Journal ArticleDOI
A particle swarm optimization approach for optimum design of PID controller in AVR system
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TLDR
The proposed PSO method was indeed more efficient and robust in improving the step response of an AVR system and had superior features, including easy implementation, stable convergence characteristic, and good computational efficiency.Abstract:
In this paper, a novel design method for determining the optimal proportional-integral-derivative (PID) controller parameters of an AVR system using the particle swarm optimization (PSO) algorithm is presented. This paper demonstrated in detail how to employ the PSO method to search efficiently the optimal PID controller parameters of an AVR system. The proposed approach had superior features, including easy implementation, stable convergence characteristic, and good computational efficiency. Fast tuning of optimum PID controller parameters yields high-quality solution. In order to assist estimating the performance of the proposed PSO-PID controller, a new time-domain performance criterion function was also defined. Compared with the genetic algorithm (GA), the proposed method was indeed more efficient and robust in improving the step response of an AVR system.read more
Citations
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Proceedings ArticleDOI
Big-bang big-crunch based optimization of PID controller for DC motor
H. K. Verma,Cheshta Jain +1 more
TL;DR: An overview of Big Bang-Big Crunch algorithm (BB-BC) is provided and its robustness under critical conditions over particle swarm optimization (PSO) and differential evaluation algorithm (DE) is shown.
Journal ArticleDOI
A Fast Induction Motor Speed Estimation based on Hybrid Particle Swarm Optimization (HPSO)
TL;DR: In this article, the authors proposed the application of hybrid particle swarm optimization (HPSO) for losses and operating cost minimization control in the induction motor drives and demonstrated the good quality and robustness in the system dynamic response and reduction in the steady-state and transient motor ripple torque.
Proceedings ArticleDOI
Evolutionary algorithm EPSO helping doubly-fed induction generators in ride-through-fault
TL;DR: In this article, an evolutionary particle swarm optimization-based (EPSO) approach is presented to tune the PI controller gains of a doubly-fed induction generator's (DFIG) rotor side converter to limit the line-to-line voltage dip at the DFIG's terminals after a short-circuit, in order to avoid its tripping-off.
Journal ArticleDOI
Rao algorithm based optimal Multi‐term FOPID controller for automatic voltage regulator system
TL;DR: In this article , an optimal multi-term fractional-order PID (MFOPID) controller for automatic voltage regulator (AVR) system has been proposed for improving the performance of the AVR system.
Journal ArticleDOI
On Deregulated Power System AGC with Solar Power
TL;DR: Different secondary controllers like Integral, PID, PI-PD controllers are used for a two area deregulated power system consisting of reheat thermal, solar thermal and solar photovoltaic units, tuned by Particle Swarm Optimization (PSO) approach.
References
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Proceedings ArticleDOI
Particle swarm optimization
TL;DR: A concept for the optimization of nonlinear functions using particle swarm methodology is introduced, and the evolution of several paradigms is outlined, and an implementation of one of the paradigm is discussed.
Proceedings ArticleDOI
A modified particle swarm optimizer
Yuhui Shi,Russell C. Eberhart +1 more
TL;DR: A new parameter, called inertia weight, is introduced into the original particle swarm optimizer, which resembles a school of flying birds since it adjusts its flying according to its own flying experience and its companions' flying experience.
Proceedings ArticleDOI
Empirical study of particle swarm optimization
Yuhui Shi,Russell C. Eberhart +1 more
TL;DR: The experimental results show that the PSO is a promising optimization method and a new approach is suggested to improve PSO's performance near the optima, such as using an adaptive inertia weight.
Book
Power System Analysis
TL;DR: This is the first text in this area to fully integrate MATLAB and SIMULINK throughout and provides students with an author-developed POWER TOOLBOX DISK organized to perform analyses and explore power system design issues with ease.
Book
Evolutionary Computation: Towards a New Philosophy of Machine Intelligence
TL;DR: In-depth and updated, Evolutionary Computation shows you how to use simulated evolution to achieve machine intelligence and carefully reviews the "no free lunch theorem" and discusses new theoretical findings that challenge some of the mathematical foundations of simulated evolution.