Indirect Self-tuning PID Vibration Control Of Wind Turbine Blade Based On Advanced Identification Algorithm

With the rapid growth of fan capacity,in order to improve the efficiency of wind power generation,the design of wind turbine blades gradually tend to lighter weight and larger size.However,the increase of blade size will lead to the increase of blade flutter,which not only greatly reduces the efficiency of wind power generation,but also seriously affects the safe operation of blades.Intelligent blade is one of the main directions of the development of modern turbine blade.Intelligent blade design based on intelligent driver has important significance for reducing the vibration fatigue loss,improving the utilization of wind energy and reducing the cost of wind power generation.The vibration of the blade mainly includes two types:classic flutter and stall vibration.The former is mainly in the case of leaves in the attached flow,caused by fluid-solid coupling vibration of the blade;the latter is mainly in the case of aerodynamic stall caused by vibration.In this paper,the classical chatter control of the blade is studied,and the effect of suppressing the flutter is achieved by combining the intelligent driver and the control algorithm.In practical engineering,due to complex operating environment,the parameters of the blade system will be affected by a variety of uncertain factors,so the study of system parameter perturbation is of great significance.In this paper,an intelligent airfoil servo-based servo blade model is established.First,a direct self-tuning PID controller based on pole placement is designed without consideration of system time-varying.Secondly,the system parameters are considered in the real load operating environment.An indirect self-tuning PID controller is designed based on least-square recursive least squares for forgetting factor optimization based on differential evolutionary optimization.The parameter estimator with excellent performance can improve the control quality of the intelligent blade vibration controller.The forgetting factor recursive least squares method is used to estimate the system model parameters,while the different values of the forgetting factor will affect the accuracy of the parameter estimator.Based on the traditional recursive least squares algorithm based on the forgetting factor,the differential evolution algorithm is used to optimize the forgetting factor,and then the parameters are estimated to obtain the best identification parameter,and then the indirect self-tuning PID vibration control is implemented.The simulation results show that the Intelligent Leaf Indirect Self-Tuning PID control based on the forgetting factor recursive least squares method can identify the perturbed blade system parameters on line and make the blade vibration control adaptive.Based on differential evolution optimization The indirect self-tuning PID control effect of identification is more robust and adaptive,which can achieve better control effect.