Adaptive self-learning controller design for feedrate maximisation of machining pro
#1

[attachment=4651]

Adaptive self-learning controller design for feedrate maximisation of machining process

F. Cus, U. Zuperl*, E. Kiker, M. Milfelner
Faculty of Mechanical Engineering, University of Maribor,
Smetanova 17, 2000 Maribor, Slovenia
* Corresponding author: uros.zuperl[at]uni-mb.si
Received 05.09.2008; published in revised form 01.12.2008

ABSTRACT
Purpose: Of this paper: The purpose of this paper is to built an adaptive control system which controlling the cutting force and maintaining constant roughness of the surface being milled by digital adaptation of cutting parameters. Design/methodology/approach: The paper discusses the use of combining the methods of neural networks, fuzzy logic and PSO evolutionary strategy (Particle Swarm Optimization) in modeling and adaptively controlling the process of end milling. An overall approach of hybrid modeling of cutting process (ANfis-system), used for working out the CNC milling simulator has been prepared. The basic control design is based on the control scheme (UNKS) consisting of two neural identificators of the process dynamics and primary regulator. Findings: The research has shown that neural control scheme has significant advantages over conventional controllers. The experimental results show that not only does the milling system with the design controller have high robustness, and global stability but also the machining efficiency of the milling system with the adaptive controller is much higher than for traditional CNC milling system. Experiments have confirmed efficiency of the adaptive control system, which is reflected in improved surface quality and decreased tool wear. Research limitations/implications: The proposed architecture for on-line determining of optimal cutting conditions is applied to ball-end milling in this paper, but it is obvious that the system can be extended to other machines to improve cutting efficiency. In this way the system compensates all disturbances during the cutting process: tool wear, non-homogeneity of the workpiece material, vibrations, chatter etc. Practical implications: The results of experiments demonstrate the ability of the proposed system to effectively regulate peak cutting forces for cutting conditions commonly encountered in end milling operations. Applicability of methodology of adaptive adjustment of cutting parameters is experimentally demonstrated and tested on a 4-axis CNC milling machine Heller. The high accuracy of results within a wide range of machining parameters indicates that the system can be practically applied in industry. Originality/value: By the hybrid process modeling and feed-forward neural control scheme (UNKS) the combined system for off-line optimization and adaptive adjustment of cutting parameters is built. Keywords: Artificial Intelligence Methods; Machining; Force control; Adaptive control with optimisation
for more information about the topic please visit :-


http://journalammepapers_amme06/184.pdf
Reply

Important Note..!

If you are not satisfied with above reply ,..Please

ASK HERE

So that we will collect data for you and will made reply to the request....OR try below "QUICK REPLY" box to add a reply to this page
Popular Searches: bisinesa studies pro, presentation clicker for macbook pro, profit maximisation vs wealth maximisation seminor topic, pro net communication wiki, list the difference between profit and wealth maximisation, design of self supported steelchimney, questionnaire of sales pro,

[-]
Quick Reply
Message
Type your reply to this message here.

Image Verification
Please enter the text contained within the image into the text box below it. This process is used to prevent automated spam bots.
Image Verification
(case insensitive)

Possibly Related Threads...
Thread Author Replies Views Last Post
  cooling system in i.c. engine,design aproach attar.raj 7 7,837 08-07-2015, 02:34 PM
Last Post: seminar report asees
Thumbs Up Design, Analysis, Fabrication And Testing Of A Composite Leaf Spring computer science crazy 3 3,173 05-09-2013, 11:43 AM
Last Post: computer topic
  Design & Fabrication of Hydraulic Crane seminar class 2 5,677 26-04-2013, 04:19 PM
Last Post: computer topic
  Design, Analysis, Fabrication And Testing Of A Composite Leaf Spring computer science crazy 6 9,614 06-04-2013, 10:01 AM
Last Post: computer topic
  Cutting tool (machining) seminar surveyer 2 4,665 29-11-2012, 02:24 PM
Last Post: seminar details
  ELECTRONBEAM MACHINING computer science crazy 2 12,132 10-11-2012, 11:24 AM
Last Post: seminar details
  Electro Discharge Machining computer science crazy 2 3,731 17-10-2012, 02:21 PM
Last Post: seminar details
  Adaptive Control machining full report project report tiger 2 5,885 17-10-2012, 01:55 PM
Last Post: seminar details
  F1 Track Design and Safety computer science crazy 5 7,840 08-09-2012, 12:37 AM
Last Post: [email protected]
  Autonomous Military Robotics:   Risk, Ethics, and Design      computer girl 0 1,368 12-06-2012, 12:34 PM
Last Post: computer girl

Forum Jump: