The voltage Converter is an electrical circuit that is used to control the transfer of energy between the source and the consumer . The need for a broad spectrum of consumer's cabinets caused the development of different types of converters. The scope of current ranges moves within the limits order of several hundred mili amperes to several hundred amperes . Converters differ according to the principle of functioning, construction, energy efficiency, size, precision control , transitional state response , and of course the price. Converter usually has an additional feature to provide protection in the event of system failure, All regulators have a power transfer stage and a control circuitry to sense the output voltage and adjust the power transfer stage to maintain the constant output voltage. Since a feedback loop is necessary to maintain regulation, some type of compensation is required to maintain loop stability .
Dc-Dc Converters are widely used for traction motor in electric automobiles, trolley cars, marine hoists, and forklift trucks. They provide smooth acceleration control, high efficiency, and fast dynamic response. General idea of dc-dc converter is to convert a fixed voltage dc source into a variable voltage dc source. In the beginning of 1970s, a good number of DC-DC converter circuits have been designed and analyzed in detail. Such converter circuits can amplify or reduce the scale of the DC voltage and/or reverse its polarity. In the topology known as Boostconverter, the inductor is used in series with input voltage source, which allows this converter to produce an output DC voltage that is greater in magnitude than the input voltage.
It is not satisfaction at DC/DC converters by conventional feedback control. Conventional feedback control is slow to respond the disturbance of power source and a large number of switching cycles is required before the steady-state is regained. The commonly used control methods for dc-dc converters are pulse width modulated (PWM) voltage mode control, PWM current mode control with proportional (P), proportional integral (PI), and proportional integral derivative (PID) controller. These conventional control methods like P, PI, and PID are unable to perform satisfactorily under large parameter or load variation.
A digital control of a boost-buckconverter for a TEG is presented. The converter can be modeled and analysed with the SSA. The control of the converter includes a MPPT, whose function it is to adapt the maximum power point of the TEG. Further, a cascade controller regulates the voltage between the two converters, and a subsidiary current controller regulates the charge current of the battery. The control design is based on a two-degrees-of-freedom controller, whose parameter are well defined for a TEG, with the assumption of a steady temperature. Variations of the temperature influence the voltage and especially the resistor of the TEG, which also affects the dynamic of the control plant. A method to compensate this influence, is a self- tuningcontroller which is uses a closed loop identification to estimate the parameter of the plant. In the experiments a RLS algorithm was used to estimate the zeros and poles of the control plant. The online re-design of the control parameters could ensure the desired closed loop dynamic of the current controller.
SMC for variable structure systems  is a robust control method of nonlinear systems due to its insensitivity of parameter variations, fast dynamic response and ease of implementation. SMC was first applied to DC-DC converters in [19, 20] and many diverse implementation examples are available in . Design criteria for SMC application to DC-DC converters is outlined in . SMC based equivalent controller is applied to buck-boost and Cuk converter topologies in . However, SMC is not popularly implemented to DC-DC converters due to its unavailability of integrated circuit forms for power electronic applications. Moreover, its variable switching frequency (SF) behavior depending on the converter parameters and operation regions complicates electromagnetic interference filter design and practical implementation. A scheme given in  outlines the SF fixing and reduction methods in SMC applications. In addition, it is known that DC-DC converters are unwanted noise generators, and this problem can be overcome with fixed frequency operation .
In This paper the performance of different models for PV system using MATLAB/Simulink are implemented. The maximum power is obtained using proposed model method. It is observed that the characteristics obtained based on this method is closest to the theoretical and simulations. Also from this proposed model, maximum values of voltage, maximum value of current and maximum value of power are developed and have a low ripple compared with the three other models. Thus the proposed simulation model of DC-DC converter with PID-MPPT algorithm can be used as a reference for presentation of actual system.
Renewable energy sources have experienced a rapid development in recent years. These systems employ with micro sources like PV, fuel cells etc. PV cells to produce high voltage but there exist severe problems like shadowing effects, short circuit which significantly reduces its efficiency. In order to overcome such unfavourable conditions this type of micro source energy is applied to the high step up converter to produce high voltage and fulfil the demands. In rapid progress of communication and computing gadgets DC-DC converters are employed for various devices like amplifiers, personal digital assistant (PDA), MP3 players, blue tooth devices etc., which need high voltage to obtain enough output power and voltage amplitude.
Abstract:- Power factor is an important performance parameter of a system .If the power factor of a system is low, it draws more current from the supply. So improving power factor is very much essential for better and economic performance of a system.This paper introduce a new power factor correction circuit which overcomes all the drawbacks of conventional power factor correction approaches. This proposed circuit will provide output voltage range of 257V, with input power factor 0.81 and input current THD of 40% .Here bridgeless buck rectifier output is given as input to the boostconverter for maximising the output voltage level. Simulation has been carried out to study the performance of the proposed topology in MATLAB/SIMULINK environment.
Abstract: This paper reports a modernized synchronously Operating buck-boostconverter with persistent current will be proposed. Contrasted and the conventional buck-boostconverter, the suggest converter can get a dynamically wide degree of the voltage transformation proportion with the similar obligation cycle. In addition, the suggest converter can work with persistent current contrasted to the existing counterparts with an inherently discontinuous current. The operational guideline and enduring-state execution of the suggest converter under persistent inductor current mode is investigated personally. At that point, the examination among the suggest converter and thus the current quadratic buck-boost converters has been directed to exhibit the unmistakable highlights of the suggest one. To check the operation of the proposed converter, a simulation model will need to develop by using MATLAB Simulink. The developed simulation model needs to be analyzing for various stacking conditions.
II. O PERATING P RINCIPLES OF T HE P ROPOSED C ONVERTER The proposed converter is able to transfer energy between two different dc sources. Such has low voltage side voltage 24V to the high voltage side 200V and the output power of 200W. It has two different modes such as discharging and charging mode is explain by its equivalent circuit diagram. Fig.2.1shows the proposed converter circuit with leakage inductances.
The dynamic characteristics of the brushless DC motor such as speed, torque, current and voltage of the inverter components are observed and analyzed using the developed MATLAB model . Proposed fuzzy logic controller system has a good adaptability and strong robustness whenever the system is disturbed. The simulation model which is implemented in a modular manner under MATLAB environment allows dynamic characteristics such as phase currents, rotor speed, and mechanical torque to be effectively considered . References:
Now consider the converter proposed in , as shown in Fig. 5(b). It can be seen in Fig. 5(a) that the converter enters a freewheeling mode of operation when switch S1 is turned OFF. The converter exits this freewheeling mode by the turning OFF of S1 and then the simultaneous turning ON of switches S3 and S4. During this transition, it is only the leakage inductance energy that is available to turn S3 and S4 ON with ZVS. Similarly, switch S1 and S2 are turned ON when the converter exits the other freewheeling mode of the switching cycle, again, with only the leakage inductance energy available to discharge their output capacitances. What this means is that all the converter switches lose the ability to turn ON with ZVS under light-load conditions as only leakage inductance energy is available to discharge their output capacitances just before they are turned ON. With respect to the proposed converter, as can be seen from Mode 2 (just like Mode 7), shown in Fig. 5(a), when S1 (or S4 ) turns OFF and the converter enters a freewheeling mode of operation, the energy available to charge the output capacitance of S1 (or S4 in Mode 7) and discharge the output capacitance of S4 (or S1 in Mode 7) is the energy stored in leakage inductance plus the energy in output filter inductor that is “reflected” to the primary. Since the energy in the filter inductor is large compared to that required to charge/discharge the capacitances, the body capacitance of S4 (or S1 in Mode 7) can be discharged completely through flying capacitor Cf . Once this happens, switch S4 (or S1 afterMode 7) can be turned ON with ZVS in anticipation for later on in the switching cycle when the converter exits a freewheeling mode of operation.
Because of the broadly utilized DC described burdens and progressively disseminated power age sources, the DC Nano-network turns out to be increasingly prevalent and it is viewed as an option in contrast to the AC-framework. For security contemplations, the DC Nano-network ought to give solid establishing to the private burdens like the low voltage AC control framework. There are three run of the mill establishing designs for a DC Nano- matrix, including the unified establishing, the unidirectional establishing and the virtual disengaged establishing. Each establishing setup has its very own details to AC/DC converters. In this letter, a double Buck-Boost AC/DC converter for use in the unified establishing arrangement based DC Nano-framework with three terminal yields is proposed. The working guideline of this converter is exhibited in subtleties through dissecting the comparable circuits. Tests are completed to confirm the hypothetical examination.
extensive background in Controls, unlike many other modern controllers that are much more complex but often provide only marginal improvement. In fact, most PID controllers are tuned on-site. Although we are learning all the theories in ME475 to design the controller, the lengthy calculations for an initial guess of PID parameters can often be circumvented if we know a few useful tuning rules. This is especially useful when the system is unknown.
In recent years, many portable equipment and handheld consumer appliances such as mobile phones, digital cameras, MP3 players, personal digital assistants, and Global Positioning Systems usually include a variety of loads such as LCD displays, memories, microprocessors, Universal Series Bus (USB) and Hard Disk Drives (HDD). These loads require different operating voltages . Voltage level may be greater than the source voltage or less than the source voltage depending on the application. By suitable arrangement of converters, multiple power supplies of different voltages can be achieved. But it will result in large number of inductors of different values. A more interesting and efficient solution is to use one converter with a single inductor to generate multiple outputs. By using a Single Inductor Dual Output (SIDO) DC-DC
The main advantage of the proposed method resides on the fact that the systems designer can define the de- sired output in order to avoid saturations or other features and the optimization algorithm will return the appro- priate PID parameters values that minimize the error between the actual and the desired output. Manipulating the system to isolate the PID terms results in a linear optimization problem, with convex space solution, restricted and rapidly solved with the interior point optimization method.
The PID control algorithm is the most popular approaches used in process industries due to easy to understand by operator, technician and maintenance. One algorithm of PID control can be successful in many applications such as petroleum processing, steam generation, polymer processing and many more. Willis On the author of  PID consists three basic mode which is Proportional mode, Integral Mode and Derivative mode. Thomas  briefly explained in his „Process Control‟ book that PID control algorithm can provide good control performance for many different processes since the PID algorithm is simple and single equation. There are only 5% to 10% of industrial system that cannot be controlled by a PIDcontroller as stated by Koivo and Tanttu . Many industry use PID as their controller because of PIDcontroller is remarkable effectiveness, simple to implant in industrial process and easy to re-tuning as concluded by Saeed and Mahdi . Below is a simple diagram of control process that uses PID as controller:
A method for pre-tuning a multivariable PIDcontroller for a quadrotor attitude and altitude control has been proposed, which is based on LQR/LQG theory, using a modified structure of the LQR, where the state feedback algorithm employs the tracking error vector instead of the state vector. Realistic computer simulations have been carried out using a nonlinear mathematical model of the DJI-F450 quadrotor, considering parametric uncertainty and external disturbances acting at the plant input. Madgwick’s algorithm and a Kalman filter have been used for data fusion and estimating state variables using data from MARG, LIDAR and optical flow camera, which have been simulated using data sheets provided by manufactures. Simulation results show that the proposed tuning algorithm gives MIMO PID controllers which are robust in the face of uncertainties and external disturbances. Supplementary Materials: The following are available online at http://www.mdpi.com//xx/1/5/https: //youtu.be/rRv-dkYR6Ro, Video S1: MIMO PIDControllerTuningMethod Based on LQR/LQG Theory:
Abstract This paper has been like to presents the Comparative study of Proportional (P), Proportional Integral (PI), and Proportional Integral Derivative (PID) controllers. The PIDcontroller is one of the most commonly used dynamic control technique. Over 85% of all low level controllers are of the PID family. The purpose of this report is to provide a brief overview and advantage of using the PIDcontroller rather than P and PI controllers. Different tuning methods include Manual TuningMethod, Ziegler-Nichols Method are used to get the stable output response. The parameters must be identified and tuned for the good performance Manual TuningMethod, Ziegler-Nichols Method
ABSTRACT : This new Mathematical Model for Auto Tuning of PIDcontroller is composed of modeling of closed loop system, modeling of the process and Tuning formulas in terms of the relative damping of the transient response to set point changes. In this paper we are interested with the response of a PID Tuned system (Linear or Non-Linear) which has been subjected to step input .In conventional PIDTuning process, initially the process curve is analyzed with the help of Runge-kutta Numerical analysis method , then parameters like ( Kc , Ti and Td) are determined using Ziegler Nichols Method and finally we got a PID response curve. However this conventional method suffers from the disadvantage of factors like Peak-Overshoot, Rise Time, steady State Error and Settling Time etc. In order to improve one factor other one has to be compromised. So we need to develop a Mathematical Model that can overcome this difficulties as well as takes care of all the above mentioned factors very efficiently. This introduces the concept of Auto Tuningmethod in which all factors as well as parameters are adjusted and determined and compared with the results of conventional PIDTuning. To start with this Method, firstly the response curve of a Linear or Non-Linear processes are divided into four different regions and it is based on the value of the Error and the change in error which occurs in the four different regions. As we see that in the first and fourth region, error is positive , while the change in error is negative and positive respectively. Similarly in the second and third region, error is negative and the change in error is negative and positive respectively. The system to be undergone Auto Tuning may be considered as a Linear or Non-Linear complex differential equation of order one or two.