Showing papers by "Binod Kumar Sahu published in 2012"

Design and performance analysis of PID controller for an automatic voltage regulator system using simplified particle swarm optimization

Abstract: This paper presents the design and performance analysis of Proportional Integral Derivate (PID) controller for an Automatic Voltage Regulator (AVR) system using recently proposed simplified Particle Swarm Optimization (PSO) also called Many Optimizing Liaisons (MOL) algorithm. MOL simplifies the original PSO by randomly choosing the particle to update, instead of iterating over the entire swarm thus eliminating the particles best known position and making it easier to tune the behavioral parameters. The design problem of the proposed PID controller is formulated as an optimization problem and MOL algorithm is employed to search for the optimal controller parameters. For the performance analysis, different analysis methods such as transient response analysis, root locus analysis and bode analysis are performed. The superiority of the proposed approach is shown by comparing the results with some recently published modern heuristic optimization algorithms such as Artificial Bee Colony (ABC) algorithm, Particle Swarm Optimization (PSO) algorithm and Differential Evolution (DE) algorithm. Further, robustness analysis of the AVR system tuned by MOL algorithm is performed by varying the time constants of amplifier, exciter, generator and sensor in the range of −50% to +50% in steps of 25%. The analysis results reveal that the proposed MOL based PID controller for the AVR system performs better than the other similar recently reported population based optimization algorithms.

Robust analysis and design of PID controlled AVR system using Pattern Search algorithm

Abstract: This paper has been presented in keeping the view of optimal design of a Proportional-Integral-Derivative (PID) controller based on Pattern Search (PS) Optimization algorithm. In order to determine the optimum parameters of the PID controller for an automatic voltage regulator (AVR) system in a 3-ph generator this meta-heuristic algorithm is used. In this paper, the objective function is expressed as a function of Integral Time Absolute Error (ITAE), damping ratio, settling time, peak time and the peak value of the amplitude of the wave. The proposed method is found to be better than Artificial Bee Colony (ABC) algorithm with objective function as Integral Time Square Error (ITSE). It has been observed that different parameters of the AVR system such as settling time, peak time, rise time, oscillations and overshoot improve drastically. The AVR system's results were analyzed by different methods like of transient analysis, root locus analysis and bode analysis. Moreover, the results obtained by the simulation derive that the AVR tuned by Pattern Search algorithm are highly better and robust.

Design and comparative performance analysis of PID controlled automatic voltage regulator tuned by many optimizing liaisons

Abstract: This paper deals with the design of Proportional, Integral, and Derivative (PID) controller to an Automatic Voltage Regulator (AVR) tuned by recently developed Simplified Particle Swarm Optimization algorithm so called, Many Optimizing Liaisons (MOL) algorithm. MOL simplifies the original PSO by randomly choosing the particle to update, instead of iterating over the entire swarm thus eliminating the particle's best known position and making it easier to tune the behavioural parameters. The proposed method is compared with the earlier used PSO algorithm. For performance studies; Transient response analysis, Bode plot analysis and Root locus analysis are explained in details. The robustness analysis is done by varying the time constants of amplifier, exciter, generator & sensor in the range of −50% to + 50% with a step size of 25% respectively. The results of these analyses using the MOL algorithm are found to be better with respect to the analysis of the PID controller using PSO algorithm.

Performance analysis and design of proportional integral derivative controlled automatic voltage regulator system using local unimodal sampling optimization technique

Abstract: Proportional---Integral---Derivative (PID) controllers are mainly used in industrial control systems, motor drives, process control, and instrumentation. Optimum tuning of PID controller parameters is a big challenge for researchers and plant operators. This paper describes the 'Local Unimodal Sampling (LUS)' algorithm to tune the PID controller for an Automatic Voltage Regulator (AVR) system to determine the optimum controller parameters. Many optimization techniques use local sampling with a fixed sampling range. Therefore, there is a risk of getting stuck in the local optima. This problem can be overcome by using LUS algorithm which decreases the sampling range as optimization progresses. Compared with the artificial bee colony (ABC), the proposed method is found to be more robust and efficient in improving the step response of an AVR system. Transient response analysis, root locus analysis and bode analysis are used to compare the performance of both the algorithms.