本文關鍵詞： 自抗擾控制器 轉動慣量辨識 負載轉矩觀測 辨識補償 轉速估計　出處：《西南交通大學》2017年碩士論文　論文類型：學位論文

【摘要】：永磁同步電機具有高功率密度,體積小,散熱好等一系列優(yōu)點。目前,永磁同步電機已在高精度、高速伺服領域扮演重要的角色。永磁同步電機得到廣泛應用的同時也對電機控制性能提出更高的要求,尤其對控制系統(tǒng)的抗擾性能提出更大的挑戰(zhàn)。為抑制負載變化給電機輸出轉速帶來的影響,本文對基于自抗擾控制技術的永磁同步電機控制策略進行研究,采用了一種Gopinath觀測器補償自抗擾控制器的方案。對轉速環(huán)和電流環(huán)采用自抗擾控制器的永磁同步電機矢量控制系統(tǒng)進行分析,電機控制問題中自抗擾控制技術相對于傳統(tǒng)PI控制具有更好的動態(tài)響應性能和對內外擾動抑制效果。本文對于自抗擾控制器參數(shù)整定問題:對線性結構自抗擾控制器的控制參數(shù)整定,通過推導其系統(tǒng)閉環(huán)特征方程完成。對非線性結構自抗擾控制器的控制參數(shù)整定,采用免疫粒子群算法完成。為減輕擴張狀態(tài)觀測器負擔,進一步提高控制系統(tǒng)抗擾性能,本文對傳統(tǒng)自抗擾控制器進行辨識補償,辨識補償?shù)奈锢砹堪ㄓ来磐诫姍C的轉動慣量和負載轉矩。轉動慣量辨識方面,分析對比了三種在線辨識方法:帶遺忘因子的最小二乘法、基于波波夫超穩(wěn)定性的模型參考自適應、基于郎道離散迭代的模型參考自適應算法。通過選擇合理的增益可以準確地在線辨識轉動慣量。負載轉矩觀測方面,常用的在線觀測方法采用降階觀測器算法對狀態(tài)量進行重構,本文根據(jù)所采用的方案特點,采用Gopinath觀測器對負載轉矩進行觀測,通過穩(wěn)定性分析選擇合理控制參數(shù)可以準確對負載轉矩進行觀測。對于不適合安裝轉速編碼器的特殊場合,本文采用模型參考自適應算法實現(xiàn)基于自抗擾控制技術的永磁同步電機無速度傳感器控制,使用的無速度傳感器控制算法結構簡單易實現(xiàn),系統(tǒng)性能可滿足基本要求。實驗部分采用PESX-Ⅱ電力電子與電力傳動實驗平臺,以TMS320F2812為控制核心。對采用PI控制、自抗擾控制、辨識補償自抗擾控制的永磁同步電機控制方案進行驗證,通過分析對比實驗結果與仿真結果來驗證采用辨識補償自抗擾控制方案的有效性和優(yōu)越性,方案可應用于實際控制中。
[Abstract]:Permanent magnet synchronous motor (PMSM) has a series of advantages such as high power density, small size, good heat dissipation and so on. The field of high speed servo plays an important role. The permanent magnet synchronous motor (PMSM) has been widely used, and the control performance of PMSM is also required to be higher. In order to restrain the influence of load variation on motor output speed, the control strategy of PMSM based on ADRC is studied in this paper. A scheme of Gopinath observer compensation ADRC is adopted. The vector control system of permanent magnet synchronous motor (PMSM) with active disturbance rejection controller in speed loop and current loop is analyzed. The ADRC technique in motor control problem has better dynamic response performance compared with the traditional Pi control, and it can restrain the internal and external disturbance. In this paper, the parameter tuning problem of the ADRC controller and the linear structure ADRC control are discussed. The control parameters of the machine are set, By deducing the closed-loop characteristic equation of the system, the immune particle swarm optimization algorithm is used to adjust the control parameters of the nonlinear structure ADRC. In order to reduce the burden of the extended state observer, the disturbance rejection performance of the control system is further improved. In this paper, the traditional ADRC is identified and compensated. The physical parameters of identification compensation include moment of inertia of permanent magnet synchronous motor, load torque and moment of inertia identification. Three online identification methods are analyzed and compared: least square method with forgetting factor and model reference adaptation based on Popov hyperstability. A model reference adaptive algorithm based on Lang Dao discrete iteration is proposed. The moment of inertia can be accurately identified online by selecting a reasonable gain. The commonly used on-line observation method uses the reduced order observer algorithm to reconstruct the state quantity. According to the characteristic of the scheme, this paper uses the Gopinath observer to observe the load torque. The load torque can be accurately observed by selecting reasonable control parameters through stability analysis. In this paper, the speed sensorless control of PMSM based on ADRC is realized by using model reference adaptive algorithm. The speed sensorless control algorithm used in PMSM is simple and easy to realize. The performance of the system can meet the basic requirements. In the experiment part, PESX- 鈪，

本文編號：1505162