Modeling and adaptive force control of milling by using artificial techniques

Journal of Intelligent Manufacturing

Volumn 23, Issue 5, 2012, Pages 1805-1815

  Zuperl, U ^a   Cus, F ^a   Reibenschuh, M ^a  

^a UNIVERSITY OF MARIBOR   (Slovenia)

Author keywords

Adaptive force control; End milling; Hybrid modeling; Neural networks

Indexed keywords

ADAPTIVE ADJUSTMENT; ADAPTIVE CONTROLLERS; ADAPTIVE FORCE CONTROL; BALL END MILLING; CNC MILLING; COMBINED SYSTEM; CONTROL PRINCIPLE; CONTROL SCHEMES; CUTTING FORCES; CUTTING PARAMETERS; CUTTING PROCESS; DESIGN CONTROLLERS; END-MILLING; EVOLUTIONARY STRATEGIES; FEED-FORWARD; GLOBAL STABILITY; HIGH ROBUSTNESS; HYBRID MODELING; HYBRID PROCESS; MACHINING EFFICIENCY; MILLING SYSTEMS; NEURAL CONTROL; NONHOMOGENEITY; OFF-LINE OPTIMIZATION; PROCESS DYNAMICS; TOOL WEAR; WORKPIECE MATERIALS;

ADAPTIVE CONTROL SYSTEMS; BALL MILLING; CUTTING TOOLS; EVOLUTIONARY ALGORITHMS; FORCE CONTROL; FUZZY LOGIC; MILLING (MACHINING); NEURAL NETWORKS; OPTIMIZATION; TURNING; VIBRATIONS (MECHANICAL);

PROCESS CONTROL;

EID: 84870939926     PISSN: 09565515     EISSN: 15728145     Source Type: Journal    
DOI: 10.1007/s10845-010-0487-z     Document Type: Article

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