K. Sundareswaran

Ant colony based feedback controller design for soft-starter fed induction motor drive

The objective of this work is to design and implement a closed loop system for induction motor starting at rated current. Thyristorized AC voltage regulator is used as the starting equipment and motor current regulation is carried out using an optimally tuned Proportional-Integral (PI) controller. Since, AC voltage controller fed starting of induction motor is a non-linear process, identification of optimal values of PI controller constants is performed using a novel ant colony based optimization technique. The complete drive system including AC voltage controller fed induction motor in conjunction with optimal PI controller is first simulated in MATLAB and subsequently verified experimentally. The successful implementation with a low cost microcontroller illustrates the feasibility of the new approach.

Feedback controller design for a buck-boost converter through evolutionary algorithms

This paper suggests a systematic design procedure for the feedback controller employed for the output voltage regulation of a buck-boost type dc-dc converter using evolutionary algorithms namely Genetic Algorithm (GA), Differential Evolution (DE) and Artificial immune system (AIS). The output voltage regulation is formulated as an optimization task with the controller elements as the variables and solution is achieved through each evolutionary method. Computer simulation results supported by experimental evidence clearly demonstrate that the controllers estimated through evolutionary algorithms are capable of delivering enhanced output voltage regulation under different types of load and supply disturbances.

Application of Particle Swarm Optimization for output voltage regulation of dual input buck-boost converter

Dual input DC-DC converters act as an interface between different renewable energy sources and a common load. With uncertainty looming large over the renewable energy sources, it is mandatory to control the dual input DC-DC converter to provide a constant voltage to the load. This work reports the design and development of a Particle Swarm Optimization (PSO) based strategy for estimation of optimal controller structure for output voltage regulation of Dual input Buck-Boost (DIBB) converter. Computed and measured results at different operating points of DIBB suggest that the PSO tuned feedback controller is far superior to its conventional counterpart in delivering the desired output voltage with excellent dynamic response.

Optimization of Dual Input Buck Converter Control through Genetic Algorithm

Abstract This paper proposes an evolutionary process for the output voltage regulation of dual input buck type dc-dc converter. The output voltage regulation against a step change in reference signal is formulated as an optimization model and the optimum controller structure is identified using Genetic Algorithm (GA). The extensive simulation results obtained on a prototype dc-converter together with a few measured results demonstrate the validity of the new method.

Output Voltage Control and Power Management of a Dual Input Buck – Boost Converter Employing P&O Algorithm

Abstract This paper addresses the dual objective of output voltage control and power management in a doubly fed DC-DC converter. The first input is taken from a photovoltaic system and second input comes from a stiff source such as battery. The DC-DC converter integrates the two inputs and feeds power to a standalone DC load. The single objective here is to extract power from the PV cell as long as the load power is less than or equal to the maximum power available from the PV system. A power management scheme is developed, which does the above mentioned objective in addition to output voltage regulation. With increases in load power demand the battery also supplies power. The entire scheme is developed based on Perturb and Observe (P&O) theory and suitable control strategy is proposed. Extensive simulation results and experimental waveforms demonstrate the effectiveness of the new method.

Buck-Boost converter controller design using bacterial foraging

This paper reports the development of a bacterial foraging algorithm for output voltage control of Buck-Boost type converter. The solution to the optimization is carried out through the said algorithm and extensive results are shown to validate the new method.

Feedback controller design for a buck converter through evolutionary algorithms

This paper suggests a systematic design procedure for the feedback controller employed for the output voltage regulation of a buck type DC-DC converter using evolutionary algorithms, namely genetic algorithm, differential evolution and artificial immune system. Computer simulation results supported by experimental evidence clearly demonstrate that the controllers estimated through evolutionary algorithms are capable of delivering enhanced output voltage regulation under different types of load and supply disturbances.

Analysis on the failure of dynamic braking of capacitor-run induction motor supplied from half-controlled converter

This paper examines the viability of applying dynamic braking to AC voltage controller supplied capacitor-run induction motor. During the variable speed operation, the AC voltage regulator is gated during both half-cycles of the supply voltage. It is proposed to effect dynamic braking of the motor by inhibiting firing pulses during the negative half-cycles of the supply voltage. This will lead to half-controlled converter operation applying DC voltage across the motor terminals, and is supposed to cause dynamic braking. Contrary to expectation, motor is observed to rotate at a very low speed instead of braking. Theoretical, computed and measured results are presented in this paper to explain the failure of dynamic braking.