scholarly journals Parameter Estimation of Nonlinear Systems using Lèvy Flight Cuckoo Search

2013 ◽  
Vol 78 (11) ◽  
pp. 1-6 ◽  
Author(s):  
Walid M.Aly
Keyword(s):  
Parameter Estimation ◽  
Nonlinear Systems ◽  
Cuckoo Search ◽  
Lévy Flight ◽  
Levy Flight

Design and application of an optimally tuned PID controller for DC motor speed regulation via a novel hybrid Lévy flight distribution and Nelder–Mead algorithm

2021 ◽  
pp. 014233122110196
Author(s):  
Davut Izci
Keyword(s):  
Pid Controller ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Absolute Error ◽  
Dc Motor ◽  
Cuckoo Search Algorithm ◽  
Lévy Flight ◽  
Motor Speed ◽  
Levy Flight ◽  
Speed Regulation

This paper deals with the design of an optimally performed proportional–integral–derivative (PID) controller utilized for speed control of a direct current (DC) motor. To do so, a novel hybrid algorithm was proposed which employs a recent metaheuristic approach, named Lévy flight distribution (LFD) algorithm, and a simplex search method known as Nelder–Mead (NM) algorithm. The proposed algorithm (LFDNM) combines both LFD and NM algorithms in such a way that the good explorative behaviour of LFD and excellent local search capability of NM help to form a novel hybridized version that is well balanced in terms of exploration and exploitation. The promise of the proposed structure was observed through employment of a DC motor with PID controller. Optimum values for PID gains were obtained with the aid of an integral of time multiplied absolute error objective function. To verify the effectiveness of the proposed algorithm, comparative simulations were carried out using cuckoo search algorithm, genetic algorithm and original LFD algorithm. The system behaviour was assessed through analysing the results for statistical and non-parametric tests, transient and frequency responses, robustness, load disturbance, energy and maximum control signals. The respective evaluations showed better performance of the proposed approach. In addition, the better performance of the proposed approach was also demonstrated through experimental verification. Further evaluation to demonstrate better capability was performed by comparing the LFDNM-based PID controller with other state-of-the-art algorithms-based PID controllers with the same system parameters, which have also confirmed the superiority of the proposed approach.

Cuckoo Search via Lévy Flight Applied to Optimal Water Supply System Design

2018 ◽  
pp. 383-395 ◽  
Author(s):  
Ricardo Soto ◽  
Broderick Crawford ◽  
Rodrigo Olivares ◽  
Carlos Castro ◽  
Pía Escárate ◽  
...  
Keyword(s):  
Water Supply ◽  
System Design ◽  
Cuckoo Search ◽  
Supply System ◽  
Water Supply System ◽  
Lévy Flight ◽  
Levy Flight

scholarly journals A Feature Selection Method by using Chaotic Cuckoo Search Optimization Algorithm with Elitist Preservation and Uniform Mutation for Data Classification

2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Le Wang ◽  
Yuelin Gao ◽  
Jiahang Li ◽  
Xiaofeng Wang
Keyword(s):  
Feature Selection ◽  
Search Algorithm ◽  
Chaotic Map ◽  
Feature Selection Method ◽  
Cuckoo Search ◽  
Selection Method ◽  
Lévy Flight ◽  
Levy Flight ◽  
Mutation Strategy ◽  
Nature Inspired Algorithm

Feature selection is an essential step in the preprocessing of data in pattern recognition and data mining. Nowadays, the feature selection problem as an optimization problem can be solved with nature-inspired algorithm. In this paper, we propose an efficient feature selection method based on the cuckoo search algorithm called CBCSEM. The proposed method avoids the premature convergence of traditional methods and the tendency to fall into local optima, and this efficient method is attributed to three aspects. Firstly, the chaotic map increases the diversity of the initialization of the algorithm and lays the foundation for its convergence. Then, the proposed two-population elite preservation strategy can find the attractive one of each generation and preserve it. Finally, Lévy flight is developed to update the position of a cuckoo, and the proposed uniform mutation strategy avoids the trouble that the search space is too large for the convergence of the algorithm due to Lévy flight and improves the algorithm exploitation ability. The experimental results on several real UCI datasets show that the proposed method is competitive in comparison with other feature selection algorithms.

scholarly journals Image Optimization using Cuckoo Search and Levy Flight Algorithms

2017 ◽  
Vol 178 (4) ◽  
pp. 31-36 ◽  
Author(s):  
Pooja Prashar ◽  
Nayan Jain ◽  
Shivanku Mahna
Keyword(s):  
Cuckoo Search ◽  
Lévy Flight ◽  
Levy Flight ◽  
Image Optimization
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