Iterative learning and self-optimization techniques for the innovative railcab-system

IECON Proceedings (Industrial Electronics Conference)

Volumn , Issue , 2006, Pages 4683-4688

  Trächtler, Ansgar ^a   Münch, Eckehard ^a   Vöcking, Henner ^a  

^a Institute for Mechatronics and Design Engineering   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMOBILE ELECTRONIC EQUIPMENT; AUTOMOBILE SUSPENSIONS; ELECTRONIC GUIDANCE SYSTEMS; ELECTRONICS INDUSTRY; ENGINEERING RESEARCH; INDUSTRIAL ELECTRONICS; LEARNING SYSTEMS; MECHATRONICS; ONLINE SYSTEMS; OPTIMIZATION; REMOTE CONTROL; RESEARCH; SUSPENSIONS (COMPONENTS); TECHNOLOGY; VEHICLE SUSPENSIONS; VEHICLES;

ACTIVE GUIDANCE; ACTIVE SUSPENSION SYSTEMS; ANNUAL CONFERENCE; COLLABORATIVE RESEARCH; INFORMATION PROCESSING; INNOVATIVE SYSTEMS; ITERATIVE LEARNING; MECHATRONIC SYSTEMS; ON-LINE ADAPTATION; RAILWAY VEHICLES; SELF-OPTIMIZATION; SELF-OPTIMIZING; SYSTEM CONDITIONS; TEST BEDS;

AUTOMOBILE PARTS AND EQUIPMENT;

EID: 50249177234     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IECON.2006.347957     Document Type: Conference Paper

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