Time-Varying Quadratic-Programming-Based Error Redefinition Neural Network Control and Its Application to Mobile Redundant Manipulators

• 成果类型: Article
• 署名作者: Zheng, Lunan; Zhang, Zhijun
• 署名单位: South China University of Technology; South China University of Technology
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2021.3128470
• 发表日期: 2022
• 页码: 6151-6158
• 关键词: convergence; Manipulators; Task analysis; Robustness; quadratic programming; Biological neural networks; Recurrent neural networks; Convergence and robustness; mobile redundant manipulator (MRM); motion planning control scheme; recurrent neural networks (RNNs); time-varying quadratic programming (TV-QP)

摘要

By incorporating the redefined error monitor function into the network design, an error redefinition neural network (ERNN) is proposed to control mobile redundant manipulators to execute the tracking task in this article. The global asymptotic stability and the strong antidisturbance capability of the ERNN are proved theoretically. Furthermore, the ERNN can overcome the overshoot and constant disturbance. Meanwhile, the ERNN is input-to-state stable, while the bounded time-varying disturbance is considered as the control input.