Research article

1. Design of Adaptive Sliding Mode Controller for
Single-Phase Grid-Tied PV System
Kamran Zeb∗†, Saif-ul-Islam∗, Waqar Uddin∗,
Imran Khan¶, Muhammad Ishfaq∗, Zahid Ullah‡, T.D.C. Busarello§, Hee Je Kim∗
∗School of Electrical Engineering, Pusan National University, Busan, South Korea
†Dept. of Electrical Engineering, National University of Sciences and Technology, Islamabad, Pakistan
‡Electrical Engineering Department, University of Management and Technology, Sialkot, Pakistan
§Department of Engineering, Federal University of Santa Catarina Blumenau, Rua Joao Pessoa, Brazil
¶C2N, University of Paris Sud, University of Paris Saclay, Palaiseau, France
kamran.zeb@pusan.ac.kr, engr.saifulislam19@gmail.com, waqudn@pusan.ac.kr,
imran.khan@c2n.upsaclay.fr engrishfaq1994@pusan.ac.kr,
zahid.ullah@skt.umt.edu.pk, tiago.busarello@ufsc.br, heeje@pusan.ac.kr
Abstract—This paper proposed Fuzzy-Sliding Mode Controller
(F-SMC) for regulation of DC-link voltage and Proportional
Resonant (PR) with Resonant Harmonic Compensator (RHC)
for output current control of two stages 3 kW single-phase
grid-tied Photovoltaic (PV) system. The dynamics of the system
are tested with and without a feed-forward PV power loop.
A SOGI phase lock loop is implemented that has harmonic
insusceptibility, a fast-tracking accuracy, and rapid-dynamic
response. The proposed controller enhances the dynamic and
steady state performance of the overall system. Furthermore,
the simulation results of PI controller is also presented to show
the effectiveness of the proposed control strategy. A graphical
and tabulated comparative assessment with a well-tuned PI
controller authenticates the effectiveness, fastness and robustness
of proposed controller. MATLAB/Simulink R2017b software is
used as a design and implementation platform.
Index Terms—Photovoltaic, Grid-tied, PI Control, Fuzzy-
Sliding Mode Control, SOGI PLL.
I. INTRODUCTION
The dilemma of continuous depletion of fossil fuel reserves
and increasing energy demand has compelled the modern
world to tend towards renewable energy resources because
of their sustainability, eco-friendly and everlasting nature [1].
In the near future, Photovoltaic (PV) power will be a vital
character of the hybrid power grid due to an abrupt increase
in the installation of PV through the past several years [2].
According to energy forecast, the PV power installed capacity
will supersede wind power by 2020 [3]. An electronics-
based voltage-source inverter (VSI) is employed to deliver PV
power to utility grid, mostly single-phase VSIs are used to be
connected with distribution grid [4].
The stability of PV output for connection with grid is an
important factor as the PV output power has a non-linear
unstable behavior. Various grid codes have been introduced
to ensure the fast control, robustness and high quality of grid
power to be injected [5]. Usually, a PV system comprises
two-stages having their own control structures which are DC-
DC converter at the input side and DC-AC inverter at the
output side [6]. Input side control is used for extraction of
maximum power with maximum power point tracking (MPPT)
algorithm and output side control is responsible to deliver that
extracted power to utility grid efficiently [7]. The DC-link
split capacitor is used for voltage regulation as it can perform
many essential functions like storage of energy, reduction of
ripples, minimize fluctuations for inverter‘s input and offers
flexibility between the two-stage to alternate instantaneous
power [8]. Similarly, the DC-AC inverter stage has other
essential duties such as synchronization, detection of islanding,
compensation of reactive power, low/high ride through for
voltage and frequency and insertion of quality current to the
grid [2]. The power quality of the PV system is evaluated by
harmonics, unbalance, flicker and slow variations in voltage
[9].
Nowadays, Transformerless Grid-Connected (TG) low rat-
ing i.e., 1 to 10 kW PV inverters are achieving a high range
of acceptability. Due to the small size of TGPV inverters
have low cost, light weight, high efficiency and much simple
as compared to transformer isolation-based inverters. A large
range of highly efficient PV inverter has been analyzed in the
novel Transformerless topologies achieved from Neutral Point
Clamped (NPC) and H-bridge topology with high proficiency
and low Electro-Magnetic Interference [3]. Although TGPV
has plenty of merits but having some concerns about leakage
current. In Reference [3], [10] various features, problems, and
TGPV trends in the future are thoroughly reported. A keen
analysis of DC-current injection and issues that can arise are
illustrated in Reference [10].
The effectiveness of energy transmission from the PV
system to AC-grids through inverters have deeply emphasized
978-1-7281-5404-6 ©2019 IEEE
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2. Fig. 1. Schematic of the proposed model for a grid-tied PV system.
by the researchers. Most of them have focused on control
schemes, inverter topologies and design of controller, etc.
Generally, the current control loop is executed by three various
reference frames i.e., stationary frame (αβ), rotating frame
(dq) and natural frame (abc). However, to optimize and control
the transient and steady-state response of grid-tied PV system
different types of controllers are designed and examined such
as Proportional Resonant (PR) controller in collaboration with
resonant harmonic compensators (RHC), repetitive controller,
deadbeat controller and Sliding Mode Controller (SMC) [11]–
[13]. Moreover, the PI controller along with feedforward volt-
age of the grid, artificial-intelligence technique based fuzzy-
logic, Hysteresis controller, neuro-fuzzy controller and some
adaptive controllers have been proposed in Reference [13]–
[19].
An adaptive frequency-selective harmonic controlled
method is designed for a PV system connected to the grid
[11], however, adaptive SMC control is proposed for a
two-level cascaded inverter in Reference [13]. A completely
digital controller hysteresis current is proposed for the
regulation of grid-tied PV output current in Reference
[25]. Further, in Reference [16], a neuro-fuzzy based on
DSPAC control is given. Although the merits and demerits
of the above-mentioned control schemes for transient and
steady-state behavior are given in literature however, these
controllers have contributed effectively in the improvement of
grid-tied PV system performance. But still, these controllers
have not carried out the comparative analysis for PR with
RHC controller, Fuzzy-PI and Fuzzy-SMC with feedforward
and without feedforward power loop for STGT PV inverter.
The main contributions of the paper to overcome the above-
mentioned detailed problems are:
• Fuzzy-Logic based on Sliding Mode Controllers (F-SMC)
is proposed to control the DC-link voltage.
• To control the current of grid-tied PV inverter, PR with
RHC is implemented.
• PLL based on SOGI technique is adopted having fast-
dynamic behavior, harmonic insusceptibility and fast-
tracking with high accuracy.
• A conventionally adopted well-tuned PI controller‘s re-
sponse is carried out for comparative analysis of proposed
controllers considering oscillations, rising time, settling
time, overshoot and undershoot etc.
• The performance evaluation of the proposed controllers is
carried out by using performance evaluation indices i.e.,
Integral Absolute Error (IAE) and Integral Square Error
(ISE).
• The Total-Harmonic-Distortion is calculated for grid volt-
age and current based on discrete samples through the
PLECS library.
The rest of the manuscript is structured as Section II
describes proposed model of grid-tied PV system, the design
of control structure is detailed in Section III, Section IV
presented the design and implementation of proposed (F-SMC)
controller, results are inspected/validated in Section V, lastly,
Section VI presents conclusion of this paper.
II. PROPOSED MODEL OF GRID-TIED PV SYSTEM
The efficient control at the various stages is important for
two-stage PV system connected to the grid e.g. maximum
extraction of PV power using the MPPT algorithm, injection
of excellent current (power) quality at the inverter side, and
auxiliary roles at the grid side. Considering solar irradiance
(mission profile) and ambient temperature is vital during
planning and design stages as it disturbs the PV energy [20],
[21]. A single-phase two stages grid-tied PV inverter (3 kW) is
presented in Figure 1. Table I tabulates the nominal parameters
of the system. MATLAB/Simulink R2017b software is used
as a design and implementation platform. The detailed design
of the proposed system is given in [22]. A Phase Lock
Loop (PLL) based on Second Order General Integral (SOGI)
is implemented that has a fast-tracking accuracy, harmonic
immunity, and fast-dynamic response.
III. DESIGN OF CONTROL STRUCTURE
There are two cascaded loops in the generic control ar-
chitecture of a single-phase grid-tied system. The current
control loop is the internal loop and the power or voltage
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3. TABLE I
SPECIFICATION OF GRID-TIED PV SYSTEM
Parameter Symbol Value
Grid voltage (RMS) Vg 230 V
Switching Frequency of Inverter finv 10 kHz
LCL-Filter L1, Cf
1.8 mH, 2.35 μF,
1.8 mH
Grid Operating Frequency ωg 314 rad/sec
Reference DC-link voltage V ∗
dc 400 V
Grid- impedance Lg, Rg 0.5mH 0.2Ω
Boost Inductance Lb 2 mH
DC-link voltage capacitance CDC 2200 μF
Boost-converter switching frequency fb 20 kHz
control loop is the external loop. The power or voltage loop is
used to generate required current references, the current loop
is accountable for power quality and protection issues [23].
Using vα and vβ generated by the orthogonal signal generator
the active and reactive power is calculated, conferring to
single-phase PQ theory.
P =
1
2
(vαiα + vβiβ)
Q =
1
2
(vβiα + vαiβ) (1)
In Eq. 1 Q is reactive power, P is active power, vαβ is
grid voltages in a stationary reference frame, iαβ is the grid
currents in a stationary reference frame. The current reference
can be calculated from Eq. 1 as:
iα =
2 (vαP∗
+ vβQ∗
)
v2
α + v2
β
iβ =
2 (vβP∗
− vαQ∗
)
v2
α + v2
β
(2)
In Eq. 2 the reference signals are presented with *. In terms
of grid references Eq. 2 can be modified as:
i∗
g = i∗
α =
2
v2
α + v2
β
vα vβ
P∗
Q∗
(3)
The overall control assembly is demonstrated in Figure 2
(a) (b). Two control structures are considered (a) with a
feedforward loop of PV power and (b) without feedforward
loop of PV power. The control and dynamics are improved in
the feedforward loop of PV power. A PI controller is used for
DC-link voltage regulation as shown in Eqn. 4.
GP I(s)/DC − link = kp +
ki
s
(4)
Where kp is proportional and ki is integral gain. Eq. 3 is
used for reference current generation. A Proportional Resonant
controller with Resonant Harmonic Compensator is used as a
current controller. The PR with RHC eliminates third, fifth,
(a)
(b)
Fig. 2. Proposed Control diagram (a) with and (b) without feed-forward PV
power
Fig. 3. The Fuzzy-Sliding Mode Controller
and seventh harmonics [24], [25]. The final equation for PR
with RHC is presented in Eqn 5.
GP I(s)
CC
=
PR
kp +
krs
s2 + ω2
0
+
RHC

4. h=3,5,7
kihs
s2 + h2ω2
0
(5)
IV. DESIGN OF FUZZY-SMC CONTROLLER
In the control structure of Fuzzy-Sliding Mode Controller
(F-SMC), two non-linear controllers i.e. Fuzzy-PI and Sliding
Mode Controller (SMC) are combined to make a hybrid
controller. Figure 3 presents the design of F-SMC, in which
the advantageous of two controllers are combined. For Fuzzy-
PI, Fuzzy IF-Then rules are used to updates the PI controller
gains kp, and ki [26], [27]. The rules employed are shown in
Table II. The Fuzzy-PI part reduces chattering and minimizes
steady state error in response. The SMC part enhances system
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5. TABLE II
FUZZY IF-THEN RULES
If-THEN Rules
Input Membership
Function
Output Membership
Function
If
Input
Then
Output
Linguistic
Terms
Range
Linguistic
Terms
Range
Zero Zero Zero [0, 0.2] Zero [0, 0.2]
Large Large Large [0.8, 1.0] Large [0.8, 1.0]
Small Small Small [0.3, 0.7] Small [0.3, 0.7]
stability, provides a fast-dynamic response, and active during
the transient state of the system. The design of SMC consists
of two stages. Stage one is the design of Sliding Surface (SS)
and stage two is the control law that dictates the controller
to minimize error abruptly. The details of designing sliding
surface and control law for a given system is discussed in
[28], [29]. Error and derivative of error calculate the SS as:
S(t) = ė(t) + λe(t) (6)
Whereas λ is the bandwidth dependent and an arbitrary
constant. In SMC error and derivative of error is continuously
coordinated towards SS. In addition, λe(t) is defined as:
λe(t) = X1L1e(t) + X2L2
e(t) (7)
The Fuzzy-PI updates the λe(t) part. The control law is given
as:
v∗
DC/I∗
g = −Usgn(S) (8)
where v∗
DC/I∗
g are reference for DC-link voltage and grid
current, U is positive constant, and S is sliding surface. The
sgn function is defined as:
sgn (S(t)) =
U if S 0
−U if S 0
(9)
The control law designed above is discontinuous and causes
chattering and oscillation in the electrical system where PWM
is utilized. Therefore, sgn function is substituted by sat func-
tion to have steady control law as:
v∗
DC
i∗
g
= −Usat (σ; ) =
−U
S
|S| +
· 0 ≈ 0 (10)
V. SIMULATION RESULTS AND DISCUSSION
Case 1 and Case 2 in Figure 4 and 5 success-
fully authenticates the efficacy of the designed con-
troller and the overall system performance. Using MAT-
LAB/Simulink/Simscape/PLECS as an implementation plat-
form, a single-phase two-stages grid-tied inverter (3 kW)
having LCL filter is designed. Table I tabulates the nominal
parameters of the system. Table III gives PV panel specifi-
cations. Controllers parameters are given in Table IV. Three
strings are connected in parallel and there are 15 PV modules
in a string and. The details of the system are given in [22]. The
purpose of this section is to verify the performance of F-SMC
and compare it with the traditionally tuned PI controller.
TABLE III
PV PANEL SPECIFICATION
Parameter Value
Nominal power (1000 kW/m2, 25 °C) Pmpp = 65 W
Voltage at MPPT Vmpp = 17.6 V
Current at MPPT Impp = 3.69 A
Short circuit voltage VOC = 21.7 V
Short circuit current ISC = 3.99 A
TABLE IV
CONTROLLER PARAMETERS
Control Name Constants Values
Without Feed Forward Loop of PP V
PI
kp 32×400
ki 280×400
F-SMC
k1 280
k2 2980
150
With Feed Forward Loop of PP V
PI
kp 32×400
ki 280×400
F-SMC
k1 280
k2 2980
150
PR + RHC
kp 22
kr 2000
k3
i 3rd harmonic compensation 1200
k5
i 5th harmonic compensation 800
k7
i 7th harmonic compensation 200
Case 1 is the analysis of various parameters (results) without
feed-forward loop of PP V and case 2 is with feedforward
loop of PP V for both F-SMC and PI controllers. The graph-
ical and tabulated analysis is performed to authenticate the
robustness of designed controllers. The tabulated analysis is
shown in Table V. In which Total Harmonic Distortion (THD)
(grid current and voltage), Integral Absolute Error (IAE), and
Integral Square Error (ISE) are calculated for the current
controller loop and DC-link loop. The lower the values of these
parameters the superior is the performance of the system as
these values give precise and exact comparisons. The F-SMC
value is lower indicates the high behavior in comparisons to
PI. In addition, the dynamics of the control loop is enhanced
to a great extent with the inclusion of feedforward loop of PV
power indicated by lower values of these parameters.
The graphical analysis consists of Figure 4 and 5 (a) to (f)
i.e. (a) Solar Irradiance and DC-link voltage, (b) input power
(PP V ), (c) PR with RHC (current control loop), (d) PV panels
voltages, (e) PV panels currents, and (f) grid voltages for both
PI and F-SMC controllers. The results of F-SMC are robust,
with less oscillation, faster, efficient, chattering, and allowable
overshoot, undershoot, rise time and fall time.
VI. CONCLUSION
The proposed control strategy shows better response in term
of rise time, settling time and overshoot. The effectiveness
of response is reflected in simulated. With the inclusion of
feedforward loop of PP V , the responses of current control
loop and DC-link voltage loop are optimum, insensitive to
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6. TABLE V
PERFORMANCE OF THE DESIGNED CONTROLLERS
Controllers Designed
DC Link Current Controller THD
ISE IAE ISE IAE Vg Ig
Without Feed-Forward Loop of PP V
PI 0.003371 0.04815 4.202 1.0305 4.8970 6.8970
F-SMC 0.000769 0.02316 3.308 0.8936 3.0980 1.5560
With Feed-Forward Loop of PP V
PI 0.000445 0.01923 3.4570 1.0330 10.570 3.3882
F-SMC 0.000232 0.01360 2.5940 0.87109 2.9910 1.4521
Fig. 4. (a)Solar Irradiance and DC-link voltage, (b) input power (PP V ), (c) PR with RHC (current control loop), (d) Voltages of PV panels, (e) PV panels
currents, and (f) grid voltages for both PI and F-SMC controllers.
Fig. 5. (a) Solar Irradiance and DC-link voltage, (b) input power (PP V ), (c) PR with RHC (current control loop), (d) Voltages of PV panels, (e) PV panels
currents, and (f) grid voltages for both PI and F-SMC controllers.
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7. parameter variation, faster, stable, and robust. The PV panel
power is improved, and the quality of grid voltage and current
is enhanced. Moreover, the proposed controllers enhance the
dynamic and steady state performance of the overall system.
The graphical results (current, voltage, power) and tabulated
values of Integral Absolute Error (IAE), and Integral Square
Error (ISE)) and THD shows the effectiveness, fastness and
robustness of proposed strategy.
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