Adaptive Neural Tracking Control for a Class of Nonstrict-Feedback Stochastic Nonlinear Systems With Unknown Backlash-Like Hysteresis

By Huanqing Wang, Bing Chen, Kefu Liu, Xiaoping Liu, Chong Lin. IEEE Transactions on Neural Networks and Learning Systems, 2014

314 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Materials Chemistry

View Paper: https://www.semanticscholar.org/paper/a54fe1aa30e9a830334ff20a6200b2c0040abe0e

How researchers see this paper

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

In Control and Systems Engineering

1. Shaocheng Tong
2. Yong-ming Li
3. Hongyi Li
4. Qi Zhou
5. Lijie Wang
6. Tie-shan Li
7. Chengwei Wu
8. Shuai Sui

In Materials Chemistry

1. Shaocheng Tong
2. Yong-ming Li

Citations in the corpus

• Adaptive Fuzzy Tracking Control Design for SISO Uncertain Nonstrict Feedback Nonlinear Systems (2016, methodology): “Assumption 1 is a common restrictive condition adopted extensively in adaptive backstepping design; for example, see [2], [3], [30], and [31].”
• Adaptive Fuzzy Control of Nonlinear Systems With Unmodeled Dynamics and Input Saturation Using Small-Gain Approach (2017, methodology): “[56] utilized NN to handle unknown nonlinear terms and then presented an adaptive NN control for stochastic systems.”
• Observer-Based Adaptive Fuzzy Tracking Control of MIMO Stochastic Nonlinear Systems With Unknown Control Directions and Unknown Dead Zones (2015, methodology): “More recently, Wang et al. [33], [34] investigated adaptive fuzzy state feedback control problems for a class of stochastic nonlinear systems with unknown hysteresis and saturation, respectively, and Yu et al. [35] developed an adaptive fuzzy state feedback control method for a class of stochastic…”