Journal ArticleDOI
Design of a fractional order PID controller for hydraulic turbine regulating system using chaotic non-dominated sorting genetic algorithm II
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TLDR
The chaotic NSGAII algorithm is used as the optimizer to search true Pareto-front of the FOPID controller and designers can implement each of them based on objective functions priority, validate the superiority of the fractional order controllers over the integer controllers.About:
This article is published in Energy Conversion and Management.The article was published on 2014-08-01. It has received 194 citations till now. The article focuses on the topics: PID controller & Control theory.read more
Citations
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Monthly runoff forecasting based on LSTM–ALO model
TL;DR: In this article, the accuracy of hybrid long short-term memory neural network and ant lion optimizer model (LSTM-ALO) in prediction of monthly runoff was investigated.
Journal ArticleDOI
Wind power prediction using hybrid autoregressive fractionally integrated moving average and least square support vector machine
TL;DR: In this paper, a hybrid autoregressive fractionally integrated moving average and least square support vector machine model is proposed to forecast short-term wind power, which takes advantage of the respective superiority of autoregression fractionally integrating moving average (AFIMA) and the least square SVM (LSVM).
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Fractional-order load-frequency control of interconnected power systems using chaotic multi-objective optimization
Indranil Pan,Saptarshi Das +1 more
TL;DR: The effect of augmenting two different chaotic maps along with the uniform random number generator (RNG) in the popular MOO algorithm-the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is explored.
Journal ArticleDOI
An adaptively fast fuzzy fractional order PID control for pumped storage hydro unit using improved gravitational search algorithm
TL;DR: In this article, an adaptive fast fuzzy fractional order PID (AFFFOPID) control method for pumped storage hydro unit (PSHU) is proposed, which is based on the standard gravitational search algorithm accelerates convergence speed with a combination of the Pbest-Gbest-guided strategy and adaptive elastic-ball method.
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Hamiltonian modeling of multi-hydro-turbine governing systems with sharing common penstock and dynamic analyses under shock load
TL;DR: In this article, the authors proposed a universal dynamic mathematical model of the multi-hydro-turbine governing system, which is fitted into the theoretical framework of the generalized Hamiltonian system, utilizing the method of orthogonal decomposition.
References
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Journal ArticleDOI
A fast and elitist multiobjective genetic algorithm: NSGA-II
TL;DR: This paper suggests a non-dominated sorting-based MOEA, called NSGA-II (Non-dominated Sorting Genetic Algorithm II), which alleviates all of the above three difficulties, and modify the definition of dominance in order to solve constrained multi-objective problems efficiently.
Journal Article
Simulated Binary Crossover for Continuous Search Space.
TL;DR: A real-coded crossover operator is developed whose search power is similar to that of the single-point crossover used in binary-coded GAs, and SBX is found to be particularly useful in problems having mult ip le optimal solutions with a narrow global basin where the lower and upper bo unds of the global optimum are not known a priori.
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Fractional-order systems and PI/sup /spl lambda//D/sup /spl mu//-controllers
TL;DR: In this article, a fractional-order PI/sup/spl lambda/D/sup /spl mu/controller with fractionalorder integrator and fractional order differentiator is proposed.
A combined genetic adaptive search (GeneAS) for engineering design
Kalyanmoy Deb,Mayank Goyal +1 more
TL;DR: The proposed technique is compared with binarycoded genetic algorithms, Augmented Lagrange multiplier method, Branch and Bound method and Hooke and Jeeves pattern search method and the solutions obtained are superior than those obtained with other methods.
Journal ArticleDOI
Tuning and auto-tuning of fractional order controllers for industry applications
TL;DR: In this article, a method for tuning the PI λ D μ controller is proposed to fulfill five different design specifications, including gain crossover frequency, phase margin, and iso-damping property of the system.