摘要
Abstract
Accurate load torque identification helps to improve the load disturbance resistance of complex nonlinear loaded permanent magnet drive systems.The sliding mode observer(SMO)has become a commonly used algorithm for load torque identification due to its advantages of high robustness to noise,fast response speed,and simple structure.However,the shortcomings of this algorithm,such as high-frequency chattering and slow response speed,limit its application in electric drive systems.This paper proposes a new adaptive sliding-mode load torque observer to solve the problem of the inherent contradiction between the convergence speed and high-frequency chattering of conventional sliding-mode observers.
Firstly,from the perspective of quasi-sliding mode,the conventional sign function is replaced by the saturation function to suppress the high-frequency chattering of the load torque estimate.The sign function can effectively suppress the chattering phenomenon of SMO,but it still fails to balance the convergence speed and observation accuracy.Second,an adaptive convergence rate is designed to introduce an exponential convergence term based on the conventional isochronous convergence rate.The adaptive gain of the isochronous convergence term is designed to make the sliding-mode observer adaptively adjust the convergence speed along with the change of the system state.Thus,the observer has a short convergence time and strong robustness,and the high-frequency chattering phenomenon of the sliding-mode observer in the steady state is suppressed.Finally,this paper introduces the average estimated value of the load torque in the conventional slip mode identification algorithm and adds it to the feedback loop of the speed observer.The improved load torque observation algorithm can suppress the chattering of the estimated torque by adjusting the feedback gain g.Since the load torque indication signal U can characterize the load torque change without additional delay,it can be directly involved in the speed estimation.Therefore,the proposed algorithm has a fast response speed during transient processes while considering the chattering suppression of the system.Based on the principle of sliding mode variable structure control,the adaptive rate of feedback gain coefficient g is designed.
Simulation and experimental results show that under varying speed and load disturbances,the proposed adaptive SMO has less chattering than traditional SMO and super-twisting SMO.Additionally,the adaptive SMO converges faster than traditional SMO and performs comparably to super-twisting SMO.In load disturbance experiments at a reference speed of 600 r/min,the speed fluctuations for no torque feedforward,traditional SMO with torque feedforward,and adaptive SMO with torque feedforward are 72.5 r/min,56 r/min,and 35.5 r/min,respectively,with system recovery times of 0.7 s,0.65 s,and 0.5 s.To further verify the impact of inertia parameter mismatch on the adaptive SMO,inertia was set to 2,5,0.5,and 0.2 times the rated value,with the maximum deviation in load torque observation being 6.7 N·m.The results indicate that the impact of parameter mismatch is not significant.
The following conclusions can be drawn.(1)The designed adaptive SMO has a simple structure and high stability,is easy to implement,observes the load torque quickly and accurately,and requires fewer parameters.(2)Compared with the conventional SMO,the proposed adaptive SMO has less chattering and faster response speed during the transient change of the load torque.(3)The proposed adaptive SMO is more suitable for the scenario of variable load torque than the conventional SMO.The experimental results show that when the load torque recognized by the adaptive SMO is used as the feedforward term of the reference torque,the response speed and load disturbance resistance of the heavy-duty chain drive system can be effectively improved.关键词
负载转矩/滑模观测器/永磁同步电机/前馈补偿/抗负载扰动Key words
Load torque/sliding mode observer/permanent magnet synchronous motor(PMSM)/feed-forward compensation/anti-load disturbance分类
动力与电气工程
