Optimization method based on Generalized Pattern Search Algorithm to identify bridge parameters indirectly by a passing vehicle

2014 ◽  
Vol 333 (2) ◽  
pp. 364-380 ◽  
Author(s):  
Wei-ming Li ◽  
Zhi-hui Jiang ◽  
Tai-long Wang ◽  
Hong-ping Zhu
Keyword(s):  
Search Algorithm ◽  
Optimization Method ◽  
Pattern Search ◽  
Pattern Search Algorithm ◽  
Generalized Pattern Search

Optimal Design of a Parallel Micromanipulator for Precision Machining

2009 ◽  
Vol 69-70 ◽  
pp. 590-594
Author(s):  
Z.F. Wang ◽  
Guan Wang ◽  
Shi Ming Ji ◽  
J.H. Sun
Keyword(s):  
Optimal Design ◽  
Search Algorithm ◽  
Design Procedure ◽  
Pattern Search ◽  
Design Parameters ◽  
Precision Machining ◽  
Pattern Search Algorithm ◽  
Generalized Pattern Search ◽  
Precision And Accuracy ◽  
Design Result

A parallel micromanipulator (PmM) which can be applied into the precision machining is optimized in the paper. This paper adopts a methodology to determine a set of optimal design parameters of PmM whose workspace is as close as possible of being equal to a prescribed cuboid dexterous workspace (PCDW). The kinematic problem is analyzed in brief to determine the design parameters and their relation. Then, an optimal design procedure which adopts the generalized pattern search algorithm in the genetic algorithm and direct search toolbox of Matlab is proposed to solve these problems. As an applying example, the results of four cases PCDW to PmM are presented. And the design result is compared with a concept of the distance between the best state of the PmM and the requirement of the operation task. The method and result of this paper are very useful for the design of micromanipulator for the machining field which requires the high precision and accuracy.

scholarly journals A Generalized Pattern Search Algorithm Methodology for solving an Under-Determined System of Equality Constraints to achieve Power System Observability using Synchrophasors

2021 ◽  
Vol 2090 (1) ◽  
pp. 012125
Author(s):  
Nikolaos P. Theodorakatos ◽  
Miltiadis Lytras ◽  
Rohit Babu
Keyword(s):  
Power System ◽  
Cost Function ◽  
Search Algorithm ◽  
Pattern Search ◽  
Equality Constraints ◽  
Pattern Search Algorithm ◽  
Generalized Pattern Search ◽  
The Impact ◽  
Linear Cost ◽  
Number Of Iterations

Abstract The impact of the generalized pattern search algorithm (GPSA) on power system complete observability utilizing synchrophasors is proposed in this work. This algorithmic technique is an inherent extension of phasor measurement unit (PMU) minimization in a derivative-free framework by evaluating a linear objective function under a set of equality constraints that is smaller than the decision variables in number. A comprehensive study about the utility of such a system of equality constraints under a quadratic objective has been given in our previous paper. The one issue studied in this paper is the impact of a linear cost function to detect optimality in a shorter number of iterations, whereas the cost is minimized. The GPSA evaluates a linear cost function through the iterations needed to satisfy feasibility and optimality criteria. The other issue is how to improve the performance of convergence towards optimality using a gradient-free mathematical algorithm. The GPSA detects an optimal solution in a fewer number of iterations than those spent by a recursive quadratic programming (RQP) algorithm. Numerical studies on standard benchmark power networks show significant improvement in the maximum observability over the existing measurement redundancy generated by the RQP optimization scheme already published in our former paper.

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