Rejection of varying-frequency periodic load disturbances in wind-turbines through active disturbance rejection-based control

Coral-Enríquez, Horacio; Cortés‐Romero, John; Dorado-Rojas, Sergio A.

doi:10.1016/j.renene.2019.04.001

Cited by 31 publications

(20 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…According to the cascade structure of a piezo-actuated nanopositioning stage shown in Fig. 1 [26], hysteresis model depicted by (19) and linear model depicted by (20) are connected in series to simulate the dynamics of a positioning stage in simulations. The LADRC and the VBADRC are designed respectively.…”

Section: Simulation Resultsmentioning

confidence: 99%

On the Disturbance Rejection of a Piezoelectric Driven Nanopositioning System

Wei¹,

Xia

Xue

et al. 2020

IEEE Access

View full text Add to dashboard Cite

Nanopositioning systems are very popular and playing an increasingly vital role in micro and nano-scale positioning industry due to their unique ability to achieve high-precision and high-speed operation. However, hysteresis, commonly existing in piezoelectric actuators, degrades the precision seriously. Uncertain dynamics and sensor noises also greatly affect the accuracy. To address those challenges, a variable bandwidth active disturbance rejection control (VBADRC) is proposed and realized on a nanopositioning stage. All undesired issues are estimated by a time-varying extended state observer (TESO), and cancelled out by a variable bandwidth controller. Convergence of the TESO, advantages of a TESO over a linear extended state observer (LESO), and the closed-loop stability of the VBADRC are proven theoretically. Improvements of the VBADRC versus the linear active disturbance rejection control (LADRC) are validated by simulations and experiments. Both numerical and experimental results demonstrate that the VBADRC is not only able to provide the same disturbance estimation ability as the LADRC, but also more powerful in noise attenuation and reference tracking.

show abstract

Section: Simulation Resultsmentioning

confidence: 99%

On the Disturbance Rejection of a Piezoelectric Driven Nanopositioning System

Wei¹,

Xia

Xue

et al. 2020

IEEE Access

View full text Add to dashboard Cite

show abstract

“…Some studies focus on the vibration characteristics of wind turbine under the influence of wind, especially the impact of wind shear and tower shadow [2,3]. To suppress the wind turbine vibration caused by wind, several control strategies have been studied [5,8,14,17]. The influence of waves on the vibration characteristics of the wind turbine needs further study, and the control strategy to suppress the vibration of the wind turbine caused by wind and waves needs to be proposed.…”

Section: Wave Model and Wave Force Calculationmentioning

confidence: 99%

“…It was found that the individual pitch control method is very effective for smoothing the fluctuation of the blade root load of wind turbines in [6,7]. Coral-Enriquez et al [8] provided two individual pitch control schemes to attenuate the main periodic load components of blade flap-wise and hub yaw/tilt-wise bending moments in wind turbines under varying-frequency conditions. Jones et al [9] pointed out the limitations of conventional individual pitch control based on blade root load feedback, and then presented an additional cascaded feedback controller based upon a local blade inflow measurement on each blade to better reduce blade root flap-wise load.…”

Section: Introductionmentioning

confidence: 99%

Vibration Reduction Strategy for Offshore Wind Turbines

et al. 2020

View full text Add to dashboard Cite

The operational environment of offshore wind turbines is much more complex than that of onshore wind turbines. Facing the persistent wind and wave forces, offshore wind turbines are prone to vibration problems, which are not conducive to their long-term operation. Under this background, first, how the wave affects the vibration characteristics of offshore wind turbines is analyzed. Based on the existing wave and wave load models, we analytically show that there exist fluctuating components related to the hydrodynamic frequency in the aerodynamic load and aerodynamic torque of offshore wind turbines. Simulation results based on a GH Bladed platform further validates the analysis. Second, in order to reduce the joint impacts of the wave, wind shear and tower shadow on the wind turbine, a variable pitch control method is proposed. The integrated tower top vibration acceleration signal is superimposed on the collective pitch reference signal, then the triple frequency (3P) fluctuating component of the wind turbine output power and the azimuth angle of each blade are converted into the pitch angle adjustment signal of each blade, which is superimposed on the collective pitch signal for individual pitch control. The simulation results show that the proposed pitch control strategy can effectively smooth the fluctuation of blade root flap-wise load caused by wind and wave, and significantly reduce the fluctuation of aerodynamic torque and output power of offshore wind turbines.

show abstract

“…Worse still, in some applications, there are also narrow-band torque disturbances in addition to the wide-band torque disturbances. [8][9][10][11][12] The nonvanishing narrow-band torque disturbances will cause residual vibrations and even excite the friction-induced limit cycle if they are not sufficiently rejected. Therefore, a robust motor control method without the need of velocity measurement, which can effectively reject the multiple disturbances, especially the friction and the narrow-band torque disturbances, is urgently needed in practice.…”

Section: Introductionmentioning

confidence: 99%

Disturbance observer‐based robust motor control enhanced by adaptive neural network in the absence of velocity measurement

Piao

Tan

Wang³

et al. 2022

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

High‐precision servo motor control has been a challenging problem due to the multiple disturbances such as the friction, the load variation and the wide/narrow‐band torque disturbances. Particularly, the discontinuous and fast time‐varying friction is very difficult to be compensated, which tends to trigger the undesirable limit cycle. In addition, the friction is a function of the angular velocity, which makes the online compensation extremely hard in the absence of velocity measurement. To make the matter worse, the nonvanishing narrow‐band torque disturbances in some applications often cause residual vibrations if they are not sufficiently rejected. To address these problems, a robust motor control method, which can effectively reject the multiple disturbances without velocity measurement, is proposed in this article. To be specific, an adaptive hybrid model, which includes an adaptive neural network and a sign function, is employed to compensate the discontinuous and fast time‐varying friction dynamics. Furthermore, by incorporating the internal models of the narrow‐band disturbances into the plant, a resonant extended state observer is designed to estimate the remaining lumped disturbance. To derive the high‐order derivatives of the angular position, a fixed‐time‐convergent differentiator is employed. Different from the previous studies, elaborately designed filters are introduced in the adaptive laws. In this way, the possible degradation of transient performance and stability robustness caused by the adaptive control can be effectively avoided. The closed‐loop stability can be rigorously proved by using the Lyapunov theory. Finally, extensive experiments are performed on a servo motor to validate the effectiveness of the proposed method.

show abstract

Rejection of varying-frequency periodic load disturbances in wind-turbines through active disturbance rejection-based control

Cited by 31 publications

References 41 publications

On the Disturbance Rejection of a Piezoelectric Driven Nanopositioning System

On the Disturbance Rejection of a Piezoelectric Driven Nanopositioning System

Vibration Reduction Strategy for Offshore Wind Turbines

Disturbance observer‐based robust motor control enhanced by adaptive neural network in the absence of velocity measurement

Contact Info

Product

Resources

About