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  1. Control of Direct Current Motor using GA and PSO
  2. Parallel combination of PMSG and SCIG
  3. Speed control of brushless DC motor using genetic algorithm based fuzzy controller
  4. Optimal Tuning of PI Controller Using Genetic Algorithm for Induction Motor Speed Control
  5. A General Theory of Phase Noise in Electrical Oscillators
  6. Direct Torque Control for Induction Motor Using Fuzzy Logic-2006
  7. GA based Optimal Sizing & Placement of Distributed Generation for Loss Minimization-2007
  8. Zero-Voltage-Switching DC–DC Converters With Synchronous Rectifiers-2008
  9. A novel dc voltage charge balance control for cascaded inverters-2009
  10. Active Power Loss Minimization With FACTS Devices Using SA/PSO Techniques-2009
  11. Control of a Cascade STATCOM With Star Configuration Under Unbalanced Conditions-2009
  12. A FACTS Device: Distributed Power-Flow Controller (DPFC)-2010
  13. Analysis and Design of High-Frequency Isolated Dual-Bridge Series Resonant DC/DC Converter-2010
  14. Fuzzy Logic Controller for Enhancement of Transient Stability in Multi Machine AC-DC Power Systems-2010
  15. Optimal Location and Control of Shunt FACTS for Transmission of Renewable Energy in Large Power Systems-2010
  16. Research on Direct Torque Control of Induction Motor Based on Genetic Algorithm and Fuzzy Adaptive PI Controller-2010
  17. Automatic Loop Shaping of QFT Robust Controllers with Multi-Objective Specifications via Nonlinear Quadratic Inequalities-2010
  18. Sensorless Speed Control of Induction Motors using Adaptive Neural-Fuzzy Inference System-2011
  19. Simulation and Experimental Studies of Permanent Magnet Synchronous Motor Control Methods-2011
  20. Design of Direct Torque Controller of Induction Motor (DTC)-2012
  21. Optimal Location and Sizing of DG using Fuzzy logic-2014
  22. Optimal Location of FACTS for ATC Enhancement-2014
  23. Differential relaying scheme for tapped transmission line connecting UPFC and wind farm-2014 
  24. Distance Protection of Lines Connected to Induction Generator-Based Wind Farms During Balanced Faults-2014
  25. Comparison between DTC using a 2-level inverters and DTC using a 3 level inverters of IM-2014



A novel multivariable laboratory process that consists of fourinterconnected water tanks is presented. The linearized dynamics of the system have a multivariable zero that is possible to move along the real axis by changing a valve. The zero can be placed in both the left and the right half-plane. In this way the quadruple-tank process is ideal for illustrating many concepts in multivariable control, particularly performance limitations due to multivariable right half-plane zeros. The location and the direction of the zero have an appealing physical interpretation. Accurate models are derived from both physical and experimental data and decentralized control is demonstrated on the process. Index Terms—Education, laboratory process, multivariable control, multivariable zeros.

MULTIVARIABLE control techniques have received increased industrial interest. It is often hard to tell when these methods are needed for improved performance in practice and when simpler control structures are sufficient. A key issue is the functional limits of the system: what design specifications are reasonable? It was already pointed out by Bode that nonminimum-phase characteristics of a system impose limitations for linear feedback designs. Still it happens that unrealistic specifications are made, as pointed out in Performance limitations in control systems have received extensive interest recently. Several new results, particularly for scalar and multivariable linear systems.

Bode’s original result together with extensions are covered in the textbooks.Zames and Francis showed that right half-plane zeros impose restrictions on the sensitivity function: if the sensitivity is forced to be small in one frequency band, it has to be large in another, possibly yielding an overall bad performance. They also showed that if the system does not have any right half-plane zeros, then theoretically it can be arbitrarily well controlled. The latter result has been generalized to decentralized control structures. This project describes a new laboratory process, which was designed to illustrate performance limitations due to zero location in multivariable control systems. The process is called the quadruple-tank process and consists of four interconnected water tanks and two pumps. The system is shown in Fig. 1.Its inputs are the voltages to the two pumps and the outputs are the water levels in the lower two tanks. The quadruple-tank process can easily be build by using two double-tank processes, which are standard processes in many control laboratories . The setup is thus simple, but still the process can illustrate several interesting multivariable phenomena.  The linearized model of the quadruple-tank process has a multivariable zero, which can be located in either the left or the right half-plane by simply changing a valve. Both the location and the direction of a multivariable zero are important for control design. They have direct physical interpretations for the quadruple-tank process, which make the process suitable to use in control education.



Brushless DC Motors (BLDCM) are widely used in automated industrial applications like Computer Numerical Control (CNC) machinery, aerospace applications and in the field of robotics. The dynamics of this motor should be smooth for many industrial and automated applications and free from unwanted interference. But due high speed switching circuits used in the commutation circuits, the BLDC motor voltage contains harmonics component and this causes high electromagnetic interference problems. During commutation the trapezoidal current pass through each phase causes pulsation in torque during its operation. This work proposes an improved methodology to reduce the high frequency harmonics components and torque ripples using a RC filter connected at the input of the motor. This work is simulated using PSIM and the effect of filter is analyzed with FFT analysis. An experimental setup is developed to analyze the performance of the drive with the proposed system and the experimental outputs were compared with the simulated values and the improvement in performance is analyzed.

The brushless dc motor (BLDCM) has found to be more efficient than the existing DC motor and induction motors Due to the simplicity in control scheme, high power density, reliability, and maintenance free operation, BLDC motors are used in the field of industrial automation, Computer numerical control machines and in the field of robotics. The mechanical losses are minimized since no brushes and no mechanical commutator present in the motor. The dynamics for this motor should be smooth for many industrial and automation applications. Due to the power electronic commutation, the usage of high frequency switching of power devices, imperfections in the stator and the associated control system, the input supply voltage to the motor contains various harmonics components. During its operation, high frequency components present in the voltage input will cause serious electromagnet interference (EMI) problem and the pulsating current input due to electronic commutation causes torque ripple. So an efficient controller is required to reduce the harmonics present in the input voltage to the motor and to reduce the pulsating variation of line current to the motor.