Implentation and Comparison of Modulation and Control Techniques of a Closed Feedback Controlled Switch Ladder Multilevel Inverter

Project Title

Implentation and Comparison of Modulation and Control Techniques of a Closed Feedback Controlled Switch Ladder Multilevel Inverter

Project Area of Specialization RoboticsProject Summary

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:

•     PID controller
•     Fuzzy logic controller

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

Project objectives are:

1.  Implementation of Multilevel  Switch-Ladder Inverter with maximum of 289 level to get the wave as pure as sine wave.
2. Comparison of different control techniques(i.e, PID,Fuzzy-Logic etc) to check which one in better for usage purposes.
3. Improvemnet in the usage of renewable Energy-Sources with help of Switch-Ladder Multilevel Inverter.
4. Implementation of Multilevel Switch-Ladder inverter which has less THD(Total Harmonic Distortion) with greater number of Levels of output wave.

Project Implementation Method

The implementation and comparison for the modulation and control of a closed feedback controlled switch ladder multilevel inverter,following techniques will be employed:

1.     PID controller
2.     Fuzzy logic controller

• Fuzzy Logic Controller:

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:

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:

 Defuzzifier converts this fuzzy output to the required output to control the system.

•     PID Controller:

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:

•      Proportional or P- controller:

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.

•     I-Controller:

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.

•     D-Controller:

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.

Benefits of the Project

Following are applications of project:

•     Highly efficient and versatile enough for load and grid connectivity.
•     Used for/in high voltage system interconnections.
•     Provide low cost load quality analysis
•     Responsible for production of  low harmonic distortion at the output.
•     Can be used in electric vehicle drivers and motor drivers.
•     Applicable for domestic renewable energy systems.
•     Medium voltage and high power industrial loads
•     Suitable for interfacing with different renewable energy resources.

Technical Details of Final Deliverable

• 17, 289 and 578 level inverter simulations and hard ware of 17 and 289 level inverter.    
•     Feedback for standalone inverter.
•     Different PWM control techniques for grid tied or load connected inverter.
•     Comparison of PWM techniques.
•     Up gradation through techniques.

Final Deliverable of the Project Hardware SystemType of Industry Energy , Manufacturing , Others Technologies RoboticsSustainable Development Goals Affordable and Clean Energy, Decent Work and Economic Growth, Industry, Innovation and Infrastructure, Sustainable Cities and Communities, Responsible Consumption and ProductionRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	76400
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