(UL)
  • Adaptive controller design for feedrate maximization of machining process
    Čuš, Franc, 1953- ...
    The paper presents an adaptive control system which has been built to control the cutting force and thus maintain a constant roughness of the surface being milled by digital adaptation of cutting ... parameters. The paper discusses the use of combining thr mrthods of neural networks, fuzzy logic and PSO evolutionary strategy (Particle Swarm Optimization) in modeling and adaptively controlling the process of enf meilling. An overall approcah to hybrid modeling of cutting processes (ANfis-syatem), used for working out the CNC milling simulator has been prepared. The basic control design is based on the control scheme (UNKS) consisting of twp neural identificators of the process dynamics and primary regulator. The experimental results show that not only does the milling system with the design controller have high robustness and global stability, but laso the machining efficiency of the milling system withthe adaptive controller is much higher than for traditonal CNC milling system. Experiments have confirmed the efficiency of the adaptive control system, which is reflected in improved surface quality and decreased tool wear. The proposed architecture for on-line determination 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 machining processes. The experimental results demonstrate the ability of the proposed system to effectively regulate peak cutting forces for cutting conditions commonly encountered in end-milling operations. The high accuracy of results indicates that the system is applicable in industry. By the hybrid process modelling and feed forward neural control scheme (UNKS) the combined system for off-lineoptimization and adaptive adjustment of cutting parameters is built.
    Vir: Journal of achievements in materials and manufacturing engineering : JAMME. - ISSN 1734-8412 (Vol. 17, iss. 1/2, Jul.-Aug. 2006, str. 237-240)
    Vrsta gradiva - članek, sestavni del
    Leto - 2006
    Jezik - angleški
    COBISS.SI-ID - 10528278

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