The effect of nonminimum-phase zero locations on the performance of feedforward model-inverse control techniques in discrete-time systems

Butterworth, Jeffrey A.; Pao, Lucy Y.; Abramovitch, Daniel Y.

doi:10.1109/acc.2008.4586900

Cited by 70 publications

(39 citation statements)

References 19 publications

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“…In previous work [17], three different model-inverse techniques [18] were tried: the non-minimum-phase zeros ignore (NPZ-Ignore), the zero-phase-error tracking controller (ZPETC), and the zero-magnitude-error tracking controller (ZMETC). These worked well when controlling a linear plant model, but performed worse than the baseline controller alone when simulated in FAST.…”

Section: Gain-scheduled Model-inverse Feedforward Controlmentioning

confidence: 99%

Adding feedforward blade pitch control to standard feedback controllers for load mitigation in wind turbines

et al. 2011

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Section: Gain-scheduled Model-inverse Feedforward Controlmentioning

confidence: 99%

Adding feedforward blade pitch control to standard feedback controllers for load mitigation in wind turbines

et al. 2011

Self Cite

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“…To obtain the desired feedforward controller, the transfer function G T should be inverted. In case the system is non-minimum phase, a zero-magnitude-error tracking controller stable inversion technique is used 28 to compute a stable inverse.…”

Section: Model-based Feedforward Controlmentioning

confidence: 99%

Predictive control of an experimental wind turbine using preview wind speed measurements

2014

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The development of a more reliable method of measuring the wind field upstream of a turbine (light detection and ranging) has enabled the implementation of feedforward-related control strategies to enhance the control performance of wind turbines. By incorporating wind speed measurements, the controller is able to anticipate upon future events and thereby improve structural load mitigation and power regulation of the wind turbine. This work aims to experimentally verify the benefits of using predictive and feedforward-based control strategies over industry standard control solutions. To achieve this, both a feedforward and a model predictive control strategy are presented, which have been validated on an experimental wind turbine in a wind tunnel. Both the model predictive controller and feedforward algorithm have shown superior performance over a baseline controller in terms of rotor speed regulation under wind speed disturbances. The experiment confirmed that a phase advantage in the control input of the predictive controller led to this performance increase. It has also been found that knowledge of just the current wind speed can already significantly increase the control performance.

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“…Therefore a stable modelinverse approximation is used instead. Three different model-inverse techniques (Butterworth et al [16]) are used: the nonminimum-phase zeros ignore (NPZ-Ignore), the zero-phase-error tracking controller (ZPETC), and the zero-magnitude-error tracking controller (ZMETC). Figure 8), even without any gain scheduling or low-pass filtering.…”

Section: • Generatormentioning

confidence: 99%

Feasibility Studies on Disturbance Feedforward Techniques to Improve Wind Turbine Load Mitigation Performance: January 2009 -- January 2010

Laks¹,

Dunne²,

Pao³

2010

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Light detection and ranging systems can measure conditions at a distance in front of wind turbines, and therefore are well suited to providing preview information of wind disturbances before they impact the turbine blades. As such, this technology makes available measurements of wind speed for use in disturbance feedforward control techniques. This study investigates disturbance feedforward and preview control to better understand the best possible improvement in load mitigation using advanced wind measurement techniques. * The work reported here also is financially supported by industry partners. † The authors thank Kathryn Johnson and Na Wang from the Colorado School of Mines for results in which feedforward control has been further augmented with additional feedback to enhance damping.

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The effect of nonminimum-phase zero locations on the performance of feedforward model-inverse control techniques in discrete-time systems

Cited by 70 publications

References 19 publications

Adding feedforward blade pitch control to standard feedback controllers for load mitigation in wind turbines

Adding feedforward blade pitch control to standard feedback controllers for load mitigation in wind turbines

Predictive control of an experimental wind turbine using preview wind speed measurements

Feasibility Studies on Disturbance Feedforward Techniques to Improve Wind Turbine Load Mitigation Performance: January 2009 -- January 2010

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