Convergence and stability analysis of active disturbance rejection control for first-order nonlinear dynamic systems

Chen, Zengqiang; Wang, Yongshuai; Sun, Mingwei; Sun, Qinglin

doi:10.1177/0142331218794812

Cited by 33 publications

(25 citation statements)

References 22 publications

(21 reference statements)

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“…It achieves an immediate and dynamic estimation and elimination of the generalized disturbance by returning its prediction to the control port with basic calculations using control law with output feedback. With ADRC, controlling a sophisticated uncertain nonlinear plant is transformed approximately into a simple linear time-invariant system [5,6]. The supremacy that makes it such a powerful control instrument is that it is a model-free method, instead of a model-based technique.…”

Section: Active Disturbance Rejection Controlmentioning

confidence: 99%

Improved Active Disturbance Rejection-Based Decentralized Control for MIMO Nonlinear Systems: Comparison with The Decoupled Control Scheme

et al. 2020

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A decentralized control scheme is developed in this paper based on an improved active disturbance rejection control (IADRC) for output tracking of square Multi-Input-Multi-Output (MIMO) nonlinear systems and compared with the decoupled control scheme. These nonlinear MIMO systems were subjected to exogenous disturbances and composed of high couplings between subsystems, input couplings, and uncertain elements. In the decentralized control scheme, it was assumed that the input couplings and subsystem couplings were both parts of the generalized disturbance. Moreover, the generalized disturbance included other components, such as exogenous disturbances and system uncertainties, and it was estimated within the context of Active Disturbance rejection Control (ADRC) via a novel nonlinear higher order extended state observer (NHOESO) from the measured output and canceled from the input channel in a real-time fashion. Then, based on the designed NHOESO, a separate feedback control law was developed for each subsystem to achieve accurate output tracking for given reference input. With the proposed decentralized control scheme, the square MIMO nonlinear system was converted into approximately separate linear time invariant Single-Input-Single-Output (SISO) subsystems. Numerical simulations in a MATLAB environment showed the effectiveness of the proposed technique, where it was applied on a hypothetical MIMO nonlinear system with strong couplings and vast uncertainties. The proposed decentralized control scheme reduced the total control signal energy by 20.8% as compared to the decoupled control scheme using Conventional ADRC (CADRC), while the reduction was 27.18% using the IADRC.

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Section: Active Disturbance Rejection Controlmentioning

confidence: 99%

Improved Active Disturbance Rejection-Based Decentralized Control for MIMO Nonlinear Systems: Comparison with The Decoupled Control Scheme

et al. 2020

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“…The core idea of ADRC is to construct an extended state observer (ESO) to estimate the 'generalized disturbance', including the lumped uncertain dynamics and unknown disturbances, and then the generalized disturbance are compensated quickly by a state feedback controller. The stability and robustness of ADRC to various uncertainties are well proved [19]- [23]. Therefore, it is natural to develop improved ADRCs for uncertain systems with time delay.…”

Section: Introductionmentioning

confidence: 99%

Linear Active Disturbance Rejection Control for Processes With Time Delays: IMC Interpretation

Tan

2020

IEEE Access

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This paper investigates linear active disturbance rejection control (ADRC) for processes with time delay. In the past years several modified active disturbance rejection control methods, including Smith predictor based ADRC (SP-ADRC), predictor observer based ADRC (PO-ADRC) and delayed designed ADRC (DD-ADRC) have been proposed to tackle systems with time delay. In this paper it is shown that these modified ADRCs can be interpreted in the framework of a two-degree-of-freedom (TDOF) internal model control (IMC), so the analysis and design can all be done via the well-known IMC framework. With the aid of the TDOF-IMC framework, the three modified ADRCs are compared and some interesting conclusions are drawn. Analysis and simulation results show that PO-ADRC structure is the best delay compensation structure among the three methods. However, the overall performance of the three methods will also depend on the tuned parameters, and the robustness measure is helpful in tuning the parameters to achieve compromise in performance. INDEX TERMS Systems with time delay, active disturbance rejection control (ADRC), internal model control (IMC), smith predictor, predictor observer.

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“…ADRC [11], put forward in 1989, has been theoretically verified and continually improved [12][13][14][15]. ADRC mainly consists of an extended state observer (ESO), a tracking differentiator (TD) and error feedback control laws, and focuses on solving the uncertain external disturbance.…”

Section: Introductionmentioning

confidence: 99%

“…When the controller structure has been determined, appropriate ESO and PID control laws could be designed/selected according to real situations, so as to improve the system robustness. More details can be found in [11,12,15,19].…”

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confidence: 99%

Active Disturbance Rejection Control of Multi-Joint Industrial Robots Based on Dynamic Feedforward

Cheng

Zhou

et al. 2019

Electronics

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In this paper, the dynamics-based high-performance robot motion control technology has been mainly studied, and the overall structure is controlled via dynamics forward, given the nonlinearity, strong coupling and time-variability of robots. Considering the unavailability of precise robot model parameters and the uncertain disturbance in real operation, we put forward an active disturbance rejection control (ADRC) strategy based on dynamic feedforward, aiming to improve the control robustness and combining the simple structure, strong anti- disturbance ability, and no restriction from the control model of ADRC. Given the multi-joint coupling of robots, controlled decoupling is conducted by using dynamic characteristics. The ADRC cascade control structure and algorithm based on dynamic feedforward have been studied and the closed-loop stability of the system is investigated by analyzing the system dynamic linearization compensation and the anti-disturbance ability of the extended state observer. Experiments have shown the new strategy is more robust over uncertain disturbance than the conventional proportional-integral-derivative control strategy.

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Convergence and stability analysis of active disturbance rejection control for first-order nonlinear dynamic systems

Cited by 33 publications

References 22 publications

Improved Active Disturbance Rejection-Based Decentralized Control for MIMO Nonlinear Systems: Comparison with The Decoupled Control Scheme

Improved Active Disturbance Rejection-Based Decentralized Control for MIMO Nonlinear Systems: Comparison with The Decoupled Control Scheme

Linear Active Disturbance Rejection Control for Processes With Time Delays: IMC Interpretation

Active Disturbance Rejection Control of Multi-Joint Industrial Robots Based on Dynamic Feedforward

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