Adaptive Fuzzy Output Feedback Tracking Backstepping Control of Strict-Feedback Nonlinear Systems With Unknown Dead Zones

By Shaocheng Tong, Yong-ming Li. IEEE transactions on fuzzy systems, 2012

435 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/87d3d0ac999510379cfffe92de3d09e60cce3fa1

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. Mou Chen
5. Qi Zhou
6. Tie-shan Li
7. Lijie Wang
8. Chengwei Wu

In Statistical and Nonlinear Physics

1. Shaocheng Tong
2. Yong-ming Li
3. Hongyi Li
4. Qi Zhou
5. Mou Chen
6. Tong Wang
7. C. Ahn
8. Lijie Wang

Citations in the corpus

• Adaptive Fuzzy Control of Nonlinear Systems With Unmodeled Dynamics and Input Saturation Using Small-Gain Approach (2017, methodology): “In [31], an observer-based adaptive fuzzy tracking control strategy was developed for SISO systems subject to dead zones.”
• Adaptive Fuzzy Output Feedback Control of MIMO Nonlinear Systems With Unknown Dead-Zone Inputs (2013, methodology): “According to [23], [24], [41], [44], and [45], the optimal parameter vector θ∗ i,ji is defined as θ∗ i,ji = arg min θi , j i ∈Ω i , j i [ sup (x̄i , j i , ˆ̄ xi , j i )∈Ui , j i |Δfi,ji |] (19)”
• Observer-Based Adaptive Fuzzy Tracking Control of MIMO Stochastic Nonlinear Systems With Unknown Control Directions and Unknown Dead Zones (2015, background): “On the other hand, dead-zone is one of the most important nonsmooth nonlinearities (including hysteresis and saturation), and it often degrades system control performance and even results in instability of the control system [17], [18], [22]–[27].”
• Fuzzy Adaptive Actuator Failure Compensation Control of Uncertain Stochastic Nonlinear Systems With Unmodeled Dynamics (2014, methodology): “FAULT-TOLERANT CONTROL DESIGN AND STABILITY ANALYSIS In this section, an adaptive fuzzy FTC scheme will be developed by using the above fuzzy state observer and the backstepping technique [51]–[55], and the stability of the closed-loop system will be given.”
• Adaptive Neural Impedance Control of a Robotic Manipulator With Input Saturation (2016, neutral): “In [46], adaptive fuzzy controllers are designed via backstepping for nonlinear strict feedback systems with unknown deadzone and immeasurable states.”
• Terminal sliding mode tracking control for a class of SISO uncertain nonlinear systems. (2013, background): “In [40], adaptive fuzzy output feedback tracking backstepping control was presented for strictfeedback nonlinear systems with unknown dead zones.”