Weiqun Wang

TL;DR: A SMDOB-based tracking control strategy for Euler–Lagrange systems with modeling uncertainties and external disturbances and the significant advantage lies in semiglobal exponential stability guarantee for the combined observer–controller system without the assumption that the time derivatives of modeling uncertainties are bounded by constants.

TL;DR: A robot, namely iLeg, is designed for the purpose of rehabilitation of patients with hemiplegia or paraplegia, and two controllers, i.e., passive training controller and active training controller, are proposed, which takes advantage of the proportional-integral control method to solve the trajectory tracking problem.

TL;DR: In this paper, the authors adopt the maximum correntropy criterion (MCC) to train the output weights, obtaining a Correntropy-based BLS (C-BLS), which is expected to achieve excellent robustness to outliers while maintaining the original performance of the standard BLS in the Gaussian or noise-free environment.

TL;DR: The results show that the classification performance can be improved significantly by using the proposed MI-BCI in terms of the classification accuracy (ACC), the area under the curve (AUC) and the F1 score (paired t-test, ${p} < 0.05$ ).

TL;DR: An indirectly generating strategy is designed, by which the valid initial solutions of the optimization problem can be found with good efficiency, and a recursive optimization method based on the optimization of the dynamic model and the exciting trajectories, is proposed to further reduce the condition number.