基于偏移量控制的MPC算法在预扭叶片振动控制中的应用
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摘要
针对风力机叶片的不稳定振动,阐述基于偏移量控制的模型预测控制(MPC)算法在预扭叶片振动控制中的应用。结构模型是基于结构阻尼计算的2D预扭典型截面,基于通用2D挥舞/摆振模型进行挥舞角/摆振角的变换,纳入了不同预扭角度下的结构阻尼。气动力是基于拟合气动系数的"六级正弦和"模型。基于偏移量控制和给定目标值的MPC算法,研究基于时域响应的稳定性分析和振动控制方法。MPC控制算法基于状态空间描述,实现位移响应分析及控制信号展示,利用罚权值实现设定点跟踪和控制信号变换,并制约输出信号幅度,迫使其急速衰减。通过变化的结构阻尼、预测水平系数和不同的目标参数下的响应分析,并对比线性二次型控制结果,验证了MPC算法的鲁棒性。
In order to deal with the unstable vibration of wind turbine blades, this study is to investigate the application of the model prediction control(MPC) algorithm based on offset control in vibration control of pretwisted blades. The structure was modeled as a 2 D pretwisted blade section with structural damping computed, which is based on the conversion from a general 2 D flap/lag model into a flapping-angle/lagging-angle model, and incorporates the structural damping under different pretwisted angles. Aerodynamic expressions are based on the fitting Sin6 model. Stability analysis of time response and vibration control were investigated based on the MPC algorithm with offset control and given target values. The MPC algorithm is based on state-space description. The MPC performance was used to realize time-domain response analysis of displacement and manipulated signal display. It uses the penalty weighting for setpoint tracking and for changes in manipulated variables, and restricts the amplitude of output signal, forcing it to decrease rapidly. The robustness of the MPC algorithm was verified by varying structural damping, the coefficients of varying prediction horizon and the response analysis of different target parameters, and the comparison of the results of linear quadratic control.
In order to deal with the unstable vibration of wind turbine blades, this study is to investigate the application of the model prediction control(MPC) algorithm based on offset control in vibration control of pretwisted blades. The structure was modeled as a 2 D pretwisted blade section with structural damping computed, which is based on the conversion from a general 2 D flap/lag model into a flapping-angle/lagging-angle model, and incorporates the structural damping under different pretwisted angles. Aerodynamic expressions are based on the fitting Sin6 model. Stability analysis of time response and vibration control were investigated based on the MPC algorithm with offset control and given target values. The MPC algorithm is based on state-space description. The MPC performance was used to realize time-domain response analysis of displacement and manipulated signal display. It uses the penalty weighting for setpoint tracking and for changes in manipulated variables, and restricts the amplitude of output signal, forcing it to decrease rapidly. The robustness of the MPC algorithm was verified by varying structural damping, the coefficients of varying prediction horizon and the response analysis of different target parameters, and the comparison of the results of linear quadratic control.
引文
[1] 刘廷瑞,于子晴.风力机叶片失速非线性颤振伺服气弹智能控制[J].中南大学学报,2016,47(10):3562-3569.LIU Tingrui,YU Ziqing.Aeroservoelastic intelligent control for stall nonlinear flutter of wind turbine blade[J].Journal of Central South University,2016,47(10):3562-3569.
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[10] ACHIN J,GEORG S,LORENZO F,et al.On the design and tuning of linear model predictive control for wind turbines[J].Renewable Energy,2015,80:664-673.
[11] DONGRAN S,JIAN Y,MI D,et al.Model predictive control with finite control set for variable-speed wind turbines[J].Energy,2017,126:564-572.
[12] 张靖,李博文,余珮嘉,等.基于状态空间的双馈风力发电机模型预测控制[J].电网技术,2017,41(9):2904-2909.ZHANG Jing,LI Bowen,YU Peijia,et al.Model prediction control based on state space for doubly-fed induction generator[J].Power System Technology,2017,41(9):2904-2909.
[13] 顾怡红.风力发电机叶片优化设计方法研究[D].杭州:浙江大学,2014.
[14] Mathworks.Adaptive MPC Design[EB/OL].http://cn.mathworks.com/help/mpc/adaptive-mpc-design.html?s_tid=gn_loc_drop.2017/11/18.
[15] LIU Tingrui,LIU Guifang.Vibration control of rotating piezo-composite blade beam with CUS configuration based on optimal LQG controller[J].Journal of Vibroengineering,2018,20(1):427-447.
[2] BARAN R P.Aeroelastic analysis and classical flutter of a wind turbine using BLADE MODE V.2.0 and PHATAS in FOCUS 6[D].Delft:Delft University of Technology,2013.
[3] CHAVIAROPOULOS P K,SRENSEN N N,HANSEN M O L.Viscous and aeroelastic effects on wind turbine blades.The VISCEL project.Part II:aeroelastic stability investigations[J].Wind Energy,2003,6:387-403.
[4] KALLES?E B S.A low-order model for analysing effects of blade fatigue load control[J].Wind Energy,2006(9):421-436.
[5] SAYED M A,LUTZ T,KR?MER E,et al.Aero-elastic analysis and classical flutter of a multi-megawatt slender bladed horizontal-axis wind turbine.Progress in Renewable Energies Offshore[M].London:Taylor and Francis,London,2016.
[6] SONG O,LIBRESCU L,OH S Y.Vibration of pretwisted adaptive rotating blades modeled as anisotropic thin-walled beams[J].AIAA Journal,2001,39(2):285-295.
[7] 刘廷瑞.风力机叶片动力失速气弹稳定性分析及颤振抑制[M].里加:金琅学术出版社,2017.
[8] CHAVIAROPOULOS P K.Flap/lead±lag aeroelastic stability of wind turbine blade sections[J].Wind Energy,1999(2):99-112.
[9] 常林,刘廷瑞.大型水平轴风力机叶片气弹稳定性研究及控制[J].机械设计与研究,2018(2):199-204.CHANG Lin,LIU Tingrui.Research and control of blade aeroelastic stability of large horizontal axis wind turbine[J].Journal of Machine Design and Research,2018(2):199-204.
[10] ACHIN J,GEORG S,LORENZO F,et al.On the design and tuning of linear model predictive control for wind turbines[J].Renewable Energy,2015,80:664-673.
[11] DONGRAN S,JIAN Y,MI D,et al.Model predictive control with finite control set for variable-speed wind turbines[J].Energy,2017,126:564-572.
[12] 张靖,李博文,余珮嘉,等.基于状态空间的双馈风力发电机模型预测控制[J].电网技术,2017,41(9):2904-2909.ZHANG Jing,LI Bowen,YU Peijia,et al.Model prediction control based on state space for doubly-fed induction generator[J].Power System Technology,2017,41(9):2904-2909.
[13] 顾怡红.风力发电机叶片优化设计方法研究[D].杭州:浙江大学,2014.
[14] Mathworks.Adaptive MPC Design[EB/OL].http://cn.mathworks.com/help/mpc/adaptive-mpc-design.html?s_tid=gn_loc_drop.2017/11/18.
[15] LIU Tingrui,LIU Guifang.Vibration control of rotating piezo-composite blade beam with CUS configuration based on optimal LQG controller[J].Journal of Vibroengineering,2018,20(1):427-447.