A multilevel inverter is a power electronic device which is capable of providing the desired AC output by using the different low level DC links as input. Multilevel inverters are the modification in simple inverters. This new Switch Ladder Multilevel Inverter in now the game changing topo
Implentation and Comparison of Modulation and Control Techniques of a Closed Feedback Controlled Switch Ladder Multilevel Inverter
A multilevel inverter is a power electronic device which is capable of providing the desired AC output by using the different low level DC links as input. Multilevel inverters are the modification in simple inverters.
This new Switch Ladder Multilevel Inverter in now the game changing topology for designing the multilevel inverters. In this topology, we can generate the output with large number of levels resulting into the waveform very close to sinusoidal waveform having low total harmonic distortion by using less number of switches.
In implementation and comparison for the modulation and control of a closed feedback controlled switch ladder multilevel inverter, following techniques will be employed:
Using these techniques we can develop highly efficient and versatile multilevel inverter for load and grid connectivity with low cost load quality analysis.
Project objectives are:
The implementation and comparison for the modulation and control of a closed feedback controlled switch ladder multilevel inverter,following techniques will be employed:
Fuzzy Logic is a particular area of concentration in the study of Artificial Intelligence and is based on the value of that information which is neither definitely true nor false. The information which humans use in their everyday lives to base intuitive decisions and can apply general rules of thumb and should be applied to those control situations which demand them. Acquired knowledge can be a powerful weapon to combat the undesired effects of the system response.
A fuzzy control system consists of the following components:
Fuzzifier which transforms the measured or the input variables in numerical forms into linguistic variables.
Controller which performs the fuzzy logic operation of assigning the outputs based on the linguistic information. It performs approximate reasoning based on human way of interpretation to achieve the control logic. The controller consists of the knowledge base and the inference engine. The knowledge base consists of the membership functions and the fuzzy rules, which are obtained by knowledge of the system operation according to the environment.
Defuzzifier converts this fuzzy output to the required output to control the system.
The proportional-integral-derivative (PID) controller, which has been widely used in the industry plants by over 90 percent. PID controller maintains the output such that there is zero error between process variable and set point/ desired output by closed loop operations. PID uses three basic control behaviors that are explained below:
It gives output which is proportional to current error e (t). It compares desired or set point with actual value or feedback process value. The resulting error is multiplied with proportional constant to get the output. If the error value is zero, then this controller output is zero.
Due to limitation of p-controller where there always exists an offset between the process variable and set point, I-controller is needed, which provides necessary action to eliminate the steady state error. It integrates the error over a period of time until error value reaches to zero. It holds the value to final control device at which error becomes zero.
Integral control decreases its output when negative error takes place. It limits the speed of response and affects stability of the system. Speed of the response is increased by decreasing integral gain Ki.
I-controller doesn’t have the capability to predict the future behavior of error. So it reacts normally once the set point is changed. D-controller overcomes this problem by anticipating future behavior of the error.
Following are applications of project:
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Transformer | Equipment | 8 | 2000 | 16000 |
| MOSFET IRF 630 -2 | Equipment | 25 | 500 | 12500 |
| DC voltage Sources | Equipment | 10 | 1000 | 10000 |
| PCB | Equipment | 10 | 400 | 4000 |
| Capacitors | Equipment | 25 | 200 | 5000 |
| Resistors | Equipment | 25 | 100 | 2500 |
| Rectifier Module | Equipment | 6 | 500 | 3000 |
| Myrio Micro-controller | Miscellaneous | 2 | 5000 | 10000 |
| Gate Driver | Equipment | 18 | 200 | 3600 |
| 2N2222 Transistors | Equipment | 20 | 80 | 1600 |
| Heat Sink | Equipment | 20 | 110 | 2200 |
| Potentiometer | Equipment | 4 | 100 | 400 |
| Digital Multimetre | Equipment | 2 | 1200 | 2400 |
| Bread-Board | Equipment | 4 | 400 | 1600 |
| Diodes | Equipment | 20 | 80 | 1600 |
| Total in (Rs) | 76400 |
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