Robust adaptive backstepping control for a class of constrained non-affine nonlinear systems via self-organizing Hermite-polynomial-based neural network disturbance observer
Robust adaptive backstepping control for a class of constrained non-affine nonlinear systems via self-organizing Hermite-polynomial-based neural network disturbance observer
复制标题
基于自组织 Hermite 多项式神经网络扰动观测器的一类约束非仿射非线性系统的鲁棒自适应反步控制
DOI：
10.1177/1687814017702811
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发表时间：
2017-05
影响因子：
2.1
通讯作者：
cui wang
中科院分区：
文献类型：
--
作者：
qiang zhang;cui wang
The article proposes a robust control approach based on self-organizing Hermite-polynomial-based neural network disturbance observer for a class of non-affine nonlinear systems with input saturation, state constraint, and unknown compound disturbance. Using Taylor series expansion, a hyperbolic tangent function, the non-affine nonlinear system with input saturation is transformed into time-varying affine system without input saturation, which can reduce step n + 1 of the backstepping technique compared with conventional method. Next, a self-organizing Hermite-polynomial-based neural network disturbance observer is proposed to estimate the compound disturbance online. Then, the auxiliary systems are designed to solve state constraint for subsystems, and hyperbolic tangent function is used to approximate the saturated control input. Simulation results proved the effectiveness of the proposed control scheme.
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影响因子：
--
作者：
Swati Swarnkar;Mangal Kothari
通讯作者：
Swati Swarnkar;Mangal Kothari
高阶不确定非仿射系统的自适应神经控制：仿射系统方法的转换
影响因子：
6.4
作者：
Meng, Wenchao;Yang, Qinmin;Jagannathan, Sarangapani;Sun, Youxian
通讯作者：
Sun, Youxian
影响因子：
6
作者：
Chun-Fei Hsu
通讯作者：
Chun-Fei Hsu
影响因子：
5.7
作者：
Mou Chen;Jing Yu
通讯作者：
Mou Chen;Jing Yu
DOI：
10.1016/j.jfranklin.2014.05.006
发表时间：
2014-08
期刊：
J. Frankl. Inst.
影响因子：
--
作者：
M. M. Arefi-M.;J. Zarei;H. Karimi
通讯作者：
M. M. Arefi-M.;J. Zarei;H. Karimi