Comparative study between neural network and sliding mode observer for process diagnostic: Application to three tank system

2021 ◽  
Author(s):  
Asma Basly ◽  
Lotfi Mhamdi ◽  
Hedi Dhouibi
Keyword(s):  
Neural Network ◽  
Comparative Study ◽  
Sliding Mode ◽  
Sliding Mode Observer ◽  
Diagnostic Application ◽  
Tank System

Robust adaptive anti-windup wheel slip tracking control for intelligent vehicle with fast terminal sliding mode observer

2020 ◽  
Vol 234 (14) ◽  
pp. 3373-3384
Author(s):  
Jiaxu Zhang ◽  
Shiying Zhou
Keyword(s):  
Neural Network ◽  
Tracking Control ◽  
Sliding Mode ◽  
Sliding Mode Observer ◽  
Intelligent Vehicle ◽  
Control Law ◽  
Wheel Slip ◽  
Terminal Sliding Mode ◽  
Fast Terminal Sliding Mode ◽  
Robust Adaptive

Aiming at the requirement of the intelligent vehicle for the fast and stable tracking control of the wheel slip, a novel robust adaptive anti-windup wheel slip tracking control method with fast terminal sliding mode observer is proposed. First, a fast terminal sliding mode observer based on equivalent control on the sliding surface is proposed to estimate the states of the wheel slip dynamic system to lay the foundation for the full state feedback control law design. Second, a robust adaptive anti-windup wheel slip tracking control law with lumped uncertainty observer and additional anti-windup dynamics is derived based on Lyapunov-based method. The lumped uncertainty observer utilizes the nonlinear mapping ability of the radius basis function neural network to estimate and compensate the lumped uncertainty of the system, and the unknown optimal weight vector of the radius basis function neural network is updated by adaptive law. The additional anti-windup dynamics is used to suppress the effect of the input saturation on the stability of the system. Finally, the performance of the proposed method is verified through simulations of various maneuvers on vehicle dynamics simulation software.

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