基于正交特性的机电伺服非线性机械参数辨识OA

Uncertainty and variation of mechanical parameters cause the mismatch of control settings in mechatronics servo systems,therefore the dynamic performance and the accuracy cannot be guaranteed continuously.A rapid parameter identification method for moment of inertia,nonlinear friction and bias load is proposed in this paper.It circumvents the introduction of noise in inertial estimation and improves the identification accuracy by exploiting the phasic and kinematic orthogonal properties of a sinusoidal reference to decouple the identifications of inertia and friction.The utilization of separable least square method relieves the computational burden for optimization solution by separating the procedures for optimizing the nonlinear and linear parameters of the friction model.The proposed method could be generalized to identifications of similar mechanical systems.The feasibility and the accuracy of the identification method are verified with a hardware-in-loop simulation respectively,and the application of incremental algorithm of the proposed method in self-tuning and feedforward compensation of speed PI control is studied experimentally.