首页|Study Results from National Autonomous University of Mexico (UNAM) Update Unders tanding of Robotics (On the Exact Parameter Estimation for Robot Manipulators Wi thout Persistence of Excitation)
Study Results from National Autonomous University of Mexico (UNAM) Update Unders tanding of Robotics (On the Exact Parameter Estimation for Robot Manipulators Wi thout Persistence of Excitation)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Robotics is the subjec t of a report. According to news reporting out of Mexico City, Mexico, by NewsRx editors, the research stated, "Adaptive control is one of the most employed tec hniques to achieve trajectory tracking of robot manipulators. Although it is des irable to obtain exact parameter estimation, most adaptive schemes need the pers istency of excitation (PE) condition on the regressor to be satisfied." Financial support for this research came from DGAPA#x2013;UNAM. Our news journalists obtained a quote from the research from the National Autono mous University of Mexico (UNAM), "In the recent years, the so-called dynamic re gressor extension and mixing (DREM) procedure was developed to provide an altern ative in the design of adaptive laws with conditions different from PE. When met , the improvement in parameter estimation is remarkable, but when not, adaptatio n can simply stop, which might be unacceptable for control purposes. This articl e proposes for the first time a composite scheme, which combines the standard gr adient adaptive law with a DREM-based additional term with the following propert ies: 1) Trajectory tracking for joint desired positions and velocities is guaran teed; 2) in the absence of PE, if a new condition that can partially be verified online for the additional DREM-based term is matched, then exact parameter esti mation takes place in finite time."
Mexico CityMexicoNorth and Central A mericaEmerging TechnologiesMachine LearningRobotRoboticsNational Auton omous University of Mexico (UNAM)
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