【摘要】：交流伺服系統(tǒng)因控制精度高,性能好在工業(yè)生產(chǎn)中得到了普遍的應(yīng)用,然而隨著工業(yè)自動(dòng)化的快速發(fā)展,人們對(duì)交流伺服系統(tǒng)控制性能的要求也在不斷提高。PID控制器依舊是交流伺服系統(tǒng)普遍采用的控制方式,雖然其結(jié)構(gòu)簡(jiǎn)單,易于實(shí)現(xiàn),但在系統(tǒng)參數(shù)變化以及外部干擾存在時(shí)其魯棒性不夠理想。近年來(lái),由于分?jǐn)?shù)階微積分理論的快速發(fā)展,分?jǐn)?shù)階控制器得到了廣泛的研究,它表現(xiàn)出了比傳統(tǒng)PID控制器更為優(yōu)越的性能。本文以提高交流伺服系統(tǒng)控制性能為目標(biāo),研究分?jǐn)?shù)階控制器在交流伺服系統(tǒng)中的應(yīng)用。首先,本文介紹了分?jǐn)?shù)階控制理論和永磁同步電機(jī)的數(shù)學(xué)模型,探討了永磁同步電機(jī)交流伺服系統(tǒng)的矢量控制原理,分析了伺服系統(tǒng)的電流環(huán)PI控制器、速度環(huán)PI控制器和分?jǐn)?shù)階PIλ控制器的設(shè)計(jì)方法,研究了空間矢量脈寬調(diào)制技術(shù),并在此基礎(chǔ)上搭建了永磁同步電機(jī)交流伺服系統(tǒng)的仿真模型。通過(guò)對(duì)分別使用整數(shù)階PI控制器和分?jǐn)?shù)階PIλ控制器的伺服系統(tǒng)進(jìn)行仿真實(shí)驗(yàn),得到的結(jié)果表明分?jǐn)?shù)階PIλ控制器可以有效地提高伺服系統(tǒng)的抗干擾能力。其次,針對(duì)伺服系統(tǒng)的分?jǐn)?shù)階PIλ控制器參數(shù)較多,整定困難,設(shè)計(jì)了一種基于差分進(jìn)化算法的控制器參數(shù)優(yōu)化方法。由于標(biāo)準(zhǔn)的差分進(jìn)化算法存在著不足,通過(guò)改變初始進(jìn)化群體的選取方式,為變異因子和交叉概率設(shè)計(jì)動(dòng)態(tài)的調(diào)節(jié)策略來(lái)改進(jìn)算法,并利用測(cè)試函數(shù)驗(yàn)證了算法改進(jìn)的正確性。之后,將改進(jìn)的算法運(yùn)用于交流伺服系統(tǒng)分?jǐn)?shù)階PIλ控制器的參數(shù)尋優(yōu)上,仿真實(shí)驗(yàn)表明,改進(jìn)的算法能夠快速的搜索到伺服系統(tǒng)理想的控制器參數(shù)值,實(shí)現(xiàn)控制器參數(shù)的離線整定。最后,為交流伺服系統(tǒng)設(shè)計(jì)了一種基于RBF神經(jīng)網(wǎng)絡(luò)的分?jǐn)?shù)階PIλ控制器,該控制器用RBF神經(jīng)網(wǎng)絡(luò)辨識(shí)被控對(duì)象的Jacobain信息來(lái)自適應(yīng)的整定分?jǐn)?shù)階PIλ控制器的參數(shù),既利用模型的信息避免了人工整定的不確定性,又兼?zhèn)淞朔謹(jǐn)?shù)階PIλ控制器的靈活性和魯棒性。仿真實(shí)驗(yàn)的結(jié)果表明本文提出的RBF神經(jīng)網(wǎng)絡(luò)分?jǐn)?shù)階PIλ控制器能夠很好的改善伺服系統(tǒng)的控制性能。
[Abstract]:Ac servo system has been widely used in industrial production because of its high control precision and good performance. However, with the rapid development of industrial automation, The requirements of AC servo system control performance are also continuously improved. Pid controller is still widely used in AC servo system, although its structure is simple and easy to realize. However, the robustness of the system is not ideal when the system parameters change and the external disturbances exist. In recent years, due to the rapid development of fractional calculus theory, fractional order controller has been widely studied, and it shows better performance than traditional PID controller. In order to improve the control performance of AC servo system, the application of fractional controller in AC servo system is studied in this paper. Firstly, the fractional order control theory and the mathematical model of PMSM are introduced, the vector control principle of PMSM AC servo system is discussed, and the current loop Pi controller of PMSM is analyzed. The speed loop Pi controller and fractional order Pi 位 controller are designed, and the space vector pulse width modulation (SVPWM) technology is studied. Based on this, the simulation model of PMSM AC servo system is built. The simulation results of the servo system using integer Pi controller and fractional Pi 位 controller show that the fractional Pi 位 controller can effectively improve the anti-interference ability of the servo system. Secondly, a parameter optimization method based on differential evolution algorithm is designed for the fractional Pi 位 controller of servo system, which has many parameters and is difficult to adjust. Due to the shortcomings of the standard differential evolution algorithm, the algorithm is improved by changing the selection method of the initial evolutionary population and designing dynamic adjustment strategies for the mutation factor and the crossover probability, and the correctness of the improved algorithm is verified by using the test function. Then, the improved algorithm is applied to the parameter optimization of the fractional Pi 位 controller of AC servo system. The simulation results show that the improved algorithm can quickly search the ideal controller parameters of the servo system. The off-line tuning of controller parameters is realized. Finally, a fractional-order Pi 位 controller based on RBF neural network is designed for AC servo system. The controller uses RBF neural network to identify the parameters of the controlled object's Jacobain information from the adaptive tuning fractional Pi 位 controller. Not only the uncertainty of manual tuning is avoided by using the information of the model, but also the flexibility and robustness of fractional Pi 位 controller are presented. The simulation results show that the RBF neural network fractional Pi 位 controller can improve the control performance of servo system.
【學(xué)位授予單位】：江蘇科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TM921.541

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