首页|Findings on Robotics and Machine Learning Reported by Investigators at North Chi na University of Technology (Improved Multiverse Optimizer-based Anti-saturation Model Free Adaptive Control and Its Application To Manipulator Grasping Systems)
Findings on Robotics and Machine Learning Reported by Investigators at North Chi na University of Technology (Improved Multiverse Optimizer-based Anti-saturation Model Free Adaptive Control and Its Application To Manipulator Grasping Systems)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Investigators discuss new findings in Robotics an d Machine Learning. According to news originating from Beijing, People’s Republi c of China, by NewsRx correspondents, research stated, “To address the stable gr asping control issue in manipulator grasping systems, this manuscript proposes a n improved multiverse optimizer-based anti-saturation model-free adaptive contro l (IMVO-AS-MFAC) algorithm. Initially, the manuscript converts the manipulator g rasping system into an equivalent data model through dynamic linearization techn iques.”
BeijingPeople’s Republic of ChinaAsiaRobotics and Machine LearningAlgorithmsMathematicsNorth China University of Technology
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