Active Disturbance Rejection Control Design With Suppression of Sensor Noise Effects in Application to DC–DC Buck Power Converter

Łakomy, Krzysztof; Madoński, Rafał; Dai, Bin; Yang, Jun; Kicki, Piotr; Ansari, Maral; Li, Shihua

doi:10.1109/tie.2021.3055187

Cited by 92 publications

(43 citation statements)

References 24 publications

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“…Finally, motivated by the obtained results of this research, the design of controls that considers the important problem of active disturbance rejection [65,66] and applications in mobile robotics and subactuated systems are considered as future work.…”

Section: Discussionmentioning

confidence: 99%

Robust Flatness Tracking Control for the “DC/DC Buck Converter‐DC Motor” System: Renewable Energy‐Based Power Supply

et al. 2021

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The design of a robust flatness-based tracking control for the DC/DC Buck converter-DC motor system is developed in this paper. The design of the control considers the dynamics of a renewable energy power source that plays the role of the primary power supply associated with the system. The performance and robustness of the control is verified through simulations via MATLAB-Simulink when abrupt changes in some parameters of the system are taken into account. Also, experiments are performed by using a built prototype of the DC/DC Buck converter-DC motor system, a TDK-Lambda G100-17 programmable DC power supply, MATLAB-Simulink, and the DS1104 board from dSPACE. In this regard, the TDK-Lambda G100-17 is implemented with the aim of emulating photovoltaic panels through the solar array mode for generating the power supply of the system. Thus, both simulations and experiments show the effectiveness of the proposed control scheme.

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Section: Discussionmentioning

confidence: 99%

Robust Flatness Tracking Control for the “DC/DC Buck Converter‐DC Motor” System: Renewable Energy‐Based Power Supply

et al. 2021

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“…It is also clear for this proposition, that the measurement noise and limited sampling remain the important factors in designing ADRC techniques in practice. (d) The scalability of ADRC scheme is retained in its error-based modification as one can easily change the observer from linear ESO (26) to a different one to address certain disadvantages of current design (like the limited disturbance reconstruction capabilities seen in ExpD and its potential remedy in SimD in form of inclusion of higher-order disturbance model). Further improvement in quality could also be possibly obtained by modifications in the controller and/or observer structure (e.g., utilization of noise suppressing observers [25,26] or reduced-order observers [18]).…”

Section: Discussionmentioning

confidence: 99%

“…The error-based ADRC has been successfully applied by now to a variety of control problems including mechanical vibration compensation [21,22], robotic manipulator control [23,24], observer design with suppression of sensor noise [25][26][27], position control of a telescope mount [28], UAV control [29,30], as well as power electronics control [31,32].…”

Section: Introductionmentioning

confidence: 99%

Simplifying ADRC design with error-based framework: case study of a DC–DC buck power converter

Madoński

Łakomy

Yang

2021

Control Theory Technol.

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In this work, the problem of designing a robust control algorithm for a DC-DC buck power converter is investigated. The applied solution is based on a recently proposed error-based version of the active disturbance rejection control (ADRC) scheme, in which the unknown higher-order terms of the reference signal are treated as additional components of the system "total disturbance". The motivation here is to provide a practical following of a reference voltage trajectory for the buck converter in specific cases where neither the analytical form of the desired signal nor its future values are known a'priori, hence cannot be directly used for control synthesis. In this work, the application of the error-based ADRC results in a practically appealing control technique, with compact structure, simplified control rule, and intuitive tuning (inherited from the conventional output-based ADRC scheme). Theoretical, numerical, and experimental results are shown to validate the efficacy of the error-based ADRC in buck converter control, followed by a discussion about the revealed theoretical and practical limitations of this approach.

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“…Peng et al combined the ADRC with the consensus algorithm to control multi-degree-of-freedom (DOF) parallel electrical manipulator systems, demonstrating better performance [38]. Łakomy et al improved the performance of the ADRC by using a new observer structure to address the problem caused by high-frequency measurement noise in practice [39]. Chi et al proposed an improved ADRC, using local dynamic linearization to realize the nonlinear system affine to control the input in the globally Lipschitz nonlinear discrete-time system [40].…”

Section: Introductionmentioning

confidence: 99%

ADRC-Based Control Method for the Vascular Intervention Master–Slave Surgical Robotic System

Zhou

Guo

et al. 2021

Micromachines

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In vascular interventional surgery, surgeons operate guidewires and catheters to diagnose and treat patients with the assistance of the digital subtraction angiography (DSA). Therefore, the surgeon will be exposed to X-rays for extended periods. To protect the surgeon, the development of a robot-assisted surgical system is of great significance. The displacement tracking accuracy is the most important issue to be considered in the development of the system. In this study, the active disturbance rejection control (ADRC) method is applied to guarantee displacement tracking accuracy. First, the core contents of the proportional–integral–derivative (PID) and ADRC methods are analyzed. Second, comparative evaluation experiments for incremental PID and ADRC methods are presented. The results show that the ADRC method has better performance of than that of the incremental PID method. Finally, the calibration experiments for the ADRC control method are implemented using the master–slave robotic system. These experiments demonstrate that the maximum tracking error is 0.87 mm using the ADRC method, effectively guaranteeing surgical safety.

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Active Disturbance Rejection Control Design With Suppression of Sensor Noise Effects in Application to DC–DC Buck Power Converter

Cited by 92 publications

References 24 publications

Robust Flatness Tracking Control for the “DC/DC Buck Converter‐DC Motor” System: Renewable Energy‐Based Power Supply

Robust Flatness Tracking Control for the “DC/DC Buck Converter‐DC Motor” System: Renewable Energy‐Based Power Supply

Simplifying ADRC design with error-based framework: case study of a DC–DC buck power converter

ADRC-Based Control Method for the Vascular Intervention Master–Slave Surgical Robotic System

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