An Efficient Control Implementation for Inverter Based Harmony Search Algorithm

2017 ◽  
Vol 8 (1) ◽  
pp. 279
Author(s):  
Mushtaq Najeeb ◽  
Hamdan Daniyal ◽  
Ramdan Razali ◽  
Muhamad Mansor
Keyword(s):  
Optimization Algorithm ◽  
Search Algorithm ◽  
Dynamic Performance ◽  
Harmony Search ◽  
Absolute Error ◽  
Fast Response ◽  
Pi Controller ◽  
Harmony Search Algorithm ◽  
Voltage Source ◽  
Output Performance

This research implements a PI controller based on harmony search (HS) optimization algorithm for voltage source inverter to improve the output performance under step load change conditions. The HS algorithm aims to handle the trial and error procedure used in finding the PI parameters and then apply the proposed control algorithm via the eZdsp TMS320F28355 board to link the inverter prototype with the Matlab Simulink. The mean absolute error (MAE) is used as an optimization problem to minimize the output voltage error for the developed controller (PI-HS) as compared to the PI controller based particale swarm optimization algorithm (PI-PSO). Based on the experimental results obtained, it is noted that the proposed controller (PI-HS) provides a good dynamic performance, robustness, constant voltage amplitude, and fast response in terms of overshoot, transient, and steady-state.

Normal Parameter Reduction in Soft Set Based on Harmony Search Algorithm

2014 ◽  
Vol 644-650 ◽  
pp. 2173-2176
Author(s):  
Zhi Kong ◽  
Guo Dong Zhang ◽  
Li Fu Wang
Keyword(s):  
Data Mining ◽  
Optimization Algorithm ◽  
Search Algorithm ◽  
Harmony Search ◽  
Harmony Search Algorithm ◽  
Soft Set ◽  
Intelligent Optimization ◽  
Parameter Reduction ◽  
Intelligent Optimization Algorithm ◽  
Normal Parameter

The normal parameter reduction in soft set is difficult to application in data mining because of great calculation quantity. In this paper, the intelligent optimization algorithm, the harmony search algorithm, is applied to solve the problem. The normal parameter reduction model is constructed and the harmony search algorithm is designed. Experience has shown that the method is feasible and fast..

scholarly journals Harmony Search Algorithm Based Control of DFIG Wind Energy System in Multi Machine Power Systems

2020 ◽  
Vol 9 (5) ◽  
pp. 320-327
Keyword(s):  
Power Systems ◽  
Wind Energy ◽  
Search Algorithm ◽  
Harmony Search ◽  
Energy System ◽  
Pi Controller ◽  
Harmony Search Algorithm ◽  
Detailed Model ◽  
Whole Process ◽  
Wind Energy System

In wind energy conversion system (WECS) Double Fed Induction generator (DFIG) preferred, though it has many advantages when used in wind energy system, but DFIG is very sensitive to the grid disruptions. When an error occurs DFIG is greatly affected in the multi- machine system. The voltage and power gets deviated. The main purpose of this paper is to stabilize the DFIG under fault conditions, but the performance of the DFIG is depends on the PI controller parameters. By using Harmony Search Algorithm (HSA) technique the PI controller parameters are tuned, by this the efficiency of a system can be improved and the voltage and power oscillations can be reduced. The simulation is performed in detailed model of four-machine two-area system. The whole process is done in the MATLAB Simulink software. A comparative study is done between tuning of PI parameter with HSA and actual existing system.

Geometric Optimization of a Delta Type Parallel Robot Using Harmony Search Algorithm

Robotica ◽  
2019 ◽  
Vol 37 (9) ◽  
pp. 1494-1512
Author(s):  
Mahmood Mazare ◽  
Mostafa Taghizadeh
Keyword(s):  
Optimal Design ◽  
Search Algorithm ◽  
Dynamic Performance ◽  
Harmony Search ◽  
Parallel Robot ◽  
Harmony Search Algorithm ◽  
Geometric Optimization ◽  
Global Error ◽  
Reachable Workspace ◽  
Sensitivity Indices

SummaryThis paper aims to provide an optimal design of geometric parameters of a special architecture of the delta parallel mechanism, in order to improve positioning accuracy, workspace size, and kinematic and dynamic performance characteristics. In the studied 3[P2(US)] robot, the radius of both fixed and moving platforms, length of the connecting rods, and installation angle of the actuators of the manipulator are chosen as the decision variables. These parameters are optimized to maximize the weighted objective function, comprising workspace volume, global dexterity, global mass, global error, and global error sensitivity indices. Optimizations are performed employing two distinct algorithms, Genetic and Harmony Search whose results confirm each other. The optimal design of the robot leads to maximum workspace size, high dexterity, and dynamic performance, with a minimum error of the end-effector position in its reachable workspace.

scholarly journals QoS and QoE aware multi objective resource allocation algorithm for cloud gaming

2021 ◽  
pp. 1-18
Author(s):  
Koné Kigninman Désiré ◽  
Eya Dhib ◽  
Nabil Tabbane ◽  
Olivier Asseu
Keyword(s):  
Resource Allocation ◽  
Optimization Algorithm ◽  
Search Algorithm ◽  
Fitness Function ◽  
Harmony Search ◽  
Harmony Search Algorithm ◽  
Potential Game ◽  
Resource Allocation Algorithm ◽  
Allocation Algorithm ◽  
Level Of Satisfaction

Cloud gaming is an innovative model that congregates video games. The user may have different Quality-of-Experience (QoE), which is a term used to measure a user’s level of satisfaction and enjoyment for a particular service. To guarantee general satisfaction for all users with limited cloud resources, it becomes a major issue in the cloud. This paper leverages a game theory in the cloud gaming model with resource optimization to discover optimal solutions to resolve resource allocation. The Rider-based harmony search algorithm (Rider-based HSA), which is the combination of Rider optimization algorithm (ROA) and Harmony search algorithm (HSA), is proposed for resource allocation to improve the cloud computing system’s efficiency. The fitness function is newly devised considering certain QoE parameters, which involves fairness index, Quantified experience of players (QE), and Mean Opinion Score (MOS). The proposed Rider-based HSA showed better performance compared to Potential game-based optimization algorithm, Proactive resource allocation algorithm, QoE-aware resource allocation algorithm, Distributed algorithm, and Yusen Li et al., with maximal fairness of 0.999, maximal MOS of 0.873, and maximal QE of 1.

scholarly journals Comparative Study of Harmony Search Algorithm and its Applications in China, Japan and Korea

2020 ◽  
Vol 10 (11) ◽  
pp. 3970 ◽  
Author(s):  
Mohammad Nasir ◽  
Ali Sadollah ◽  
Jin Hee Yoon ◽  
Zong Woo Geem
Keyword(s):  
Comparative Study ◽  
Computer Science ◽  
Optimization Algorithm ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Harmony Search ◽  
Harmony Search Algorithm ◽  
Fields Of Study ◽  
Complex Optimization ◽  
Near Future

Harmony Search (HS) is a music-inspired optimization algorithm for solving complex optimization problems that imitate the musical improvisational process. This paper reviews the potential of applying the HS algorithm in three countries, China, South Korea, and Japan. The applications represent several disciplines in fields of study such as computer science, mathematics, electrical/electronic, mechanical, chemical, civil, and industrial engineering. We anticipate an increasing number of HS applications from these countries in near future.

Hybrid Harmony Search Algorithms

2015 ◽  
Vol 24 (06) ◽  
pp. 1530001 ◽  
Author(s):  
Nazmul Siddique ◽  
Hojjat Adeli
Keyword(s):  
Local Search ◽  
Optimization Algorithm ◽  
Heuristic Search ◽  
Search Algorithm ◽  
Harmony Search ◽  
Computational Cost ◽  
Population Based ◽  
Search Algorithms ◽  
Harmony Search Algorithm ◽  
Solution Quality

Harmony search algorithm (HSA) is a music-inspired population-based meta-heuristic search and optimization algorithm. In order to improve exploration or global search ability, exploit local search more effectively, increase convergence speed, improve solution quality, and minimize computational cost, researchers have advanced the concept of hybridizing HSA with other algorithms. This article presents a review of hybrid harmony search algorithms.

Application of Static Var Compensator (SVC) With PI Controller for Grid Integration of Wind Farm Using Harmony Search

2016 ◽  
Vol 17 (5) ◽  
pp. 555-566 ◽  
Author(s):  
H. E. Keshta ◽  
A. A. Ali ◽  
E. M. Saied ◽  
F. M. Bendary
Keyword(s):  
Wind Farm ◽  
Reactive Power ◽  
Control Method ◽  
Search Algorithm ◽  
Harmony Search ◽  
Pi Controller ◽  
Harmony Search Algorithm ◽  
Optimization Techniques ◽  
Operating Conditions ◽  
Static Var Compensator

Abstract Large-scale integration of wind turbine generators (WTGs) may have significant impacts on power system operation with respect to system frequency and bus voltages. This paper studies the effect of Static Var Compensator (SVC) connected to wind energy conversion system (WECS) on voltage profile and the power generated from the induction generator (IG) in wind farm. Also paper presents, a dynamic reactive power compensation using Static Var Compensator (SVC) at the a point of interconnection of wind farm while static compensation (Fixed Capacitor Bank) is unable to prevent voltage collapse. Moreover, this paper shows that using advanced optimization techniques based on artificial intelligence (AI) such as Harmony Search Algorithm (HS) and Self-Adaptive Global Harmony Search Algorithm (SGHS) instead of a Conventional Control Method to tune the parameters of PI controller for SVC and pitch angle. Also paper illustrates that the performance of the system with controllers based on AI is improved under different operating conditions. MATLAB/Simulink based simulation is utilized to demonstrate the application of SVC in wind farm integration. It is also carried out to investigate the enhancement in performance of the WECS achieved with a PI Controller tuned by Harmony Search Algorithm as compared to a Conventional Control Method.

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