Study on evaluation of perpendicularity errors with an improved particle swarm optimisation for planar lines
by Ke Zhang; Shengze Wang
International Journal of Modelling, Identification and Control (IJMIC), Vol. 18, No. 1, 2013

Abstract: According to characteristics of perpendicularity error evaluation of planar lines, an improved particle swarm optimisation (PSO) is proposed to evaluate the minimum zone error. The evolutional optimum model and the calculation process are introduced in detail. Compared with conventional optimum methods such as simplex search and Powell method, PSO can find the global optimal solution, and the precision of calculating result is very good. Compared to other intelligence computation algorithms such as genetic algorithm (GA), PSO is easier to carry out with fewer parameters to adjust. Then, the objective function calculation approaches for using the particle swarm optimisation algorithm to evaluate minimum zone error are formulated. Finally, the control experiment results evaluated by different method such as the least square, simplex search, Powell optimum methods and genetic algorithm (GA), indicate that the proposed method can provide better accuracy on perpendicularity error evaluation effectively, and is well suited for position error evaluation.

Online publication date: Tue, 05-Feb-2013

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Modelling, Identification and Control (IJMIC):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com