Adaptive neural network based prescribed performance control for teleoperation system under input saturation

• DOI: 10.1016/j.jfranklin.2015.01.032
• Publication Date: 2015-02-14T06:47:03Z
• Authors: Yana Yang; Chao Ge; Hong Wang; Xiaoyi Li; Changchun Hua
• Keywords: Teleoperation; Linear matrix inequality; Transient (computer programming); Saturation (graph theory); Position (finance)

Abstract 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.