage uL in traditional model; the line “up2I1” is represented transfer function of converter output voltage up to converter output current I1 in traditional model.From Figure4 it is seen that the frequency characteristics of traditional simplified model are obviously different with proposed precise model, which means the traditional model cannot describe the system correctly. Thus it is necessary to establish a precise model for analyzing parameters and designing controller.


### 4.2. Impact of Grid Impedance

The Bode diagram of converter output voltageup to source current Is “up2Is” in different grid inductive impedance Ls is shown in Figure 5.Figure 5
Bode diagram ofup2Is in different Ls.From Figure5 it is seen that with the grid inductive impedance increasing the high frequency magnitude of Is decreases, and the resonant frequency also decreases.The Bode diagram of converter output voltageup to source current Is “up2Is” in different grid resistance Rs is shown in Figure 6.Figure 6
Bode diagram ofup2Is in different Rs.From Figure6 it is seen that with the grid resistance increasing the steady magnitude of Is decreases, and the resonant quality factor decreases.


### 4.3. Comparison of Control Systems

In PI controller, the parameters are inner loop proportionality coefficientKp=10, integral coefficient Ki=2000, outer loop proportionality coefficient Kp=1, and integral coefficient Ki=1000.In FBL-QSMC controller, the inner loop is based on equivalent inputueq and QSMC input usw, the outer loop is based on PI controller, the proportionality coefficient Kp=1, and integral coefficient Ki=1000.Comparison of the step response performances is shown in Figure7.Figure 7
Step response in different controller.From Figure7 it is known that in PI controller converges slowly. However, FBL controller responds quickly and converges fast.In cos signal input, the responses of PI controller and FBL controller are shown in Figure8.Figure 8
Cos input response in different controller.From Figure8 it is known that in PI controller the convergence time is more than a period. However, FBL controller responds quickly and converges fast.


## 4.1. Analysis of Transfer Functions

In traditional method [15], the LC filter is designed based on the transfer function of converter output voltage up to load voltage uL without load and grid impedance. The transfer function is (27)tup2uL=1L1Cs2+CR1s+1.In traditional model, it is unable to obtain the transfer relationship of converter output voltageup to source current Is. Only the relationship of converter output voltage up to converter output current I1 is obtained, in assuming the load voltage uL is constant, such that(28)tup2I1=1L1s+R1.The resonant frequencyfr is (29)fr=12πL1C.Substitute the system parametersL1 and C into (29); the resonant frequency fr = 2055 Hz.From the above equations, applying Matlab obtained the transfer functions and the Bode diagrams are shown in Figure4.Figure 4
Bode diagram of transfer functions.In Figure4, the line “up2Is” is represented transfer function of converter output voltage up to source current Is in proposed model; the line “up2uL” is represented transfer function of converter output voltage up to load voltage uL in proposed model; the line “up2I1” is represented transfer function of converter output voltage up to converter output current I1 in proposed model; the line “tup2uL” is represented transfer function of converter output voltage up to load voltage uL in traditional model; the line “up2I1” is represented transfer function of converter output voltage up to converter output current I1 in traditional model.From Figure4 it is seen that the frequency characteristics of traditional simplified model are obviously different with proposed precise model, which means the traditional model cannot describe the system correctly. Thus it is necessary to establish a precise model for analyzing parameters and designing controller.


## 4.2. Impact of Grid Impedance

The Bode diagram of converter output voltageup to source current Is “up2Is” in different grid inductive impedance Ls is shown in Figure 5.Figure 5
Bode diagram ofup2Is in different Ls.From Figure5 it is seen that with the grid inductive impedance increasing the high frequency magnitude of Is decreases, and the resonant frequency also decreases.The Bode diagram of converter output voltageup to source current Is “up2Is” in different grid resistance Rs is shown in Figure 6.Figure 6
Bode diagram ofup2Is in different Rs.From Figure6 it is seen that with the grid resistance increasing the steady magnitude of Is decreases, and the resonant quality factor decreases.


## 4.3. Comparison of Control Systems

In PI controller, the parameters are inner loop proportionality coefficientKp=10, integral coefficient Ki=2000, outer loop proportionality coefficient Kp=1, and integral coefficient Ki=1000.In FBL-QSMC controller, the inner loop is based on equivalent inputueq and QSMC input usw, the outer loop is based on PI controller, the proportionality coefficient Kp=1, and integral coefficient Ki=1000.Comparison of the step response performances is shown in Figure7.Figure 7
Step response in different controller.From Figure7 it is known that in PI controller converges slowly. However, FBL controller responds quickly and converges fast.In cos signal input, the responses of PI controller and FBL controller are shown in Figure8.Figure 8
Cos input response in different controller.From Figure8 it is known that in PI controller the convergence time is more than a period. However, FBL controller responds quickly and converges fast.


## 5. Simulation Analysis

The simulations are in Matlab/Simulink; the simulation parameters are listed in Table1. The load consists of both linear and nonlinear type. The system is analyzed for different operating conditions as discussed in the following cases.


### 5.1. Case 1: Load Change

Cutting down nonlinear load att=0.105 s, the results in PI controller are shown in Figure 9, and the results in FBL-QSMC controller are shown in Figure 10.Figure 9
Results in load change with PI controller.
(a)
Current results in load change
(b)
Voltage results in load changeFigure 10
Results in load change with FBL-QSMC controller.
(a)
Current results in load change
(b)
Voltage results in load changeIn Figure9(a), the upper part is load current and source current, the total harmonic distortion (THD) of large load current is 16.25%, the THD of source current is 4.98%, the THD of small load current is 12.65%, and the THD of source current is 4.96%. When cutting down the nonlinear load, the THD of load current decreases obviously; however, the ratio frequency harmonic increases; thus the THD decreases a little. The load change means the active power change; thus there is an impulse to direct current error ed. In Figure 9(b), the load voltage increases when load power change is smaller, which is because the load current decreases and the voltage loss decreases. Also there is an impulse to DC-link voltage.In Figure10(a), the upper part is load current and source current, the THD of load current is 16.37%, the THD of source current is 2.58%, the THD of load current is 12.74%, and the THD of source current is 2.55%. When cutting down the nonlinear load, the THD of load current decreases obviously; however, the ratio frequency harmonic increases; thus the THD decreases a little. There is an impulse to direct current error ed; however, convergence is fast; in addition, the direct current error ed and quadrature current error eq are very small. In Figure 10(b), the load voltage increases when load power change is smaller. The DC-link voltage is similar to PI controller, which is because the outer loops are both applying PI control.


### 5.2. Case 2: DC-Link Voltage Change

The reference DC-link voltage changes from 700 V to 680 V att=0.105 s; the results in PI controller are shown in Figure 11; the results in FBL-QSMC controller are shown in Figure 12.Figure 11
Results in DC-link voltage change with PI controller.
(a)
Current results in DC-link voltage change
(b)
Voltage results in DC-link voltage changeFigure 12
Results in DC-link voltage change with FBL-QSMC controller.
(a)
Current results in DC-link voltage change
(b)
Voltage results in DC-link voltage changeIn Figure11(a), the upper part is load current and source current, the THD of load current is 16.24%, and the THD of source current is 5.01%. With DC-link voltage decrease, the compensating current track ability decreases. The compensation harmonic increases more than frequency harmonic decrease; thus the THD increases. The DC-link voltage decrease means exporting active power; thus the source current decreases; there is an impulse to direct current error ed. In Figure 11(b), the load voltage increases when DC-link voltage decreases, which is because the source current decreases and the voltage loss decreases.In Figure12(a), the upper part is load current and source current, the THD of load current is 16.37%, and the THD of source current is 2.55%. With DC-link voltage decrease, the compensating current track ability decreases, and the frequency harmonic decreases. The compensation harmonic increases less than frequency harmonic decrease; thus the THD decreases. There is an impulse to direct current error ed and converge fast. In addition, the direct current error ed and quadrature current error eq are very little. In Figure 12(b), the load voltage increases when DC-link voltage change is smaller. The DC-link voltage response is similar to PI controller which is because the outer loops are both applying PI control.


### 5.3. Case 3: Reactive Power Change

Att=0.105 s without reactive power compensation, the results in PI controller are shown in Figure 13; the results in FBL-QSMC controller are shown in Figure 14.Figure 13
Results in reactive power change with PI controller.
(a)
Current results in reactive power change
(b)
Voltage results in reactive power changeFigure 14
Results in reactive power change with FBL-QSMC controller.
(a)
Current results in reactive power change
(b)
Voltage results in reactive power changeIn Figure13(a), the upper part is load current and source current, the THD of load current is 16.24%, and the THD of source current is 4.95%. Without reactive power compensation the compensating current decreases, which can improve the harmonic current tracking ability; thus the THD decreases. Without reactive power compensation the source current’s power angle is equal to the load current’s, and there is an impulse to quadrature current error ed. In Figure 13(b), the change of reactive power produces a little impact on the load voltage and no impact on DC-link voltage.In Figure14(a), the upper part is load current and source current, the THD of load current is 16.37%, and the THD of source current is 2.46%. Without reactive power compensation, there is an impulse to quadrature current. The tracking current error is obviously smaller than in PI controller. In Figure 14(b), with the reactive power change there is little impact on load voltage and no impact on DC-link voltage.


## 5.1. Case 1: Load Change

Cutting down nonlinear load att=0.105 s, the results in PI controller are shown in Figure 9, and the results in FBL-QSMC controller are shown in Figure 10.Figure 9
Results in load change with PI controller.
(a)
Current results in load change
(b)
Voltage results in load changeFigure 10
Results in load change with FBL-QSMC controller.
(a)
Current results in load change
(b)
Voltage results in load changeIn Figure9(a), the upper part is load current and source current, the total harmonic distortion (THD) of large load current is 16.25%, the THD of source current is 4.98%, the THD of small load current is 12.65%, and the THD of source current is 4.96%. When cutting down the nonlinear load, the THD of load current decreases obviously; however, the ratio frequency harmonic increases; thus the THD decreases a little. The load change means the active power change; thus there is an impulse to direct current error ed. In Figure 9(b), the load voltage increases when load power change is smaller, which is because the load current decreases and the voltage loss decreases. Also there is an impulse to DC-link voltage.In Figure10(a), the upper part is load current and source current, the THD of load current is 16.37%, the THD of source current is 2.58%, the THD of load current is 12.74%, and the THD of source current is 2.55%. When cutting down the nonlinear load, the THD of load current decreases obviously; however, the ratio frequency harmonic increases; thus the THD decreases a little. There is an impulse to direct current error ed; however, convergence is fast; in addition, the direct current error ed and quadrature current error eq are very small. In Figure 10(b), the load voltage increases when load power change is smaller. The DC-link voltage is similar to PI controller, which is because the outer loops are both applying PI control.


## 5.2. Case 2: DC-Link Voltage Change

The reference DC-link voltage changes from 700 V to 680 V att=0.105 s; the results in PI controller are shown in Figure 11; the results in FBL-QSMC controller are shown in Figure 12.Figure 11
Results in DC-link voltage change with PI controller.
(a)
Current results in DC-link voltage change
(b)
Voltage results in DC-link voltage changeFigure 12
Results in DC-link voltage change with FBL-QSMC controller.
(a)
Current results in DC-link voltage change
(b)
Voltage results in DC-link voltage changeIn Figure11(a), the upper part is load current and source current, the THD of load current is 16.24%, and the THD of source current is 5.01%. With DC-link voltage decrease, the compensating current track ability decreases. The compensation harmonic increases more than frequency harmonic decrease; thus the THD increases. The DC-link voltage decrease means exporting active power; thus the source current decreases; there is an impulse to direct current error ed. In Figure 11(b), the load voltage increases when DC-link voltage decreases, which is because the source current decreases and the voltage loss decreases.In Figure12(a), the upper part is load current and source current, the THD of load current is 16.37%, and the THD of source current is 2.55%. With DC-link voltage decrease, the compensating current track ability decreases, and the frequency harmonic decreases. The compensation harmonic increases less than frequency harmonic decrease; thus the THD decreases. There is an impulse to direct current error ed and converge fast. In addition, the direct current error ed and quadrature current error eq are very little. In Figure 12(b), the load voltage increases when DC-link voltage change is smaller. The DC-link voltage response is similar to PI controller which is because the outer loops are both applying PI control.


## 5.3. Case 3: Reactive Power Change

Att=0.105 s without reactive power compensation, the results in PI controller are shown in Figure 13; the results in FBL-QSMC controller are shown in Figure 14.Figure 13
Results in reactive power change with PI controller.
(a)
Current results in reactive power change
(b)
Voltage results in reactive power changeFigure 14
Results in reactive power change with FBL-QSMC controller.
(a)
Current results in reactive power change
(b)
Voltage results in reactive power changeIn Figure13(a), the upper part is load current and source current, the THD of load current is 16.24%, and the THD of source current is 4.95%. Without reactive power compensation the compensating current decreases, which can improve the harmonic current tracking ability; thus the THD decreases. Without reactive power compensation the source current’s power angle is equal to the load current’s, and there is an impulse to quadrature current error ed. In Figure 13(b), the change of reactive power produces a little impact on the load voltage and no impact on DC-link voltage.In Figure14(a), the upper part is load current and source current, the THD of load current is 16.37%, and the THD of source current is 2.46%. Without reactive power compensation, there is an impulse to quadrature current. The tracking current error is obviously smaller than in PI controller. In Figure 14(b), with the reactive power change there is little impact on load voltage and no impact on DC-link voltage.


## 6. Conclusion

The Bode diagram of traditional simplified model is obviously different with complete model, which means the descriptions of the system based on the traditional simplified model are inaccurate and incomplete. Thus, it is necessary to popularize complete model of APF. The proposed feedback linearization and quasi-sliding mode control algorithm has fast response and robustness; the compensation performance is superior to PI control obviously. The simulation results proved that the complete modeling and proposed control algorithm are correct.



---

*Source: 9840657-2017-11-21.xml*