Development of ANFIS Based Controller for Variable Speed
Induction Generator
AbdulQadir O. A 1, Fitri Yakub 2, Andika Aji Wijaya 3, and Mahbubur Rashid 1
121

Graduate School of Mechatronics Engineering, International Islamic University, Malaysia
Malaysia-Japan International Institute of Technology, Universiti Teknologi Malaysia, Malaysia
3
Faculty of Engineering, College of Engineering & Information Technology, Saudi Arabia

Introduction

Induction generators which may be operated in grid or selfexcited mode, are found to be successful machines for windenergy conversion. Self-excited modes is gaining importancedue to its ability to convert the wind energy into electricalenergy for large variations in operating speed [1]. However, it
has been found that these machines exhibits a poor voltage
regulation. Steady-state analysis of self-excited induction
generator reveals that such generators are not capable tomaintain the terminal voltage and frequency in the absence ofexpensive controllers. There have many way to control theterminal voltage through excitation control using series
compensation. In this paper, the adaptive neuron-fuzzy
interference (ANFIS) control is proposed for proper reactive
compensation under different operating conditions for windturbine.
The scope of this study is to design, implement in theprototype and test dc-dc converter control circuit which input isa variable voltage for a wind-energy conversion system that issuitable for grid-connected wind turbine. The control circuit not
only can be implemented for the wind generator but also hybrid
system couple with photovoltaic systems. Many researchers
have been done nowadays to design the speed controller ofinduction generator, but in fact, the contribution of this researchis to design artificial intelligent for push-pull dc-dc converter toimprove the response of the system.
Successful implementation of the control could pave a way
for cheaper cost with high performance of the implementation
speed controller to control the speed of the induction generator.
Due to desirable feature and specifications of the induction
generator, it can be seen in many green house power
applications, including the power systems. As the result, it isvery significant to develop ANFIS control to stimulate the input
voltage of the dc-dc converter; therefore, increase theperformance of the speed controller for induction generator.

This research involved the design of a high-voltage dc-dc
converter capable of converting 12 volt dc into 240 volt ac anddelivering 300 watt of power. The design is based on a push-pull
topology utilizing power switches, a custom center-tapped
transformer, and an all analog feedback control systems. The
design comprised the front-end of a dc-ac sine wave inverter andwas implemented using a custom proto circuit board and tested.
The control circuitry worked as expected by using ANFIS
controller. A generic block diagram of how one of theseconverters works with feedback loop can be seen in Fig. 2.

Fig. 2. Block diagram of generic dc-dc converter.
From the block diagram, it is easy to see that the switches
control the current that gets fed into the transformer. From there,
the transformer creates a magnetic field which induces a voltage
on the secondary side of the transformer. This voltage then,turns on a part of the rectifying circuit and charges a capacitor.
Here, the signal is passed through an LC filter to remove ripples,forming the output of the dc converter. The output iscontinuously monitored by the switching controller to adjust theduty cycle of the switches. This feedback loop is normallyisolated through optical or magnetic when using an isolated
topology.
2.1

2System Description

Total system of power generation from wind turbine isdivided into 5 steps. Block Diagram of the complete system isshown in Fig. 1.

Fig. 1. Total Block Diagram of the System.

Push-Pull DC-DC Converter
The push-pull topology is an ideal choice for this dc-dc
converter for multiple reasons. The most important reason is theisolation between the source and output provided by themagnetic in the transformer [2]. Another deciding factor is thesimplicity of the switching over a full bridge design. By only
having to turn on one switch at a time, timing issues becomeless critical. The other important factor is that the push-pull
topology is commonly used at this power level. This makes thestudy on the topology more reliable and achievable. The ANFIS
controller is implemented to the voltage control of push-pullconverter. The result obtained in section 3.1 proves that
implementation of ANFIS controller system can observe
enhancement in the dynamic response of the system.

2.2

ANFIS-Based Equivalent Control
An adaptive networks architecture which functionallyequivalent to fuzzy inference system was proposes by Jang [3].
It is method for tuning an existing rule base of fuzzy with alearning algorithm based on a collection of training data foundin artificial neural network. Furthermore, ANFIS has much lesstuneable parameters than conventional artificial neural network;
the advantage of ANFIS is that each rule produces one value
rather a distribution.
To develop ANFIS-based inverse model, the input layer has
two nodes which consists of output and input. One Bellmembership function is used for all input nodes since it suitable
membership function for function approximation purpose.
The main aim of ANFIS is to optimize the ANFISparameters. There are two steps in the ANFIS design. Firstly,
the design of the premise parameters, while the other isconsequent parameters training. There are many methods fordesigning the premise parameter such as grid partition, fuzzy cmeans clustering and subtractive clustering. In this study, hybrid
learning algorithm is used to train the ANFIS model. Itcombines the back propagation gradient decent and least squares
methods.
3Result and Discussion

Results
To describe the controller, plant model was taken fromsystem description in Section 2. By applying the controller andcollecting the data from the system, ANFIS controller isdeveloped to control the duty cycle of the converter. The resultshows that, when the input changes, then the ANFIS controller
will change the duty cycle accordingly to the output voltage.
The evolution of training error is present and it shows that
network error is convergent at 500 epochs. The root meansquared error (RMSE) of the network is equal to 0.05 at the end
training process; there is evolution of the membership function.
After ANFIS train the data and ANSIF block set up themembership function. The data inhere in the simulation tocontrol the output voltage and compare with voltage reference.
The ANFIS input is voltage error and ANFIS output is dutycycle.
Results also shows that, duty cycle was varying between
0.49 to 0.23. In converter control, the operation of single phase
inverter is discussed. Push-pull converter control the voltage andfeed the constant voltage to the inverter. The inverter convert
240V dc into 240 ac with 50 Hz and ready to used. The
harmonic component magnitude and phase are shown in Table1.

3.2

Discussion
The input is fed by 12V dc from the diode rectifier and the12V will step up by the transformer from 12V dc to 240V ac.
The voltage coming out of the dc-dc converter will comparewith voltage reference, and the error will send to the input
ANFIS controller. ANFIS controller will send command to theduty cycle from the output of ANFIS controller and the duty
cycle will change to the max which is 0.49 and will not excess
more than 0.49. Otherwise the transformer will damage. Afterchanging the duty cycle by ANFIS controller, the duty cycle
give the correct pulsing to the switches, and the current willcross the transformer and the diode rectifier deliver the current
to the inductor , then to the LC filter which have the desired
output voltage.
When the input voltage is low, the ANFIS controller force
the duty cycle to increase till reach the desired output. Whereas,
when the input voltage is high, ANFIS controller command theduty cycle to decrease till reach the desired output voltage.
Voltage reference compares the output voltage coming from thepush-pull converter and will send the error to the ANFIS input.
Furthermore, the ANFIS output will send the desired duty cycle
after calculating the error and duty cycle will reset the command
coming from the output voltage. At 12V input it takes more time
to reach the steady state, whereas at 24V input, it more smoothand quickly to reach the steady state.

3.1

Table 1. Fundamental and Harmonics of The Inverter

4Conclusion

In this paper, wind turbine power conversion project, thatneed for 12-24 dc volt to 240 ac volt converters was presented,
especially when a requirement is pure sine wave. Complete
project was split into some part such as rectifier, dc-dc boost
converter and sine wave inverter. For the desired power ratingof 300W, a push-pull inverter topology seems to work best with
an efficiency rating of 85% at 350W.
Part of the goals for this paper was to produce a pure sine
wave dc or ac inverter that would give output at 50 Hz, 240
volts root mean square with 250 watt output, would be cheap tomanufacture, and fairly efficient in the method in which it
produced. Based on the result achieve from simulation andexperimental, it can be said that goals and objective were met.
For variable speed induction generator, ANFIS based
control system is developed that keeps the output ac voltage ofinduction generator at constant magnitude and frequency eventhe speed of the wind turbine is varied. Here, single phaseinduction generator output voltage is rectified then dc-dc boost
conversion is done using PWM inverter that convert
to constant frequency ac voltage.
Acknowledgement
This research is supported by Malaysia -Japan
International Institute of Technology (MJIIT),
Universiti Teknologi Malaysia Kuala Lumpur .
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