Resonance Suppression Of Servo System Based On Random Disturbance Of Resonance Point

In the field of modern industry,servo system is widely used as the core component of production and processing.The servo system is mainly composed of speed loop,current loop and two-mass system,which is connected by motor,load and transmission device between them.However,since these drives are not all ideal rigid structures,elastic coupling between mechanical load and rotary motor drive is mostly used at present.The elastic coupling mechanical structure contains the inherent resonance frequency.When the system executes the high dynamic action command,it may produce obvious mechanical vibration,which will reduce the positioning accuracy and response speed of the servo system.The long-term mechanical vibration will lead to excessive torque of the transmission parts and damage,reduce the service life of the equipment,and even directly scrap the equipment.Therefore,it is very important to effectively suppress the mechanical resonance.Aiming at the problem of resonance suppression of servo system under random disturbance of resonance point,the following research is carried out in this paper:The second chapter establishes the mathematical model of the two-mass system,analyzes the resonance mechanism,and expounds the causes of mechanical resonance,so as to lay a foundation for follow-up research.In Chapter 3,recursive least square method is used to identify parameters based on Gauss process.Firstly,the Gauss-Markov model of the motor is established,and the principle and parameter identification algorithm of least square method and recursive least square method are described.Then,the unbiased estimator of variance is solved by using the sum of deviation squares.Finally,parameter identification is carried out,and the identification results show that the method is simple and feasible.Compared with the traditional parameter identification method,this method can realize the online parameter identification in one step,and the identification speed is2-10 times faster than the traditional method.It can not only ensure the real-time online identification of parameters,make up for the low efficiency of offline identification and poor real-time performance,but also improve the accuracy of the model,and can quickly and accurately identify the system parameters.In chapter 4,the simulated annealing algorithm is used to suppress the drift resonance points.Firstly,the trisection method is used to search the drift resonance points online.Then,the principle of notch filter is analyzed and simulated annealing algorithm is used to determine the optimal width and depth parameters of notch filter.Finally,on the basis of determining the optimal parameters,experiments and system robustness analysis are carried out.Experimental results show that this method can not only quickly search for drift resonance points,effectively suppress resonance,and maintain the stability of the system,but also avoid the defect of time-consuming manual adjustment parameters,can accurately and quickly suppress drift resonance points.In chapter 5,resonance suppression of random disturbed resonant points is carried out based on the principle of control chart.Firstly,a method to determine the control limit is proposed for the resonance points with random disturbance based on the principle of control chart.Then,the simulated annealing algorithm is used to determine the optimal parameters of notch filter,which can not only suppress the resonance effectively,but also minimize the phase angle loss and prevent excessive suppression.Finally,simulation and experiment verify the feasibility and effectiveness of the proposed method.Compared with manual adjustment of parameters,this method is less time-consuming and can suppress the resonance points of random disturbance accurately and quickly.