Dynamic Surface Control Using Neural Networks for a Class of Uncertain Nonlinear Systems With Input Saturation

• Published in: IEEE transaction on neural networks and learning systems Vol. 26; no. 9; pp. 2086 - 2097
• Main Authors: Chen, Mou, Tao, Gang, Jiang, Bin
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.09.2015; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive systems; Artificial neural networks; Backstepping; Backstepping control; Computer Simulation; Control design; dynamic surface control (DSC); Feedback; Humans; Neural networks; Neural Networks (Computer); nonlinear disturbance observer (NDO); Nonlinear Dynamics; Nonlinear systems; Observers; robust control; Robustness; uncertain nonlinear system; Uncertainty; Backstepping control; nonlinear disturbance observer (NDO); robust control; dynamic surface control (DSC); uncertain nonlinear system

In this paper, a dynamic surface control (DSC) scheme is proposed for a class of uncertain strict-feedback nonlinear systems in the presence of input saturation and unknown external disturbance. The radial basis function neural network (RBFNN) is employed to approximate the unknown system function....