Adaptive neural network based prescribed performance control for teleoperation system under input saturation. Issue 5 (May 2015)

• Record Type: Journal Article
• Authors: Yang, Yana; Ge, Chao; Wang, Hong; Li, Xiaoyi; Hua, Changchun
• Is Part Of: Journal of the Franklin Institute. Volume 352:Issue 5(2015:May)
• Page Start: 1850
• Page End: 1866
• Publication Date: 2015-05
• Subjects: Science -- Periodicals; Technology -- Periodicals; Patents -- United States -- Periodicals; 505
• DOI: 10.1016/j.jfranklin.2015.01.032
• Languages: English
• ISSNs: 0016-0032

Abstract

<abstract abstract-type="author" id="ab0005"> <title id="sect0005">Abstract</title> <sec> <p id="sp0065">This paper addresses the stability and position synchronization problems for bilateral nonlinear teleoperation system with asymmetric constant time delays under input saturation. Compared with previous work, not only the steady-state performance but also the transient-state performance is considered. In the presence of system uncertainties and external disturbances, the corresponding adaptive neural network (ANN) based prescribed performance control (PPC) scheme is designed. Moreover, the time-dependent stability conditions are derived by applying the linear matrix inequality (LMI). Finally, in simulation comparisons with P+d (proportion plus differential) controller are conducted, simulation results are presented to demonstrate the effectiveness of the proposed PPC approach.</p> </sec> </abstract>