DocumentCode
2030114
Title
Pre-filter design for high speed contouring machines
Author
Chang, Bill C H ; Ko, Roy C. ; Halgamuge, Saman K.
Author_Institution
Dept. of Mech. & Manuf. Eng., Melbourne Univ., Parkville, Vic., Australia
Volume
3
fYear
1999
fDate
1999
Firstpage
1100
Abstract
High-speed and high-precision tracking control is required for future contouring machine tools. It is known that, by pre-filtering the command trajectory in an appropriate way, the contouring error can be effectively reduced. This paper presents the result of a hybrid approach applied to pre-filter design, which incorporates a MLP (multilayer perceptron) neural network to enhance the performance of a recently-proposed adaptive calibrating controller. Due to the presence of nonlinearities, such as friction and signal quantization, the proposed method further reduces the contouring error by taking advantage of the nonlinear and learning nature of the neural network. Simulation results on a dynamic model of a commercial laser profiling machine are demonstrated
Keywords
adaptive control; calibration; control nonlinearities; errors; filters; friction; laser materials processing; learning (artificial intelligence); machine tools; motion control; multilayer perceptrons; neurocontrollers; performance index; quantisation (signal); tracking; adaptive calibrating controller; command trajectory prefiltering; contouring error reduction; contouring machine tools; dynamic model; friction; high-precision tracking control; high-speed contouring machines; laser profiling machine; multilayer perceptron; neural network learning; nonlinearities; performance enhancement; pre-filter design; signal quantization; simulation; Adaptive control; Control systems; Error correction; Mechatronics; Motion control; Neural networks; Poles and zeros; Programmable control; Tracking; Transfer functions;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Information Processing, 1999. Proceedings. ICONIP '99. 6th International Conference on
Conference_Location
Perth, WA
Print_ISBN
0-7803-5871-6
Type
conf
DOI
10.1109/ICONIP.1999.844689
Filename
844689
Link To Document