本文選題：自抗擾控制 + 免疫遺傳算法��； 參考：《華北電力大學》2014年碩士論文

【摘要】：隨著我國電力工業(yè)的快速發(fā)展,熱工過程中被控對象維數(shù)越來越高、結(jié)構(gòu)越來越復雜,致使系統(tǒng)控制難度越來越大。為了提高系統(tǒng)性能,各類先進控制算法應運而生,如魯棒控制、預測控制、自適應控制及分散控制等,雖然這些算法都能改善系統(tǒng)的性能,但結(jié)構(gòu)比較復雜,計算量較大。自抗擾控制(ADRC)結(jié)構(gòu)簡單、易于設計、抗干擾能力強,自上世紀八十年代被提出以來,已經(jīng)取得了突破性的進展,迄今為止仍然是控制理論研究的中心問題之一。本文主要研究自抗擾控制器的優(yōu)化設計及應用研究,努力做到結(jié)構(gòu)優(yōu)化與參數(shù)優(yōu)化并重,改善系統(tǒng)的性能。 首先,在非線性自抗擾控制的基礎(chǔ)上,針對其參數(shù)多不易調(diào)節(jié)的缺點,本文將免疫理論中的非特異性免疫、特異性免疫與遺傳算法結(jié)合,形成了免疫遺傳算法。該算法不僅繼承了遺傳算法與免疫算法的優(yōu)點,還提高了算法的穩(wěn)定性、收斂精度和收斂速度。并通過變速恒頻風力發(fā)電系統(tǒng)自抗擾控制器參數(shù)優(yōu)化實例證明該算法的有效性,解決控制器參數(shù)優(yōu)化問題,提高風能利用效率。 其次,針對實際生產(chǎn)過程中多變量系統(tǒng)普遍存在耦合的特點,本文首先采用不變性原理設計多變量系統(tǒng)的動態(tài)解耦補償器；為了簡化控制模型,進一步對補償器模型進行簡化；其次在動態(tài)解耦的基礎(chǔ)上,引入自抗擾控制(ADRC),形成自抗擾解耦控制方案,利用ADRC的解耦功能,將變量間的耦合看作一種擾動進行實時估計和補償,實現(xiàn)進一步解耦；然后,以循環(huán)流化床系統(tǒng)為例,設計該系統(tǒng)解耦前、解耦后的Matlab仿真實驗,并與PID控制的仿真結(jié)果進行對比,驗證該方案的有效性。 最后,鑒于工業(yè)控制系統(tǒng)中普遍存在著遲延現(xiàn)象,本文充分利用Smith結(jié)構(gòu)對遲延的補償優(yōu)勢以及ADRC抗擾性強的優(yōu)點,將Smith結(jié)構(gòu)和ADRC相結(jié)合,形成既能補償遲延又能抑制擾動的史密斯-自抗擾控制(Smith-ADRC)方案。該方案結(jié)構(gòu)簡單,設計簡便,且具有很強的魯棒性和適應性。然后,以單變量的主汽溫系統(tǒng)、多變量的球磨機系統(tǒng)為例設計仿真實驗,并與Smith-PID、ADRC的優(yōu)化結(jié)果進行對比,驗證該方案的有效性。
[Abstract]:With the rapid development of electric power industry in our country, the dimension of the controlled object is getting higher and the structure is more and more complex in the process of thermal engineering, which makes the control of the system more and more difficult. In order to improve the performance of the system, various advanced control algorithms emerge as the times require, such as robust control, predictive control, adaptive control and decentralized control. Although these algorithms can improve the performance of the system, the structure is complex and the calculation is large. ADRC (active disturbance rejection Control) has a simple structure, easy design and strong anti-interference ability. Since it was proposed in the 1980s, it has made a breakthrough and is still one of the central problems in the control theory research up to now. In this paper, the optimal design and application of the ADRC are studied, and the structural optimization and parameter optimization are emphasized to improve the performance of the system. Firstly, on the basis of nonlinear ADRC, the immune genetic algorithm (IGA) is formed by combining the non-specific immunity, specific immunity and genetic algorithm in the immune theory, aiming at the disadvantage that the parameters are not easy to adjust. The algorithm not only inherits the advantages of genetic algorithm and immune algorithm, but also improves the stability, convergence accuracy and convergence speed of the algorithm. An example of parameter optimization of active disturbance rejection controller for variable speed constant frequency wind power generation system is given to prove the effectiveness of the algorithm, to solve the problem of controller parameter optimization and to improve the efficiency of wind energy utilization. Secondly, in order to simplify the control model, the dynamic decoupling compensator of multivariable system is designed based on invariance principle in order to simplify the control model. Secondly, on the basis of dynamic decoupling, the ADRC controller is introduced to form the ADRC control scheme. By using the decoupling function of ADRC, the coupling between variables is estimated and compensated as a disturbance in real time to realize further decoupling. Taking the circulating fluidized bed system as an example, the Matlab simulation experiment before and after decoupling is designed, and the simulation results of PID control are compared to verify the effectiveness of the scheme. Finally, in view of the widespread phenomenon of delay in industrial control system, this paper makes full use of the advantage of Smith structure to compensate delay and the advantage of strong ADRC immunity, and combines Smith structure with ADRC structure. A Smith-ADRC scheme, which can compensate delay and suppress disturbance, is formed. The structure of the scheme is simple, the design is simple, and it has strong robustness and adaptability. Then, the simulation experiment is designed with the single-variable main steam temperature system and the multi-variable ball mill system as an example, and compared with the optimized results of Smith-PIDN ADRC, the effectiveness of the scheme is verified.
【學位授予單位】：華北電力大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TM571

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