Bounded decoupling control for flexible‐joint robot manipulators with state estimation. Issue 16 (9th September 2020)

• Record Type: Journal Article
• Authors: Cheng, Xin; Liu, Huashan
• Is Part Of: IET control theory & applications. Volume 14:Issue 16(2020)
• Page Start: 2348
• Page End: 2358
• Publication Date: 2020-09-09
• Subjects: control system synthesis -- closed loop systems -- uncertain systems -- Kalman filters -- robust control -- radial basis function networks -- state estimation -- tracking -- adaptive control -- manipulators -- neurocontrollers -- control nonlinearities -- nonlinear filters; closed‐loop tracking control -- flexible‐joint robot manipulator -- bounded controller -- state measurements -- joint motors -- slow subsystems -- fast subsystems -- adaptive scheme combining backstepping control -- control law -- bounded decoupling control -- extended Kalman filter; Control theory -- Periodicals; Automatic control -- Periodicals; 629.8312
• DOI: 10.1049/iet-cta.2019.1007
• Languages: English
• ISSNs: 1751-8644

Abstract

Abstract : This study proposes a bounded controller for flexible‐joint robot manipulators that only requires state measurements of joint motors. Firstly, the singular perturbation theory is used to decouple the dynamics model of the flexible‐joint robot manipulator into slow and fast subsystems. Then, a saturated adaptive scheme combining backstepping control and radial basis function neural network approximator is applied to make the controller bounded and simplify the control law for the slow subsystem, and a new filtering operator is used in the fast subsystem to enhance the overall performance. Furthermore, the extended Kalman filter is involved to eliminate the states measurements of links in the closed‐loop tracking control. Finally, the stability of the whole system is analysed and the effectiveness of the proposed approach is verified.