Optimal utilization of UPQC during steady state using evolutionary optimization techniques

2021 ◽  
Author(s):  
Swati A. Gade ◽  
Rahul Agrawal
Keyword(s):  
Steady State ◽  
Evolutionary Optimization ◽  
Optimization Techniques ◽  
Evolutionary Optimization Techniques

scholarly journals Proportional + integral + derivative control of nonlinear full-car electrohydraulic suspensions using global and evolutionary optimization techniques

2019 ◽  
Vol 39 (2) ◽  
pp. 393-415
Author(s):  
Olurotimi A Dahunsi ◽  
Muhammed Dangor ◽  
Jimoh O Pedro ◽  
M Montaz Ali
Keyword(s):  
Particle Swarm Optimization ◽  
Random Search ◽  
Particle Swarm ◽  
Evolutionary Optimization ◽  
Optimization Techniques ◽  
Swarm Optimization ◽  
Modified Particle Swarm Optimization ◽  
Controlled Random Search ◽  
Evolutionary Optimization Techniques ◽  
Vehicle Suspension System

Resolving the trade-offs between suspension travel, ride comfort, road holding, vehicle handling and power consumption is the primary challenge in the design of active vehicle suspension system. Multi-loop proportional + integral + derivative controllers’ gains tuning with global and evolutionary optimization techniques is proposed to realize the best compromise between these conflicting criteria for a nonlinear full-car electrohydraulic active vehicle suspension system. Global and evolutionary optimization methods adopted include: controlled random search, differential evolution, particle swarm optimization, modified particle swarm optimization and modified controlled random search. The most improved performance was achieved with the differential evolution algorithm. The modified particle swarm optimization and modified controlled random search algorithms performed better than their predecessors, with modified controlled random search performing better than modified particle swarm optimization in all aspects of performance investigated both in time and frequency domain analyses.

scholarly journals Modeling and Optimization of EDM of Metal Matrix Composite using Black Hole Algorithm

2019 ◽  
Vol 8 (3) ◽  
pp. 8094-8100
Keyword(s):  
Black Hole ◽  
Metal Matrix Composite ◽  
Matrix Composite ◽  
Metal Matrix ◽  
Electrical Discharge Machining ◽  
Evolutionary Optimization ◽  
Optimization Techniques ◽  
Experimental Investigations ◽  
Machining Processes ◽  
Evolutionary Optimization Techniques

Many advanced materials have been developed in the recent past to meet the present day technological demands. Aluminum-boron-carbide (Al-B4C) metal matrix composite (MMCs) is such a material slowly gaining popularity among researchers. The advanced machining processes (AMPs) are best manufacturing method to shape these types of innovative materials. The experimental investigations on Al-B4C MMC using one such AMP known as electrical discharge machining (EDM) have been carried out in the present work. Important electrical parameters of EDM have been considered as input control factors to evaluate two of the most important responses. Four evolutionary optimization techniques; black hole, differential evolution, shuffled frog leaping algorithm and coordinated aggregation based particle swarm optimization is applied to get best out of the process. Finally all the evolutionary optimization techniques have been compared for their performances.

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