High-Performance Double Boost DC-DC Converter Based on Fuzzy Logic Controller

Difference types of DC-DC converter are used in various electronic devices and applications for so many years. But conventional converter cannot afford in high voltage and high current applications. Many researchers have been tried to full-fill the requirements. In this paper, dual stage double boost DC-DC converter is used for data center, high voltage vehicles and renewable system. Many control methods are developed for the control of DC-DC converter. To obtain a control method has the best performance under any condition is always demand. The main objective of this paper is to study the voltage mode control of proposed converter based on fuzzy logic controller (FLC) under the response of different parameters of proposed converter using Matlab/Simulink Software.


INTRODUCTION
DC-DC converters are used in many different applications like electric vehicles, distributed DC systems, electric traction, machine tools, fuel cell, special electrical machine drives and solar PV based applications. DC-DC converter can convert low input voltage to high output voltage (required voltage) [1]. But, the basic boost topology does not provide a high boost factor. This has led to many proposed topologies [1]. If a very high voltage gain is required, it may be more beneficial to use of two or more series connected (cascaded) boost converters. This approach gives some advantages, but it creates new challenges in the same time. Main advantages include a high voltage gain, a good power decoupling between the output and input, better utilization of semiconductors, presence of an intermediate DC bus. Main drawbacks are more complex circuit, more complex controls and a potential stability problem [2]. DC-DC boost converter is specialized making control in this paper. Schematic diagram of DC-DC boost converter in solar energy application system is described in Figure. 1.
The classical control methods employed to design the controllers for double boost converter depends on the operating point so that it is very difficult to select control parameters because of the presence of parasitic elements, time varying loads and variable supply voltages [3]. Conventional controllers require a good knowledge of the system and accurate tuning in order to obtain the desired performances [5]. Neural Network Controller (NNC) are gaining popularity in modeling, identification and control of power electronic converters [6]. The linear controllers such as Proportional (P), Proportional-Integral (PI) and Proportional-Integral-Derivative (PID) control were widely used to control the active performance of the converter [4]. However, the linear control of converter is not sufficient to face the changes in line voltage or load current. Hence non-linear controlling techniques such as Fuzzy Logic Control (FLC), Neuro-Fuzzy Logic Control (NFLC), Adaptive Neural Network (ANN) and Genetic algorithm (GA) controlling techniques are implemented to increase the performance of the converter [7]. In this regard, the objectives of this study are to propose a simple and efficient method of advanced converter based on the properties of simple boost converter topology and to analyse the performance of proposed method for the voltage loop. The main objectives are to make the constant output voltage to track and to regulate the output dc voltage to desired reference voltage.

Design Operation Of Double Boost DC-DC Converter
The double boost DC-DC converter will operate in Continuous Conduction Mode (CCM). The voltage gain of the converter is the product of the voltage gain of each stage. The transistor Q 1 and diode D 1 have to handle the intermediate voltage V 1 , while the transistor Q 2 and diode D2 have to handle the output voltage V out . For a large voltage gain cascading of two or more boost converters lead to significant reduction of the required transistors power rating, but in the same time it increases required diodes power rating by number of cascaded converter stages [8].  . Each inductor has its own switch and thus is similar with the cascading of two single/classic converters. The value two capacitors is different because different voltage storage of the each capacitor.
Electronic copy available at: https://ssrn.com/abstract=3393499 Where i 1 is the current through inductor/transistor Q 1 , i 2 is the current through inductor/transistor Q2, i o is the output current through load RL and C is the smoothing capacitor.

For switch OFF state; (Charge time)
For the charging interval (Q 1 = Q 2 = OFF), the voltage across each inductor is V in & V 1 and the currents i 1 (t) and i 2 (t) will be as following.
To get duty ratio for single converter; The inductor value can be chosen by using the following equations.

METHODOLOGY OF THE PROPOSED SYSTEM
TS type fuzzy logic controller is implemented in the proposed system in form of cascaded design.
It is used to control the voltage mode and to get constant output voltage in non-linear condition.
TS controller has two input and one output for the double boost converter. The overall schematic diagram is shown in Figure 5. The control command is based on a fuzzy logic technique, a relevant strategy offering outstanding performance. The input voltage range of converter is considered between 12 V and 60V. The voltage range of converter is setup from 12 to 400V. Electronic copy available at: https://ssrn.com/abstract=3393499

FUZZY LOGIC CONTROLLER IMPLEMENTATION DETAILS
The FLC controller is very powerful in the non-linear system. Mamdani inference system and Takagi-Sugeno inference system are commonly used in the control system [7]. Takagi-Sugeno inference (TS) system is used in this paper. The step by step basic operation of the fuzzy logic controller is shown in Figure 6.

Fuzzification
The membership function values are assigned to the linguistic variables using nine fuzzy subsets.

Inference engine
Sugeno method is used with Min-Max operation fuzzy combination. Fuzzy inference is based on fuzzy rules. Rules are framed in inference engine block. The output membership function of each rule is given by MAX (maximum) operator and MIN (minimum) operator.

Defuzzification
The output of fuzzy controller is a fuzzy subset. As the actual system requires a non-fuzzy value of control, defuzzification is required. Defuzzifier is used to convert the linguistic fuzzy sets back into actual value. Centriod defuzzification method is used in this system.

FLC input and output description
The inputs to the TS type FLC voltage mode controller are  7) Positive Large (PL) In most of fuzzy controller antecedent part has multiple parts; the following rule is used in this system: FR: If E is NVL AND CEV is PVL THEN U is ZE E and CE are input variables which in design controllers defined by fuzzy logic input, U is output variable, NVL and PVL are the Linguistic variables that can be defined by fuzzy set, the part of "E is NVL" is called the antecedent part and the part of "U is ZE" is called the consequent or conclusion part. The rest of other rules are built in this way. The output of the FLC is U (duty cycle value). Inference system of all the rules is Min-Max operation. Centroid defuzzification method is used in TS controller. The input membership function of voltage error (EV), change in voltage error (CEV), the output membership function (duty cycle value (U)) and control surface of the proposed system are shown in Figure 10, 11 and 12. Electronic copy available at: https://ssrn.com/abstract=3393499 The output for the fuzzy logic block is the duty cycle change in order to achieve the desired duty cycle. Seven memberships function are used for each input and output in fuzzification step. The choice of seven memberships gives to the system better representation and precision [5]. After that, the second step which is the fuzzy rule base comes which is a collection of rules that allows linking the fuzzy variables of input and output. The description of the control is via these rules. It collects various combinations between the membership functions of the two inputs to generate the appropriate duty cycle change value. After the inference step, the overall result is a fuzzy value. This result is defuzzified to obtain a final crisp or non-fuzzy output. Several defuzzification methods can be used such as center of gravity.

RESULT AND DISCUSSION
The power switching device that is used to develop the simulation of boost converter is MOSFET. This is because the characteristics of MOSFET are fast switching due to its operating frequency is very high. While designing the DC-to-DC boost converter, the parameters value of design requirement has been set. The voltage range of converter is setup from 12V to 400V, switching frequency that is used is about 48 kHz and the load resistor is fixed at 3000Ω. The overall proposed system simulation diagram is shown in Figure 13. The simulation results of output voltage for double boost converter with fuzzy logic controller have shown at Figure. 14-17. All of results are achieved from FLC with two scaling gain k p =0.005 and k d =0.0015. When different range of incoming DC voltage is supplied to converter system, the desired output voltage is achieved with the minimum overshoot/ undershoot effect. Electronic copy available at: https://ssrn.com/abstract=3393499 Electronic copy available at: https://ssrn.com/abstract=3393499 According to Table 2, the characteristic of different simulation results with different input voltages can be seen clearly.

CONCLUSIONS
Control system is very important role in power electronic switching control system to stable the system performance. Fuzzy logic controller is designed in order to control the converter output voltage. This paper represents the proposed converter control design and TS Rule Base Model. Simulation results of the proposed system show the ease of applying fuzzy logic control to double boost dc/dc converters, as an interesting alternative to conventional techniques. According to the simulation, the output voltage of the converter with FLC has minimum overshoot and produces high output voltage gain. But this control design can very well operate even 12V input. This design can also work for other high input voltage range to get stable constant output voltage.