Data-driven iterative tuning based active disturbance rejection control for piezoelectric nano-positioners

Tian, Chuan; Peng, Yan

doi:10.1016/j.mechatronics.2020.102321

Cited by 23 publications

(8 citation statements)

References 27 publications

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“…It is to control systems with a high relative degree using fractional-order controllers and to enforce the planeness of the phase margin. • The LADRC control system, a control structure linked with a fractional order integral action inserted in the SPT loop, has been proposed [20,21]. • The main theoretical contribution is a new design technique of the SPT controller-based design.…”

Section: Introductionmentioning

confidence: 99%

Fractional Order Linear Active Disturbance Rejection Control for Linear Flexible Joint System

Mehedi¹,

Mansouri²,

Al‐Saggaf³

et al. 2022

Computers, Materials &Amp; Continua

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A linear flexible joint system using fractional order linear active disturbance rejection control is studied in this paper. With this control scheme, the performance against disturbances, uncertainties, and attenuation is enhanced. Linear active disturbance rejection control (LADRC) is mainly based on an extended state observer (ESO) technology. A fractional integral (FOI) action is combined with the LADRC technique which proposes a hybrid control scheme like FO-LADRC. Incorporating this FOI action improves the robustness of the standard LADRC. The set-point tracking of the proposed FO-LADRC scheme is designed by Bode's ideal transfer function (BITF) based robust closed-loop concept, an appropriate pole placement method. The effectiveness of the proposed FO-LADRC scheme is illustrated through experimental results on the linear flexible joint system (LFJS). The results show the enhancement of the robustness with disturbance rejection. Furthermore, a comparative analysis is presented with the results obtained using the integer-order LADRC and FO-LADRC scheme.

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Section: Introductionmentioning

confidence: 99%

Fractional Order Linear Active Disturbance Rejection Control for Linear Flexible Joint System

Mehedi¹,

Mansouri²,

Al‐Saggaf³

et al. 2022

Computers, Materials &Amp; Continua

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show abstract

“…ADRC was also designed and analyzed for uncertain time-delay nonlinear and nonaffine-in-control nonlinear systems recently. , A hybrid paradigm combining model-based and data-driven ADRC is proposed for a proton-exchange membrane fuel cell stack cooling control in which experiments validate the efficacy of the proposed hybrid paradigm . The authors of ref developed a data-driven iterative feedback tuning based ADRC approach to optimize the control performance by conducting controller parameter tuning iteratively from experimental test data, and simulations demonstrate significant performance improvement on nanopositioning and tracking over the conventional ADRC method.…”

Section: Introductionmentioning

confidence: 99%

Active Disturbance Rejection Control Design Based on Probabilistic Robustness for Uncertain Systems

Chen

2020

Ind. Eng. Chem. Res.

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Uncertainties always exist in practical industrial processes which result in many difficulties for controller design. To enhance the ability of closed-loop systems to handle uncertainties, an active disturbance rejection control (ADRC) design based on probabilistic robustness (PR) is proposed in this paper. The necessity of the proposed design method is explained by introducing the problem formulation. Then the principle and parameter stability region of ADRC are introduced. On the basis of these fundamentals, a design method of ADRC based on PR is proposed for uncertain systems and the corresponding design procedure is summarized, which is applicable for uncertain single-input single-output (SISO), multi-input multi-output (MIMO) and nonlinear systems. The simulation results for SISO, MIMO, and nonlinear systems illustrate that the proposed ADRC always has a larger estimated value of the probability than other comparative controllers which means that the proposed ADRC design method can not only ensure the satisfactory control performance for nominal systems, but also meet control requirements for all uncertain systems with the largest probability. In addition, the superiority of the proposed ADRC design is also verified by comparative experiments based on the Peltier temperature control platform. The proposed ADRC design method can offer a practical solution and shows a promising future for uncertain systems in practical industrial processes.

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“…The results are shown in Figures 7–8. Second, the composite controller can compensate the disturbance estimation error in real time and increase the control accuracy compared with LADRC (Tian et al, 2020). The results are shown in Figures 12–13.…”

Section: Introductionmentioning

confidence: 99%

Linear active disturbance rejection control for hysteresis compensation based on backpropagation neural networks adaptive control

Liu

Zhao

Wu³

et al. 2020

Transactions of the Institute of Measurement and Control

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This paper proposes a compound control framework for non-affine nonlinear systems facing hysteresis disturbance. The controller consists of linear active disturbance rejection control (LADRC) and backpropagation (BP) neural networks adaptive control. BP neural networks are utilized to arbitrarily approximate the uncertainty nonlinear caused by the deviation of control parameter from its nominal value and LADRC is designed to real-time estimate and compensate the disturbance with vast matched and mismatched uncertainties including unknown internal system dynamic uncertainty and external hysteresis disturbance therein. Combining the adaptive neural networks design with LADRC design techniques, a new dual-channel composite controller scheme is developed herein whereby adaptive neural networks are used as feed-forward inverse control and LADRC as closed-loop feedback control. Furthermore, as compared with a traditional control algorithm, the proposed BP-LADRC dual-channel composite controller can guarantee that the desired signal can be tracked with a small domain of the origin and it is confirmed to be effective under Lyapunov stability theory and MATLAB simulations.

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Data-driven iterative tuning based active disturbance rejection control for piezoelectric nano-positioners

Cited by 23 publications

References 27 publications

Fractional Order Linear Active Disturbance Rejection Control for Linear Flexible Joint System

Fractional Order Linear Active Disturbance Rejection Control for Linear Flexible Joint System

Active Disturbance Rejection Control Design Based on Probabilistic Robustness for Uncertain Systems

Linear active disturbance rejection control for hysteresis compensation based on backpropagation neural networks adaptive control

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