On the convergence of an extended state observer for nonlinear systems with uncertainty

By B. Guo, Zhi-liang Zhao. Systems & control letters (Print), 2011

865 citations recorded by the source corpus.

Subfields: Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/09a1ab61a4873e8380ad2e6d46708de034c34989

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. Jun Yang
2. Shihua Li
3. Lei Guo
4. Wen‐Hua Chen
5. Jianyong Yao
6. Yi Huang
7. Wenchao Xue
8. Zhe Gao

Citations in the corpus

• Extended-State-Observer-Based Output Feedback Nonlinear Robust Control of Hydraulic Systems With Backstepping (2014, background): “In addition, the proof difficulty of the closed-loop stability associated with ESO-based controllers is still open, although there are some research works [34]–[36].”
• Active disturbance rejection control for nonlinear fractional‐order systems (2016, background): “The research on the convergence of ESO for nonlinear systems with uncertainty was offered in [12].”
• Sliding mode control and active disturbance rejection control to the stabilization of one‐dimensional Schrödinger equation subject to boundary control matched disturbance (2014, background): “Its convergence has been proved for lumped parameter systems in [20].”
• ADRC With Adaptive Extended State Observer and its Application to Air–Fuel Ratio Control in Gasoline Engines (2015, methodology): “Additionally, [28] and [29] suggested a design method for the gain of nonlinear feedback functions to ensure the stability of nonlinear ESO and ADRC.”
• Active disturbance rejection control: methodology and theoretical analysis. (2014, background): “Guo and Zhao [59,62] opened the theoretical analysis of nonlinear ESO (NESO) and ADRC (NADRC) for nonlinear time varying uncertain systems.”
• On convergence of nonlinear active disturbance rejection for SISO systems (2012, neutral): “The convergence of the extended state observer is presented in [3] where it is shown that (1.”
• Disturbance-Observer-Based Control and Related Methods—An Overview (2016, methodology): “recently in developing rigorous tools for analyzing theoretic properties such as stability [21], [22].”
• Output-Feedback Path-Following Control of Autonomous Underwater Vehicles Based on an Extended State Observer and Projection Neural Networks (2018, background): “turbance, and even deviations in control coefficients from their nominal value can be estimated, in addition to recovering unmeasured state information [40]–[42].”