In order for the **ANFIS** to work in any given application it is necessary to firstly perform training on the network. This training stage is much the same as the training stage of a Neural Network. The **ANFIS** is presented with a set of training data, which consists of a number of inputs and the expected outputs. Training is then completed to minimize the error between the actual output and the expected output. There are two adaptive nodes which are trained in the **ANFIS** – the fuzzy logic sets in layer one and the consequent parameters in the fourth layer. This training is typically supervised by a hybrid training algorithm which features a forward pass and a backward pass phase. The forward pass phase of this training the node outputs are fed forward until layer four. In this stage the consequent parameters in layer four are then tuned using the least squares estimation method. The least squares method is designed to minimize the sum of the squared error of the system output. In the back pass phase of the hybrid algorithm the membership sets in layer one are tuned. In this part of the training the error signals are propagated backwards from the output and the membership parameters are optimized using the gradient descent algorithm. The gradient descent algorithm, which is also typically employed in neural network training, finds the minimum error by moving the membership parameters a distance which is proportional to the functions gradient at the given point. This movement is performed in every training iteration until the output error is sufficiently minimized.

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After the neural network architecture is modelled, the next stage defines the learning model to update network parameters. By this learning capability, it makes the ANN suitable to be implemented for the system with motor parameters which are difficult to define and vary against with environment. The training process minimizes the error output of the network through an optimization method. Generally, in learning mode of the neural network controller a sufficient training data input-output mapping data of a plant is required. Since the motor parameters of the induction motor drive vary with temperature and magnetic saturation, the online learning Back propagation algorithm is developed. **Based** on the first order optimization **scheme**, updating of the network parameters is covered. The performance index sum of square error is given by

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controller is most challenging task for DC-DC converters. There are linear and non-linear controllers. Non-linear controllers are more accurate as compared to linear controller [3]. In traditional controller, application of linear **control** theory **based** on linearised model. A linear **control** method fails to respond properly to any variation in the operating point and load disturbance. To overcome these issues, nonlinear controller can be used which are more robust and faster dynamic response [4]. There are many non-linear **control** schemes, such as fuzzy logic **control**, current-mode **control** and sliding mode **control** proposed for DC-DC **converter**. Due to simple and model free implementation sliding mode **control** and fuzzy logic **control** can be applied with satisfactory results [4], [5]. Out of this controller sliding mode **control** is powerful method which able to makes the system very robust. The system with sliding mode **control** avoided effects of modeling uncertainties, fluctuations and disturbance of parameter and load variations. The advantages of sliding mode controller are robustness and stability [4]. Due to this reason sliding mode **control** technique has gained popularity in the applications involving **converter** and inverters [5].

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any mechanical device or mechanical technique to extract power but it works on **control** algorithm specially designed for a particular task. MPPT can be used along with with a mechanical tracking system, but both the systems act differently in case of power tracking. MPPT algorithms use the variation of irradiance and temperature to obtain or extract the maximum power from solar PV array. The voltage at which PV array can gives maximum power is called ‘maximum power point’ (or peak power voltage). Maximum power depends on solar radiation, ambient temperature and varies accordingly to the changes of these parameters. A characteristic PV module generates power having maximum power voltage of around 17 V measured when temperature of the cell is 25 degree Celsius, it can go down up to 15 V on a very hot day and it can also elevate to 18 V on a very cold day. The first and foremost principle of MPPT is to extract maximum power from the PV module by the application of suitable algorithm. MPPT Algorithm operates on the simple logic that, MPPT calculates the output of PV module, then compares it to voltage of battery then fix the optimum power which can be generated by PV module which helps in charging of battery and then converts it to the suitable voltage to obtain maximum current into battery. It can also use to supply power to a DC load, which is connected directly to the battery. MPPT is generally used to charge the deep discharged batteries mostly on cloudy days or time of faults

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Modulation (PWM) [2]. The conventional PWM controlled power electronics circuits are modelled **based** on averaging technique and the system being controlled operates optimally only for a specific condition [3]-[4]. The linear controllers like P, **PI**, and PID do not offer a good large-signal transient (i.e. large-signal operating conditions) [4]-[5]. Therefore, research has been performed for investigating non-linear controllers. The main advantages of these controllers are their ability to react immediately to a transient condition. The different types of non-linear analog controllers are: (a) hysteretic current-mode controllers, (b) hysteretic voltage-mode/V2 controllers, (c) sliding- mode/boundary controllers. Advantages of hysteretic **control** approach include simplicity in design and do not require feedback loop compensation circuit. M. Castilla [6]-[7] proposed voltage-mode hysteretic controllers for synchronous buck **converter** used for many applications. The analysis and design of a hysteretic PWM controller with improved transient response have been proposed for buck **converter** in 2004.

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Abstract - Power factor correction of **boost** **converter** is done by using predictive **control** strategy. In this paper predictive **control** algorithm is presented **based** on this algorithm all of the duty cycles required to achieve unity power factor in one half line period are calculated in advance by proportional Integral (**PI**) controller, the simulation results show that the proposed predictive strategy for PFC achieves near unity power factor. The power factor and input current distortion are analyzed using with **control** and without **control** techniques. Simulation results are shows that the power factor is higher than 0.99, and current total harmonics distortion (THD) is smaller than 20% under full load condition.

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In this paper, the voltage regulation problem associated with mode switching in low voltage hybrid system has been addressed .This paper presents a hybrid zero voltage-switching (ZVS) isolated front end interface dc–dc **converter** which combines a **boost** half bridge (BHB) cell and a full-bridge (FB) cell, so that two different type of power sources, i.e., both current fed and voltage fed, can be combined togetherly by the proposed soft switched **converter** for various applications, such as pv cell and wind energy. By using two high-frequency transformers and a combined leg of switches, number of switches and gate driver circuits can be minimized. By phase-shift **control**, the **converter** can achieve ZVS turn-on of active switches and zero-current switching (ZCS) turn-off of diodes. In this paper, derivation, analysis, and design of the proposed **converter** are presented. Intelligent Adaptive Neuro-Fuzzy Inference System (**ANFIS**) **based** supervisory EMS(Energy Management System) controls the charge/ discharge of the energy storage system (ESS) when there is voltage changes to cooperate with ANFISPID in point of common coupling( PCC) voltage regulation. Finally, a 5–10V input, 600–700Voutput prototype with a 600W nominal power rating is built up and tested to demonstrate the effectiveness of the proposed **converter** topology.

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Abstract—Positive output re-lift Luo **converter** is a recently developed DC-DC **converter** which performs the conversion from positive source voltage to positive load voltage and are used in computer peripherals, dc drives, industries and other high voltage projects. Voltage lifting technique is employed and hence the output voltage increases in an arithmetic progression unlike classical **boost** **converter**. This paper presents the closed loop **control** of positive output re-lift Luo **converter** with Proportional-Integral controller. **PI** controller is capable of providing good static and dynamic performances and can be used to analyze the system performance under disturbances. Using state space averaging technique dynamic equations can be derived and **converter** is modeled. **Control** algorithm such as Cuckoo and Particle Swarm Optimization are implemented to track output voltage with respect to the reference voltage. These optimization techniques reject the system disturbances at line and load side, hence steady state can be reached with less overshoot and settling time. The simulation model of the proposed **converter** is implemented in Matlab/Simulink and Cuckoo technique is compared over PSO.

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Abstract: In this paper, an attempt has been made to highlight the importance of optimizing parameters of **PI** controller to **control** the speed of DC drive fed by the **boost** **converter**. In this paper, the designing procedure of **boost** **converter** is presented to minimize the switching losses. The effectiveness is examined in open loop and closed loop operations. The conventional DC motor and brushless DC motors speed can be controlled to a preset value by choosing the appropriate **control** parameters using effective algorithm. In this, the objective function formulated is **based** on the performance times. The stated hypothesis is verified using necessary diagrammatical and numerical results.

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The unidirectional **boost** **converter** achieves an interface between the battery and the rectifier capacitor and ensures the rapid transfer of power. When Vdc ≥ Vb, the **boost** **converter** is not working, and the current provided by the generator is channeled through the bypass Schottky diode Ds.It is assumed that there is no power loss in the **converter**. The input and output signals of the **boost** **converter** are modeled by two controlled current sources The reference current (I Lconv) is supplied by the maximum power point tracking (MPPT). The error between the reference current and the measured current (ILconv) is applied to a proportional integrator (**PI**) regulator. The output of the regulator is summed with the positive voltage reaction, which realizes Vdc/Vb. The modulation factor D is obtained, which is used as a reference for the PWM generator, The modulation factor provides the **control** signal for the converter’s switching device ST . In order to **control** the generator current and to provide over speed limitation, our research team proposed in a **control** method which is applicable to the dc **boost** **converter** block diagram analyzed . Also, the operation of the PMSG rectifier is characterized by variable frequency and variable voltage, as the wind turbine rotor speed varies.

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ABSTRACT: A novel synchronous double- stage buck-**boost** **converter** with **PI** controller is used in this project. Due to the advancement in power electronic techniques various types of renewable energy sources are have become very popular but the losses associated with the conversions are high. In order to improve efficiency the converters are implemented. Here the double stage buck-**boost** **converter** is used to increase the efficiency. Switching losses are reduced by double-stage buck-**boost** converters. In order to enhance the converters efficiency the soft switching schemes **based** on the interleaved **converter** is proposed. The **converter** units are connected to each other by an inductor as a bridge that plays an important role in the soft switching operation by maintaining the voltage applied to switches at zero switching intervals. A modified **PI** controller is used to **control** the **converter** to maintain a constant voltage set point for energy **control** applications. The circuit is simulated by MATLAB SIMULINK software and more than 93% efficiency is obtained from the simulation results.

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Numerical simulation is conducted to test the effectiveness of the proposed system. Test simulation is set to be 0.9 seconds. Two different controllers, which are PID controller and observer **based** sliding mode with conventional sliding surface [13], are employed to be compared with proposed method. The PID controller parameters are determined by using direct synthesis method. According to the calculation, the PID controller parameters are obtained and presented in Table 3. The difference of our proposed method with [13] are sliding surface structure and reaching law dynamics. In [13], the sliding surface is merely using state of inductor current error, while our proposed method is using **PI** structure for its surface. Reaching law dynamics in [13] is not utilized, while it is employed in our proposed method. The parameters of [13] are **based** on Table 1, but there are no reaching law dynamics parameters and λ defines the gain of inductor current error. The test scenarios conducted for system testing are illustrated in Table 4. There are six scenarios for this system testing, includes input voltage, resistance load, and reference voltage variations.

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Where is the current draw through the diode rectifier shown in fig.4. is sinusoidal current , is the current drawn through the non linear load and is the compensating current which has to be trough the inductor(storage element) of a **boost** **converter**. in this way the source current draws the approximate sinusoidal current by which the power factor is improved. This **scheme** uses the hysteresis current controller to **control** the switching pulse of a power switch „S‟of a **boost** **converter** to track the line current command and A single MOSFET free-wheeling diode with simple **control** circuit form the chopper circuit. The motor drives a mechanical load friction coefficient B, characterized by inertia J, and load torque TL. The **control** circuit consists of voltage controller ( **PI** controller) senses the actual voltage and compares it with the required reference voltage to determine the required armature current there by to produce the desired voltage across output terminals of a **boost** **converter** to **control** the speed of a SEDM by armature voltage **control** method.

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Abstract – This document gives you a brief idea of the Design and simulation of DC/DC **Boost** **converter** operating in continuous conduction mode using pulse width modulation **based** sliding mode controller. The performance and properties of sliding mode controller is compared with Proportional Integral Derivative (PID) controller and Proportional Integral (**PI**) controller. Simulation results shows that the sliding mode **control** **scheme** provides good voltage regulation and is suitable for **boost** DC-to-DC conversion purposes. The derived controller/**converter** system is suitable for any changes on line voltage and parameters at input keeping load as a constant.

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In this paper, the modified LCC type of series-parallel Resonant **Converter** (RC) was designed and state-space modeling analysis was implemented. In this proposed **converter**, one leg of full bridge diode rectifier is replaced with Synchronous Rectifier (SR) switches. The proposed LCC **converter** is controlled using frequency modulation in the nominal state. During hold-up time, the SR switches **control** is changed from in-phase to phase-shifted gate signal to obtain high DC voltage conversion ratio. Furthermore, the closed loop **PI** and fuzzy provide **control** on the output side without de- creasing the switching frequency. The parameter such as conduction loss on primary and second- ary side, switching loss, core and copper also reduced. Simultaneously, the efficiency is increased about 94.79 is realized by this **scheme**. The proposed **converter** with an input of 40 V is built to produce an output of 235 V with the help of ZVS **boost** **converter** [1] even under line and load dis- turbances. As a comparison, the closed loop fuzzy controller performance is feasible and less sen- sitive than **PI** controller.

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Abstract : This paper deals about the improvement of output from hybrid (Wind and PV) system through the maximum power point technique (MPPT). Though various power tracking techniques are available, Constant Voltage method is simple and effective way to track the maximum power. In this method output voltage is compared with the maximum voltage and **based** on the comparison gate signal is generated to the **boost** **converter** switch. Two **boost** converters are used individually for PV and Wind system. The whole system is modeled by using the Matlab/Simulink Model.

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Abstract — The efficiency of the DC-DC converters is an important issue which has received great attention in literature works. Nowadays, step up conversion is widely used in many applications like Electric vehicles, Photovoltaic (PV) system, Uninterruptable power supplies (UPS) and fuel cell system. Frequency dependent **boost** **converter** and interleaved **boost** DC-DC converters presents a novel two-stage **boost** **converter** with a soft switching operation. The **converter** units are connected to each other by an inductor known as interleaved inductor as a bridge. This inductor plays an important role in the soft switching operation of the **converter** by zero-voltage switching. By paralleling the converters, high reliability and efficiency in power electronic systems can be obtained. . Using high frequency converters we can get improved efficiency, reduced ripple voltage, reduced inductor current ripple. Both the converters are simulated using MATLAB/SIMULINK. The converters are tested by varying the frequency with constant duty cycle and varying the duty ratio with constant frequency in Continuous Conduction Mode(CCM). The performance parameters of the converters are compared. A circuit prototype of frequency dependent **boost** **converter** is designed and tested to verify the proof of concept. The hardware realization is done using PIC16F877A controller.

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One could either measure the rotor speed or obtain the power reference to regulate the power or measure the wind speed and obtain the rotor speed reference to regulate the rotor speed [2]. The former produces more accurate output power while the latter will have faster **control** response. Aside from an accurate reference power curve, analysis is necessary to verify the stability of the method in terms of varying wind speed and output power [3] [4]. Few publications just address the stability issue of such method, but more detailed quantitative analysis should be conducted. This paper studies the performance of wind turbine under reference power curve MPPT power **control**. In particular, it presents a small-signal analysis on generator speed dynamics induced by variable wind speed. Also, an experimental setup to emulate the wind turbine operation in torque **control** mode is presented. Both steady-state and dynamic responses are implemented to verify the proposed analysis and conclusions [5]. Section IIwill present how to obtain the optimal reference power curve and analyze the stability of this method by conducting the small-signal.

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In this new ZCT-ZVT PWM DC-DC interleaved **boost** **converter** having an active snubber cell is used to overcome the drawbacks of converters. The basic circuit **scheme** of this new soft switching ZCT-ZVT PWM DC-DC interleaved **converter** is shown in Fig.1. In this **converter**, the main switches perfectly turn on with ZVT and turn off with ZCT. The auxiliary switch turns on with ZCS and turns off with ZVS. The main diodes turn on with ZVS and turn off with ZCS. Also, any voltage and current stresses do not occur on the main switches and the main diodes. The current stress on the auxiliary switch is acceptable level. All of the other semiconductor devices turn on and turn off with SS. An auxiliary switch, a coupled resonance inductance, a resonance capacitor and four auxiliary diodes are used in the snubber circuit. MOSFET is chosen for main switches and IGBT is chosen for auxiliary switch. In addition to the new **converter** can operate under light load conditions and it operates a wide range of duty cycle.

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Now a day, single switch high voltage gain dc –dc converters is used to reduce voltage stress and recycle the output by leakage inductance energy. In this **converter** used in many industrial applications such as fuel cell energy conversion systems, uninterrupted power supply electric traction and some medical equipment’s. The above applications depend on the dc- dc **converter** types which are **boost** **converter**. Here with the help of **boost** **converter** rather than classical, high output voltage is equal to voltage stress of the main switch. The result of an extremely high duty cycle will give large conduction losses on power device and it is not realizing high voltage gain. This **converter** achieve high conversion ratio and reduced at extremely high duty cycle. In high voltage applications the rating of active switch is high voltage must be selected.

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