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
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Book ChapterDOI
Application of Intensified Current Search to Optimum PID Controller Design in AVR System
TL;DR: This paper demonstrates how to conduct the intensified current search to search efficiently the optimum PID controller parameters of the AVR system and results show the ICS-based design approach performs high robustness once parameter variations are occurred in the control loop.
Particle swarm optimisation algorithms and their application to controller design for flexible structure systems
M. O. Tokhi,Alam +1 more
TL;DR: A modified multi-objective PSO (MOPSO) proposal is made which will allow the algorithm to deal with multi-Objective optimisation problems and a new technique is introduced that combines external archive and non-dominated fronts of the current population in order to select the global best for each particle.
Journal ArticleDOI
Leader Harris Hawks algorithm based optimal controller for automatic generation control in PV-hydro-wind integrated power network
TL;DR: In this article , a model predictive controller aided with Leader Harris Hawks Optimization (MPC-LHHO) algorithm is proposed for the regulation of frequency and voltage in renewable penetrated power systems.
Book ChapterDOI
Power Electronic Drives and Control Technology Status: Brief Review
TL;DR: The significance of power hardware, the late advances in power semiconductor devices, converters, AC motors with variable frequency, the dawn of microprocessors/microcontrollers/microcomputers permitted to actualize and these control methods will be discussed briefly.
Proceedings ArticleDOI
ITAE-optimal PI controller based on Genetic Algorithm for low-order process with large time delays
TL;DR: Monte-Carlo stochastic experiment on robust performance indicates that the proposed PI controller tuning method has good performance robustness when parameter uncertainty occurs compared with other four PI tuning methods.
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.
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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.
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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.