李幸芳 趙世海
摘 要:以連續(xù)軋染機(jī)軋車(chē)部分織物張力控制為研究對(duì)象,針對(duì)其張力耦合等因素導(dǎo)致的張力控制難的問(wèn)題,建立了軋車(chē)部分張力系統(tǒng)的非線(xiàn)性耦合數(shù)學(xué)模型,并推導(dǎo)出靜態(tài)解耦模型。采用混沌粒子群優(yōu)化算法與自抗擾控制技術(shù)結(jié)合的方法,設(shè)計(jì)了相鄰軋車(chē)間的張力控制器,通過(guò)自抗擾算法主動(dòng)估計(jì)和補(bǔ)償張力系統(tǒng)動(dòng)態(tài)耦合部分,實(shí)現(xiàn)了系統(tǒng)的靜、動(dòng)態(tài)解耦;并采用混沌粒子群算法在線(xiàn)自整定自抗擾控制器中的主要參數(shù)。通過(guò)仿真實(shí)驗(yàn)與常規(guī)PID控制器對(duì)比發(fā)現(xiàn),混沌粒子群自抗擾控制器能使張力系統(tǒng)實(shí)現(xiàn)解耦控制及抑制內(nèi)外部干擾引起的張力波動(dòng),保證軋車(chē)恒張力穩(wěn)定運(yùn)行,提高系統(tǒng)的穩(wěn)定性和抗干擾性能。
關(guān)鍵詞:張力控制;解耦控制;抗干擾;自抗擾控制;混沌粒子群算法
中圖分類(lèi)號(hào):TS103.8 文獻(xiàn)標(biāo)志碼:A 文章編號(hào):1009-265X(2023)06-0207-09
現(xiàn)代連續(xù)軋染機(jī)運(yùn)行速度較高,在機(jī)器運(yùn)行過(guò)程中張力波動(dòng)危害巨大;張力過(guò)大產(chǎn)生經(jīng)伸緯縮現(xiàn)象、張力過(guò)小產(chǎn)生褶皺現(xiàn)象會(huì)造成織物染色不均,嚴(yán)重影響生產(chǎn)質(zhì)量[1]。同時(shí),連續(xù)軋染機(jī)是一種多單元聯(lián)合設(shè)備,相鄰輥間張力存在耦合性,速度波動(dòng)或張力波動(dòng)都會(huì)影響后一步工序的順利進(jìn)行,織物經(jīng)過(guò)染液槽后在適當(dāng)?shù)膲毫ο萝垑菏箍椢锞鶆蛉旧?,需保證織物在此過(guò)程中張力保持恒定,軋車(chē)軋輥的線(xiàn)速度是連續(xù)軋染機(jī)的基準(zhǔn)速度[2-3]。軋車(chē)部分張力系統(tǒng)具有非線(xiàn)性、時(shí)變性、強(qiáng)耦合性和強(qiáng)干擾性的特點(diǎn),設(shè)計(jì)一款能夠解耦控制并且具有良好抗干擾性能的張力控制器,對(duì)連續(xù)軋染機(jī)完成均勻軋染非常重要。
目前,印染工業(yè)領(lǐng)域應(yīng)用中常用比例-積分-微分(Proportion integration differentiation,PID)控制器實(shí)現(xiàn)張力控制,常規(guī)PID對(duì)于非線(xiàn)性、時(shí)變性的張力系統(tǒng)不能取得理想的控制效果[4]。該控制方法往往忽視了不同輥間的張力耦合性,難以滿(mǎn)足連續(xù)軋染機(jī)生產(chǎn)加工要求,在實(shí)際生產(chǎn)過(guò)程中織物張力會(huì)受到諸多因素影響,如機(jī)組構(gòu)件的制造和安裝誤差[5-6]以及外部環(huán)境溫度濕度的變化都會(huì)對(duì)織物張力的穩(wěn)定性造成干擾,張力控制系統(tǒng)難以達(dá)到理想控制效果。近年來(lái),一些現(xiàn)代控制方法被廣泛應(yīng)用在張力控制中。應(yīng)用魯棒控制方法和模糊自適應(yīng)PID[7-9]理論上可以解決張力控制難的問(wèn)題,但這些方法都依賴(lài)系統(tǒng)的精確模型,在實(shí)際應(yīng)用中不易實(shí)現(xiàn)。李琳等[10]針對(duì)滑??刂拼嬖诙墩竦膯?wèn)題,采用變速趨近律的方法設(shè)計(jì)了滑模變結(jié)構(gòu)控制器,解決張力控制系統(tǒng)中速度與張力耦合的問(wèn)題。Janabi-sharifi[11]在軋鋼張力控制中應(yīng)用模糊控制,但模糊規(guī)則需依賴(lài)經(jīng)驗(yàn)和專(zhuān)家知識(shí)確定,且模糊控制規(guī)則的數(shù)量隨系統(tǒng)階次的增加而增加。
本文將自抗擾控制(Active disturbance rejection control,ADRC)[12]應(yīng)用到連續(xù)軋染機(jī)軋車(chē)張力控制系統(tǒng)中,該算法無(wú)需確定被控系統(tǒng)的精確模型,通過(guò)將系統(tǒng)內(nèi)外部干擾主動(dòng)總和并對(duì)擾動(dòng)實(shí)時(shí)補(bǔ)償[13],解決軋車(chē)張力系統(tǒng)中的張力波動(dòng)問(wèn)題。針對(duì)該算法參數(shù)難整定的問(wèn)題,結(jié)合混沌粒子群優(yōu)化(Chaos particle swarm optimization,CPSO)算法[14]對(duì)自抗擾控制器中的眾多參數(shù)進(jìn)行在線(xiàn)自整定,根據(jù)軋車(chē)張力系統(tǒng)的數(shù)學(xué)模型設(shè)計(jì)了二階混沌粒子群自抗擾控制器[15]。將軋車(chē)部分張力系統(tǒng)中難以建模部分與干擾部分通過(guò)控制器估計(jì)補(bǔ)償,仿真實(shí)驗(yàn)表明該控制器能實(shí)現(xiàn)張力解耦控制且對(duì)張力波動(dòng)有良好的抑制效果。
1 張力系統(tǒng)建模分析
連續(xù)軋染機(jī)軋車(chē)部分共有3個(gè)軋車(chē),每個(gè)軋車(chē)由主動(dòng)輥和被動(dòng)輥組成,伺服電動(dòng)機(jī)驅(qū)動(dòng)各個(gè)主動(dòng)輥來(lái)控制軋車(chē)的速度。軋車(chē)張力系統(tǒng)示意如圖1所示,其中:Li(i= 3)為輥間織物長(zhǎng)度,近似等于各軋車(chē)間的距離;v0、F1分別為織物開(kāi)始速度與張力;F2、F3為各軋車(chē)間織物的張力;v3、F4為織物結(jié)束速度與張力;v1、v2為輥間織物速度;Mei(i= 3)為軋車(chē)電機(jī)的轉(zhuǎn)矩;Ri(i= 3)為各輥筒的半徑;ωi(i= 3)為各輥筒的角速度。
假定布料與輥筒之間的相互運(yùn)動(dòng)為純滾動(dòng),且織物只產(chǎn)生純彈性變形,依據(jù)織物質(zhì)量守恒定律、各輥間動(dòng)力學(xué)原理,連續(xù)軋染機(jī)軋車(chē)部分的張力系統(tǒng)數(shù)學(xué)模型為:
由式(2)可知,軋車(chē)張力系統(tǒng)具有耦合性,且每個(gè)車(chē)段都可以建立二階非線(xiàn)性微分方程,根據(jù)張力系統(tǒng)的階數(shù)選擇二階自抗擾控制器。將式(2)的方程解耦分析,得出狀態(tài)空間模型:
3 仿真分析
為驗(yàn)證混沌粒子群自抗擾控制器(CPSO-ADRC)在軋車(chē)張力系統(tǒng)中的解耦和抗干擾方面的控制性能,在MATLAB/Simulink中設(shè)置軋車(chē)張力數(shù)學(xué)模型和自抗擾控制器模型并編寫(xiě)混沌粒子群優(yōu)化算法程序驅(qū)動(dòng)仿真模型,經(jīng)過(guò)算法迭代更新得到5個(gè)參數(shù)的最優(yōu)解,并與常規(guī)PID控制器的控制效果進(jìn)行對(duì)比分析。軋車(chē)部分模型參數(shù)如表1所示,控制器參數(shù)如表2所示。
3.1 解耦性能仿真分析
由胡克定律可得在軋車(chē)過(guò)程中織物張力源于相鄰導(dǎo)輥間的速度差,根據(jù)軋車(chē)模型參數(shù)和相鄰導(dǎo)輥的轉(zhuǎn)速差,本文將織物張力設(shè)置為40 N。分析軋車(chē)張力數(shù)學(xué)模型得出相鄰軋車(chē)間張力存在耦合性的結(jié)論,即前車(chē)段的織物張力發(fā)生擾動(dòng)變化將影響后車(chē)段的織物張力,因此需要對(duì)其進(jìn)行解耦控制。在Simulink模型中將F2在4 s時(shí)階躍到45 N持續(xù)2 s后恢復(fù)至40 N,模擬張力在實(shí)際工作過(guò)程中發(fā)生的張力突變,比較不同控制器的控制效果。各車(chē)段解耦性能系統(tǒng)的仿真響應(yīng)曲線(xiàn)如圖3所示。
由圖3可知,當(dāng)F2張力變化時(shí),在PID控制下F3和F4在4 s和6 s都產(chǎn)生波動(dòng),而在混沌粒子群自抗擾控制器控制下F3和F4基本未發(fā)生波動(dòng),因此混沌粒子群自抗擾控制器有良好的解耦性能。
3.2 抗干擾性能仿真分析
3.2.1 抗彈性模量變化
在連續(xù)軋染機(jī)實(shí)際運(yùn)行工況中軋車(chē)前后會(huì)經(jīng)過(guò)染液槽和水洗槽,織物的溫度和濕度產(chǎn)生變動(dòng),致使織物自身彈性模量變化,而織物彈性模量是計(jì)算張力的重要參數(shù),這種織物組織內(nèi)部參數(shù)的變化會(huì)引起織物張力波動(dòng),增加了軋染機(jī)恒張力控制的難度。在上文設(shè)定的張力變化條件的基礎(chǔ)上將織物彈性模量減少15%,比較兩種控制器的控制效果。各車(chē)段彈性模量變化的系統(tǒng)仿真響應(yīng)曲線(xiàn)如圖4所示。
由圖4可知,當(dāng)織物彈性模量發(fā)生變化時(shí)PID控制下張力均出現(xiàn)2.3%的超調(diào)且到達(dá)穩(wěn)定時(shí)間增加,而在混沌粒子群自抗擾控制器控制下彈性模量的變化基本未引起張力變化,表明混沌粒子群自抗擾控制器有較好的抗參數(shù)變化性能。
3.2.2 抗速度擾動(dòng)
織物張力的大小與軋車(chē)的速度差有關(guān),軋車(chē)的運(yùn)行速度是由電機(jī)帶動(dòng)軋輥傳動(dòng)產(chǎn)生,連續(xù)軋染機(jī)運(yùn)行過(guò)程中速度擾動(dòng)是不可忽略的影響因素,當(dāng)織物的運(yùn)行速度發(fā)生波動(dòng)時(shí)將直接影響織物張力大小,對(duì)其進(jìn)行抗速度擾動(dòng)仿真實(shí)驗(yàn)。軋染張力系統(tǒng)運(yùn)行5 s時(shí)在軋輥ω1上疊加10 r/min、0.5 Hz的正弦信號(hào)作為速度擾動(dòng),速度波動(dòng)的系統(tǒng)仿真響應(yīng)曲線(xiàn)如圖5所示。
由圖5可知,在加入速度擾動(dòng)時(shí),PID控制下F2、F3和F4均有明顯波動(dòng),但混沌粒子群自抗擾控制器控制下張力無(wú)明顯波動(dòng),表明混沌粒子群自抗擾控制器有較好的抗速度擾動(dòng)性能。
3.2.3 抗噪聲擾動(dòng)
在連續(xù)軋染機(jī)實(shí)際工作過(guò)程中常受外部環(huán)境的噪聲、溫度、濕度等因素的影響而引起張力傳感器測(cè)量不穩(wěn)定,造成反饋信號(hào)波動(dòng)。將噪聲信號(hào)加入張力F2的反饋信號(hào)中,模擬生產(chǎn)過(guò)程中外部環(huán)境對(duì)張力傳感器檢測(cè)值的影響,觀察兩種控制器的控制性能,抗干擾性能系統(tǒng)仿真響應(yīng)曲線(xiàn)如圖6所示。
由圖6可知,當(dāng)F2受到白噪聲干擾時(shí),PID控制下F3和F4受到明顯擾動(dòng),但混沌粒子群自抗擾控制器控制下張力無(wú)明顯波動(dòng),表明混沌粒子群自抗擾控制器有良好的抵制外界干擾的性能。
4 結(jié) 語(yǔ)
本文針對(duì)連續(xù)軋染機(jī)軋車(chē)部分織物張力控制穩(wěn)定性的要求,根據(jù)張力系統(tǒng)強(qiáng)干擾、耦合性、時(shí)變性等特性,提出了一種混沌粒子群自抗擾張力控制器。通過(guò)與常規(guī)PID控制器的仿真對(duì)比實(shí)驗(yàn)表明,混沌粒子群自抗擾控制器能更好地實(shí)現(xiàn)張力動(dòng)態(tài)解耦控制,提升織物張力抗干擾能力,提高了軋車(chē)張力控制系統(tǒng)的魯棒性和控制精度。
本文提出的混沌粒子群自抗擾張力控制器具有良好的仿真性能,但實(shí)際控制策略的效果還需工程實(shí)踐的進(jìn)一步驗(yàn)證。實(shí)際工業(yè)生產(chǎn)過(guò)程中存在滑動(dòng)現(xiàn)象和織物塑性變形,同時(shí)工業(yè)控制中還可能出現(xiàn)控制指令延時(shí)現(xiàn)象,會(huì)影響控制策略的精度;而混沌粒子群自抗擾控制器能夠?qū)⒖烧{(diào)參數(shù)根據(jù)張力系統(tǒng)的實(shí)際運(yùn)行情況作出最優(yōu)解,自適應(yīng)調(diào)整織物張力。后期將進(jìn)行實(shí)驗(yàn)研究并根據(jù)實(shí)驗(yàn)結(jié)果修正調(diào)整本文提出的張力控制方法。
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Tension control of rolling and dyeing machines based on chaotic particle swarmand auto disturbance rejection control
LI Xingfang, ZHAO Shihai
Abstract: The continuous pad dyeing machine is a typical multi-unit joint equipment. According to its pad dyeing process, the continuous pad dyeing machine is divided into unwinding, pad dyeing, drying and winding units. The continuous pad dyeing machine needs to be controlled by constant tension during operation to ensure uniform dyeing of the fabric. If the fabric is subjected to excessive tension, it will produce warp and weft contraction and even fracture, which will affect the quality of pad dyeing. If the fabric tension is too small, it will produce wrinkles or fabric deviation, which seriously affects the economic benefits of enterprises. The pad dyeing unit is the most critical unit of the continuous pad dyeing machine, and its tension control effect will directly affect the printing and dyeing quality of the fabric. Therefore, it is crucial to ensure the constant tension of the fabric during the operation of the continuous pad dyeing machine. In this paper, the tension control system of the pad dyeing unit of the continuous pad dyeing machine was taken as the research object. In view of the difficulty of tension control such as tension coupling, the nonlinear coupling mathematical model of the tension system of the rolling mill was established, the static decoupling model was obtained, and the control algorithm was designed and verified by simulation experiments.
Firstly, according to the operation mechanism of pad dyeing unit and its structure diagram, the parameters such as moment of inertia inthe pad dyeing process were analyzed, and the dynamic model of the pad dyeing unit was established according to the law of mass conservation and Hooke's law. By observing the tension mathematical model of the pad dyeing unit, it is concluded that there are tension coupling and tension speed coupling between adjacent two rollers, and the system has nonlinear, time-varying, multi-interference and strong coupling characteristics. It is difficult to achieve the ideal control effect for the conventional PID controller of this kind of system. In this paper, the tension controller of adjacent rolling workshop was designed by using the combination of chaotic particle swarm optimization (CPSO) and active disturbance rejection control (ADRC). The dynamic coupling part of the tension system was estimated and compensated by the active disturbance rejection algorithm to realize the complete decoupling of the system, and the chaotic particle swarm optimization algorithm was used to adjust the main parameters of the active disturbance rejection controller online. The tension system of pad dyeing unit was simulated by MATLAB/Simulink, and the control effect of chaotic particle swarm auto disturbance rejection controller and conventional PID controller was observed. The experimental results show that the chaotic particle swarm active disturbance rejection controller is insensitive to the change of internal parameters and has good anti-interference. The control accuracy and stability are better than those of the conventional PID controller, and it can effectively suppress the tension fluctuation caused by coupling and interference. It is of great significance to improve the overall operation performance of the continuous pad dyeing machine.
Keywords: tension control; decoupling control; anti-interference; active disturbance rejection control; chaos particle swarm optimization algorithm
收稿日期:20230523 網(wǎng)絡(luò)出版日期:20230804
基金項(xiàng)目:天津市科技支撐重點(diǎn)計(jì)劃項(xiàng)目(15ZCDGX00840)
作者簡(jiǎn)介:李幸芳(1998—),女,遼寧本溪人,碩士研究生,主要從事機(jī)電一體化方面的研究。
通信作者:趙世海,E-mail:tjshzhao@163.com