Robust Adaptive Tracking Control for Nonlinear Systems Based on Bounds of Fuzzy Approximation Parameters

By Yan-Jun Liu, Wei Wang, Shaocheng Tong, Yisha Liu. IEEE transactions on systems, man and cybernetics. Part A. Systems and humans, 2010

303 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Adaptive Fuzzy Control via Observer Design for Uncertain Nonlinear Systems With Unmodeled Dynamics (2013, methodology): “Moreover, by using backstepping design and the approximation property of the FLSs or the NNs, several adaptive control algorithms were developed in [25]–[27] to achieve the tracking performance for nonlinear interconnected systems in the nested form with completely unknown functions.”
Adaptive Neural Output Feedback Tracking Control for a Class of Uncertain Discrete-Time Nonlinear Systems (2011, methodology): “, u j (k) ] ; n j denotes the order of the j th subsystem; m jl represents the order difference between the j th and the lth subsystem, as introduced in [11], [20], and [34].”
Dynamic Surface Control Using Neural Networks for a Class of Uncertain Nonlinear Systems With Input Saturation (2015, methodology): “Robust adaptive tracking control scheme was proposed for nonlinear systems based on the fuzzy approximator in [21].”