Pitch control for wind turbine systems using optimization, estimation and compensation

Gao, Richie; Gao, Zhiwei

doi:10.1016/j.renene.2016.01.057

Cited by 134 publications

(88 citation statements)

References 18 publications

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“…The simulation study for a 4.8 MW wind turbine model has well demonstrated the effectiveness of the proposed fault estimation technique. It is encouraged to develop resilient control techniques [28] for wind turbine systems characterized by nonlinear stochastic Brownian systems.…”

Section: Discussionmentioning

confidence: 99%

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Robust fault estimation for stochastic Takagi-Sugeno fuzzy systems

Liu

Binns

Shao

2016

IECON 2016 - 42nd Annual Conference of the IEEE Industrial Electronics Society

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Abstract-Nowadays, industrial plants are calling for highperformance fault diagnosis techniques to meet stringent requirements on system availability and safety in the event of component failures. This paper deals with robust fault estimation problems for stochastic nonlinear systems subject to faults and unknown inputs relying on Takagi-Sugeno fuzzy models. Augmented approach jointly with unknown input observers for stochastic Takagi-Sugeno models is exploited here, which allows one to estimate both considered faults and full system states robustly. The considered unknown inputs can be either completely decoupled or partially decoupled by observers. For the un-decoupled part of unknown inputs, which still influence error dynamics, stochastic input-to-state stability properties are applied to take nonzero inputs into account and sufficient conditions are achieved to guarantee bounded estimation errors under bounded unknown inputs. Linear matrix inequalities are employed to compute gain matrices of the observer, leading to stochastic input-to-state-stable error dynamics and optimization of the estimation performances against un-decoupled unknown inputs. Finally, simulation on wind turbine benchmark model is applied to validate the performances of the suggested fault reconstruction methodologies.

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Section: Discussionmentioning

confidence: 99%

“…Then the system can be described in the form of plant (2). The actuator fault taken into account occurs in reference of generator torque with the following value: (28) And the sensor fault is assumed to be decrease of the first output. The estimation results of full system states and concerned faults are shown in Figs.…”

Section: Simulationmentioning

confidence: 99%

Robust fault estimation for stochastic Takagi-Sugeno fuzzy systems

Liu

Binns

Shao

2016

IECON 2016 - 42nd Annual Conference of the IEEE Industrial Electronics Society

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“…The block diagram is illustrated in Figure 5. Substitute Equation (18) into Equation (17) to linearize the map between the tracking command v and the system output y . Therefore, a linear controller can be designed to satisfy the control objectives.…”

Section: Theory Of Feedback Linearization Controlmentioning

confidence: 99%

“…In case that some nonlinear forms may exist in the system and some states have no relation with the system input u, the stability of the zero dynamics is necessary for closed-loop stability. Substitute Equation (18) into Equation (17) to linearize the map between the tracking command v and the system output y. Therefore, a linear controller can be designed to satisfy the control objectives.…”

Section: Theory Of Feedback Linearization Controlmentioning

confidence: 99%

“…Figure 11 shows the experimental results of the path-positioning control of the pitch angle with stroke of 15 • in 20 s under the loading torque calculated by the disturbance system model derived in Equation (17) where the practical measurement results of wind speed of a 2MW wind turbine in Taiwan are given. The disturbance loading torque is inserted during the path-positioning control.…”

Section: Disturbance Rejection Of Pitch Control Systemmentioning

confidence: 99%

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A Novel Pitch Control System of a Large Wind Turbine Using Two-Degree-of-Freedom Motion Control with Feedback Linearization Control

Wang

Chiang

2016

Energies

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Pitch Control plays a significant role for a large wind turbine. This study investigates a novel robust hydraulic pitch control system of a large wind turbine. The novel hydraulic pitch control system is driven by a novel high efficiency and high response hydraulic servo system. The pitch controller, designed by two degree-of-freedom (2-DOF) motion control with feedback linearization, is developed to enhance the controllability and stability of the pitch control system. Furthermore, the full-scale testbed of the hydraulic pitch control system of a large wind turbine is developed for practically experimental verification. Besides, the wind turbine simulation software FAST is used to analyze the motion of the blade which results are given to the testbed as the disturbance load command. The 2-DOF pitch controller contains a feedforward controller with feedback linearization theory to overcome the nonlinearities of the system and a feedback controller to improve the system robustness for achieving the disturbance rejection. Consequently, the novel hydraulic pitch control system shows excellent path tracking performance in the experiments. Moreover, the robustness test with a simulated disturbance load generated by FAST is performed to validate the reliability of the proposed pitch control system.

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Comparative study of the pitch control of a wind turbine using Linear Quadratic Gaussian and the Unrestricted Horizon Predictive Controller

Junior

Trentini

Prioste

2020

Int Trans Electr Energ Syst

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This paper proposes a comparative study among a widely known optimal control approach (Linear Quadratic Gaussian-LQG) and a novel predictive one (Unrestricted Horizon Predictive Controller-UHPC) for the pitch control of a grid-connected wind turbine. The main challenge for the use of predictive controllers in power systems is the size of plant's model and controller's sampling time, which increase substantially the computational cost. On the other hand, the UHPC promises a lower computational cost, which is a welcome feature for power system applications. For the development of this work, first, the wind turbine is implemented at a simulation environment to allow its linearization and state-space modelling. Later, both controllers are presented and equated. Finally, the wind turbine is modelled and simulated in two benchmark systems: a Single-Machine Infinite Bus (SMIB) system and a 11-bars test system. The simulation results show that the UHPC presents lower control oscillations for external perturbations of the grid, leading to less mechanical stress on the generator, which tends to increase its lifespan.

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Pitch control for wind turbine systems using optimization, estimation and compensation

Cited by 134 publications

References 18 publications

Robust fault estimation for stochastic Takagi-Sugeno fuzzy systems

Robust fault estimation for stochastic Takagi-Sugeno fuzzy systems

A Novel Pitch Control System of a Large Wind Turbine Using Two-Degree-of-Freedom Motion Control with Feedback Linearization Control

Comparative study of the pitch control of a wind turbine using Linear Quadratic Gaussian and the Unrestricted Horizon Predictive Controller

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