【摘要】：永磁同步電機具有動態(tài)響應快、穩(wěn)態(tài)精度高、調(diào)速范圍寬等優(yōu)點,在高精度伺服控制領域得到了廣泛的應用。伺服系統(tǒng)電流內(nèi)環(huán)的控制效果對電機的動穩(wěn)態(tài)性能影響較大,傳統(tǒng)的電流環(huán)控制策略難以滿足人們對電機控制性能的要求。因此,新的控制策略如預測控制等被用于電機電流環(huán)的控制中。本文首先對表貼式永磁同步電機的數(shù)學模型進行簡化,推導出其在三相靜止坐標系下的數(shù)學模型,基于磁勢守恒原則推導其CLARK和PARK變換矩陣,從而得到三相永磁同步電機在d、q軸下的數(shù)學模型,實現(xiàn)電機勵磁分量和轉(zhuǎn)矩分量的解耦。通過一階泰勒公式對其數(shù)學模型離散化,得到電機的預測控制模型。其次,對無差拍電流預測控制原理和控制性能進行了研究,由于預測控制的性能依賴于電機參數(shù)的準確性,本文對電機參數(shù)偏差和預測控制動穩(wěn)態(tài)性能的關系進行了理論分析,當預測模型電感與電機實際電感相差較大時,控制系統(tǒng)發(fā)散。為了增強控制系統(tǒng)對電感參數(shù)的魯棒性,采用一種魯棒電流預測控制算法,通過改變權重系數(shù)的大小來調(diào)節(jié)控制系統(tǒng)的穩(wěn)定范圍。但是權重系數(shù)的減小會降低控制系統(tǒng)的帶寬,導致電流的動態(tài)響應變慢,因此,為了最大程度的提高預測控制的性能,需要結合這兩種算法的優(yōu)點,取長補短。然后,為了消除電機參數(shù)偏差導致的電流穩(wěn)態(tài)誤差,采用模型參考自適應的方法對電機的電感和磁鏈進行在線辨識,用電機參數(shù)的辨識值去實時的修正預測模型參數(shù)。同時,基于電感參數(shù)的在線辨識提出了一種在線切換策略,在電感偏差較大時使用魯棒控制算法提高控制系統(tǒng)的穩(wěn)定性,而當電感參數(shù)收斂到真實值時,再切換回傳統(tǒng)無差拍電流預測控制,使得控制系統(tǒng)穩(wěn)定性提高的同時維持其良好的動態(tài)響應。最后,基于TMS320F28335芯片設計了永磁同步電機驅(qū)動系統(tǒng),通過實驗進一步研究了無差拍電流預測控制性能和電機參數(shù)的關系,驗證了魯棒預測控制算法、模型參考自適應參數(shù)辨識算法以及預測控制算法在線切換策略的正確性和有效性。
[Abstract]:Permanent magnet synchronous motor (PMSM) has many advantages, such as fast dynamic response, high steady-state precision and wide speed range, so it has been widely used in the field of high-precision servo control. The control effect of the current inner loop of servo system has a great influence on the dynamic and steady performance of the motor. The traditional current loop control strategy is difficult to meet the requirements of the motor control performance. Therefore, new control strategies such as predictive control are used in motor current loop control. In this paper, the mathematical model of permanent magnet synchronous motor (PMSM) is simplified, and its mathematical model in three-phase stationary coordinate system is deduced. Based on the principle of conservation of magnetic potential, the CLARK and PARK transformation matrices are derived. The mathematical model of the three-phase permanent magnet synchronous motor under dq-axis is obtained, which can decouple the excitation and torque components of the motor. The mathematical model is discretized by the first order Taylor formula and the predictive control model of the motor is obtained. Secondly, the principle and control performance of predictive control are studied. Because the performance of predictive control depends on the accuracy of motor parameters, the relationship between the error of motor parameters and the dynamic and steady performance of predictive control is analyzed theoretically in this paper. The control system diverges when the difference between the predictive model inductance and the actual inductance of the motor is large. In order to enhance the robustness of the control system to the inductance parameters, a robust current predictive control algorithm is used to adjust the stable range of the control system by changing the weight coefficient. However, the decrease of the weight coefficient will reduce the bandwidth of the control system and slow down the dynamic response of the current. Therefore, in order to maximize the performance of predictive control, it is necessary to combine the advantages of the two algorithms to complement each other. Then, in order to eliminate the current steady-state error caused by the parameter deviation of the motor, the inductance and flux chain of the motor are identified online by the model reference adaptive method, and the model parameters are corrected in real time by the identification value of the motor parameters. At the same time, an on-line switching strategy based on inductance parameter identification is proposed. The robust control algorithm is used to improve the stability of the control system when the inductance deviation is large, but when the inductance parameter converges to the real value, the robust control algorithm is used to improve the stability of the control system. Then switching back to the traditional deadbeat current predictive control, the stability of the control system is improved while maintaining its good dynamic response. Finally, a permanent magnet synchronous motor drive system based on TMS320F28335 chip is designed. The relationship between the performance of beat free predictive control and motor parameters is further studied through experiments, and the robust predictive control algorithm is verified. Model reference adaptive parameter identification algorithm and predictive control algorithm are correct and effective.
【學位授予單位】：哈爾濱工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TM341

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本文編號：2199199