An overview on recent progress of extended state observers for uncertain systems: Methods, theory, and applications

Zhang, Xiaoyan; Xue, Wenchao; Xin, Bin

doi:10.1002/adc2.89

Cited by 27 publications

(16 citation statements)

References 61 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Lemma 2. For ω c > 1, and under Assumptions 1-6, the control error subsystem in (13), parametrized by (12), is input-to-state stable, and locally satisfies e e e(t)…”

Section: Overview Of Implemented Adrc Algorithmmentioning

confidence: 99%

“…In the process of controller tuning (12), the same bandwidth-parametrization concept is utilized as in the case of the observer, but this time by placing the eigenvalues of the state matrix in closed-loop control error subsystem (13), i.e.,…”

Section: Controller Bandwidth ω Cmentioning

confidence: 99%

“…Since its inception, it has attracted considerable attention among both scholars and industry practitioners. The effectiveness of its disturbance-centric approach ( [11]) of handling uncertainties in governed systems has been verified to date in numerous control problems seen in motion, process, and power control areas [12,13]. The combination of modern control elements with pragmatism of minimum-modeling approach has made ADRC an interesting alternative to the proportional integral derivative (PID) controllers [14].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Active Disturbance Rejection Control (ADRC) Toolbox for MATLAB/Simulink

Giernacki¹,

Łakomy²,

Michalski³

et al. 2021

Preprint

View full text Add to dashboard Cite

In this paper, an active disturbance rejection control (ADRC) toolbox for MAT-LAB/Simulink is introduced. Although ADRC has already been established as a powerful robust control framework with successful industrial implementations and strong theoretical foundations, a comprehensive tool for computer-aided design of ADRC has not been developed until now. The proposed ADRC Toolbox is a response to a growing need of both scientific community and control industry looking for a straightforward software utilization of the ADRC methodology. Its main purpose is to fill the gap between current theories and applications of ADRC and to provide an easy-to-use solution to users in various control fields wanting to employ the ADRC scheme in their applications. The ADRC Toolbox contains a single, general-purpose, drag-and-drop function block allowing to synthesize a predefined ADRC-based strategy with minimal design effort. Its efficacy is validated here in both simulations and hardware experiments, conducted using a variety of problems known from motion, process, and power control areas. The proposed ADRC Toolbox is an open-source project 1 .

show abstract

“…Lemma 2. For ω c > 1, and under Assumptions 1-6, the control error subsystem in (13), parametrized by (12), is input-to-state stable, and locally satisfies e e e(t)…”

Section: Overview Of Implemented Adrc Algorithmmentioning

confidence: 99%

Section: Controller Bandwidth ω Cmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Active Disturbance Rejection Control (ADRC) Toolbox for MATLAB/Simulink

Giernacki¹,

Łakomy²,

Michalski³

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…34 Recent surveys on the variants of the conventional disturbance observers can be found in. [35][36][37] One of the common issues of these observer-based methods is the usage of conservative assumptions. To obtain asymptotic convergence of the estimation errors, previous work usually assumes the disturbance derivative to be zero 19,33 or strictly bounded.…”

Section: Introductionmentioning

confidence: 99%

“…They have been widely applied to various robotic tasks, including precise control, 31 flexible manipulation, 32 fault detection and isolation, 33 and multi‐agent system control 34 . Recent surveys on the variants of the conventional disturbance observers can be found in 35–37 . One of the common issues of these observer‐based methods is the usage of conservative assumptions.…”

Section: Introductionmentioning

confidence: 99%

Disturbance estimation for robotic systems using continuous integral sliding mode observer

Zhang

Wollherr

Najjaran

2022

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

This article presents a novel force‐sensor‐less method for the estimation of external forces for a general class of second‐order robotic systems. The method is based on the integral sliding mode observer (ISMO) which serves as a second‐order differentiator for the position measurement of the system. As a result, the system states and disturbance are estimated without explicitly using force and velocity measurements. To apply the ISMO to the general second‐order systems, a proper assumption is proposed to address their nonlinearity and discontinuity. The boundary‐layer method is applied to ensure that the virtual inputs of the observer are continuous such that the chattering phenomenon is attenuated. A Lyapunov‐based method is used to analyze the influence of the boundary layers on the convergence of the state‐ and disturbance‐estimation errors. This influence, mainly determined by the boundary‐layer scalars, is given in analytical forms as a reference for parameter selection. The method is evaluated by numerical simulation on a robot manipulator system and compared with a conventional sliding mode observer (SMO). The validation of the performance of the continuous ISMO indicates its generalizability to general second‐order robotic systems. Also, the advantage of continuous ISMO over the conventional SMO is reflected by its small estimation errors and superior responsiveness. In general, the proposed method in this paper may interest those who are seeking solutions for haptic robotic tasks without using force sensors.

show abstract

Active disturbance rejection control: Practical technology and industrial application

Xue

Xin

2021

Adv Control Appl

Self Cite

View full text Add to dashboard Cite

Active disturbance rejection control (ADRC) has been developed as an enabling technique to reduce the influence of both unmodeled uncertainties and disturbances. The key idea of ADRC is a data-driven mechanism through the extended state observer (ESO), to timely estimate the affect caused by unknown unmodeled uncertainties and disturbances. As ADRC in its nature is a model-guided data-driven method, the potential of ADRC has been gradually discovered in industry, leading to many successful applications such as manufacturing, process control, robotic systems, and energy systems. Driven by some top companies such as Texas Instruments, FreeScale, Danfoss, and so forth, ADRC has been recognized as one effective alternative control method to the dominant one: proportional-integral-derivative (PID). Hence the research on ESO/ADRC based control and its application have world-wide interest.The aim of the special issue on "Active Disturbance Rejection Control: Practical Technology and Industrial Application" is to bring together papers of ADRC with different design principles and multifarious industrial applications. Moreover, the special issue is to present the latest developments in design methods, performance analysis, and implementation technologies for ADRC and other disturbance rejection methods. Also, the issue provides an international platform for scholars in ADRC field to exchange and discuss novel ideas by submitting and reviewing contributions.Eight papers were eventually selected from a number of submissions through a strict peer-reviewed procedure. These papers are featured with ADRC based novel designs or appealing technologies to achieve disturbance/uncertainty estimation as well as attenuation. Despite different focuses, almost all papers contain both theoretic developments and successful applications. To make them easy for the reference, the selected contributions will be briefly introduced as follows.The articles 1-3 aimed to propose new ADRC methods for different kinds of uncertain plants. Li and Wang 1 constructed a fuzzy active disturbance rejection controller (FADRC) for autonomous underwater vehicle manipulator system (AUVMS). The FADRC was designed to estimate and compensate the total disturbance with fuzzy rules of parameters tuning. Moreover, in typical control tasks, the simulation results showed that FADRC can achieve better performance and consume less energy than classic fuzzy logic controllers and traditional linear ADRC. Zhao et al. 2 focused on designing nonlinear ESO for output tracking of a class of uncertain nonlinear affine systems. By using some special nonlinear functions of estimation error in ESO, more accurate estimation and smaller peaking value were achieved. The system output was capable to track the given reference signal despite a large scope of nonlinear uncertainties, which was shown by both theory and simulation. In Reference 3, an improved ADRC was conceived for output tracking of uncertain plants with unknown control direction. Without assuming the knowledge of the cont...

show abstract

An overview on recent progress of extended state observers for uncertain systems: Methods, theory, and applications

Cited by 27 publications

References 61 publications

Active Disturbance Rejection Control (ADRC) Toolbox for MATLAB/Simulink

Active Disturbance Rejection Control (ADRC) Toolbox for MATLAB/Simulink

Disturbance estimation for robotic systems using continuous integral sliding mode observer

Active disturbance rejection control: Practical technology and industrial application

Contact Info

Product

Resources

About