Dear Editor, This letter considers the control problem of an experimental flexible manipulator in position tracking, vibration suppression, and saturation compensation. Based on the backstepping technology and a Nussb...Dear Editor, This letter considers the control problem of an experimental flexible manipulator in position tracking, vibration suppression, and saturation compensation. Based on the backstepping technology and a Nussbaum function, we develop an anti-windup control to restrain the manipulator’s vibration, realize the desire trajectory tracking, and eliminate the saturation.展开更多
Dear Editor,This letter proposes a parameter-free multiple kernel clustering(MKC)method by using shifted Laplacian reconstruction.Traditional MKC can effectively cluster nonlinear data,but it faces two main challenges...Dear Editor,This letter proposes a parameter-free multiple kernel clustering(MKC)method by using shifted Laplacian reconstruction.Traditional MKC can effectively cluster nonlinear data,but it faces two main challenges:1)As an unsupervised method,it is up against parameter problems which makes the parameters intractable to tune and is unfeasible in real-life applications;2)Only considers the clustering information,but ignores the interference of noise within Laplacian.展开更多
基金supported in part by the National Natural Science Foundation of China(62273112)the Scientific Research Projects of Guangzhou Education Bureau(202032793)+1 种基金the Guangzhou University-Hong Kong University of Science and Technology Joint Research Collaboration Fund(YH202205)the Open Research Fund from the Guangdong Laboratory of Artificial Intelligence and Digital Economy[Shenzhen(SZ)](GML-KF-22-27)。
文摘Dear Editor, This letter considers the control problem of an experimental flexible manipulator in position tracking, vibration suppression, and saturation compensation. Based on the backstepping technology and a Nussbaum function, we develop an anti-windup control to restrain the manipulator’s vibration, realize the desire trajectory tracking, and eliminate the saturation.
基金Guangxi Key Laboratory of Machine Vision and Intelligent Control(2022B07)the Open Research Fund from Guangdong Laboratory of Artificial Intelligence and Digital Economy(SZ)(GML-KF-22-04)+1 种基金the Natural Science Foundation of Southwest University of Science and Technology(22zx7101)the National Natural Science Foundation of China(62106209)。
文摘Dear Editor,This letter proposes a parameter-free multiple kernel clustering(MKC)method by using shifted Laplacian reconstruction.Traditional MKC can effectively cluster nonlinear data,but it faces two main challenges:1)As an unsupervised method,it is up against parameter problems which makes the parameters intractable to tune and is unfeasible in real-life applications;2)Only considers the clustering information,but ignores the interference of noise within Laplacian.
