基于改进的遗传-PID算法的机组轴承油雾排放控制策略
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摘要
发电机组轴承在运行过程中会出现"甩油"和油雾溢出现象,该现象会带来许多安全隐患。针对此问题提出了基于改进的遗传-PID算法的发电机轴承油雾排放策略。油雾排放控制的关键就是控制系统的平稳性,封闭式轴承内部气压大幅度的波动会造成其内部的油雾短时间内激增,给系统正常运行带来危险,基于改进的遗传-PID算法的控制策略可以满足控制系统的平稳性要求。该算法将目标函数作为控制器的评估值,通过改进之后的遗传算法的选择、交叉、变异、迭代等遗传操作获得PID控制器参数的最优解,以弥补传统PID算法在控制高阶复杂带有延时的线性系统时的不足,使控制器获得良好的控制性能,降低了系统的超调量,减少了系统的调节时间。
When the bearing of a generator set is in operation, the shedding of oil and overflowing of oil mist may occur,which can bring hidden trouble for the running of generator set. For this issue, the oil mist emission strategy based on improved genetic-PID algorithm of the generator's bearings is presented in this paper. The key of oil mist emission control is the stability of control system because large fluctuations of the pressure in the enclosed bearing will cause the inside oil mist to increase rapidly, which endangers normal operation of the system. The improved genetic-PID control algorithm proposed in this paper can meet the stability requirement of the control system. The algorithm proposed in this paper uses the objective function as the evaluation value of the controller, and obtains the optimal solution of the PID controller parameters through selection, crossover, mutation, and iteration of the improved genetic algorithm, which compensates for the inadequacy of traditional PID algorithms in controlling high order complex linear control systems with delay. This makes the controller obtain good control performance, reduces the overshoot of the system, and reduces the system's adjustment time.
When the bearing of a generator set is in operation, the shedding of oil and overflowing of oil mist may occur,which can bring hidden trouble for the running of generator set. For this issue, the oil mist emission strategy based on improved genetic-PID algorithm of the generator's bearings is presented in this paper. The key of oil mist emission control is the stability of control system because large fluctuations of the pressure in the enclosed bearing will cause the inside oil mist to increase rapidly, which endangers normal operation of the system. The improved genetic-PID control algorithm proposed in this paper can meet the stability requirement of the control system. The algorithm proposed in this paper uses the objective function as the evaluation value of the controller, and obtains the optimal solution of the PID controller parameters through selection, crossover, mutation, and iteration of the improved genetic algorithm, which compensates for the inadequacy of traditional PID algorithms in controlling high order complex linear control systems with delay. This makes the controller obtain good control performance, reduces the overshoot of the system, and reduces the system's adjustment time.
引文
[1]张德选,张晓刚.巨型水轮发电机推力轴承甩油处理[J].水电站机电技术,2016,39(1):68-71.
[2]王伟,孙文艳,范江艳,等.大型水轮发电机组油雾问题分析与处理[J].水电与新能源,2017,31(2):74-77.
[3]OZANA S,DOCEKAL T.PID controller design based on global optimization technique with additional constraints[J].Journal of electrical engineering,2016,67(3):160-168.
[4]JAMALUDIN J,RAHIM N A,HEW W P.Development of a self-tuning fuzzy logic controller for intelligent control of elevator systems[J].Engineering applications of artificial intelligence,2009,22(8):1167-1178.
[5]熊四昌,高玉科,钱冰,等.基于容积补偿的气体泄漏检测遗传PID控制研究[J].机电工程,2015,32(3):348-351.
[6]张倩,杨耀权.基于遗传算法的PID控制器参数优化方法研究[J].电力科学与工程,2011,27(11):53-57.
[7]尼文斌,董金刚,刘书伟,等.自适应遗传PID算法在风洞风速控制中的应用[J].实验流体力学,2015,29(5):84-89.
[8]陈永前,曹艳琼,于治明,等.基于遗传PID整定的单柱校正压装液压机控制[J].机械研究与应用,2016,29(3):202-204.
[9]张炳兰.改进遗传算法PID在电液伺服系统的应用[J].自动化仪表,2017,38(8):28-32.
[10]张志文,王沛元,安柏楠,等.基于遗传算法PID的风电机组变桨控制[J].电力电子技术,2017,51(7):37-39,85.
[11]刘金琨.先进PID控制MATLAB仿真[M].4版.北京:电子工业出版社,2016:129-133.
[12]HARRAG A,MESSALTI S.Variable step size modified P&O MPPT algorithm using GA-based hybrid offline/online PID controller[J].Renewable and sustainable energy reviews,2015,49:1247-1260.
[2]王伟,孙文艳,范江艳,等.大型水轮发电机组油雾问题分析与处理[J].水电与新能源,2017,31(2):74-77.
[3]OZANA S,DOCEKAL T.PID controller design based on global optimization technique with additional constraints[J].Journal of electrical engineering,2016,67(3):160-168.
[4]JAMALUDIN J,RAHIM N A,HEW W P.Development of a self-tuning fuzzy logic controller for intelligent control of elevator systems[J].Engineering applications of artificial intelligence,2009,22(8):1167-1178.
[5]熊四昌,高玉科,钱冰,等.基于容积补偿的气体泄漏检测遗传PID控制研究[J].机电工程,2015,32(3):348-351.
[6]张倩,杨耀权.基于遗传算法的PID控制器参数优化方法研究[J].电力科学与工程,2011,27(11):53-57.
[7]尼文斌,董金刚,刘书伟,等.自适应遗传PID算法在风洞风速控制中的应用[J].实验流体力学,2015,29(5):84-89.
[8]陈永前,曹艳琼,于治明,等.基于遗传PID整定的单柱校正压装液压机控制[J].机械研究与应用,2016,29(3):202-204.
[9]张炳兰.改进遗传算法PID在电液伺服系统的应用[J].自动化仪表,2017,38(8):28-32.
[10]张志文,王沛元,安柏楠,等.基于遗传算法PID的风电机组变桨控制[J].电力电子技术,2017,51(7):37-39,85.
[11]刘金琨.先进PID控制MATLAB仿真[M].4版.北京:电子工业出版社,2016:129-133.
[12]HARRAG A,MESSALTI S.Variable step size modified P&O MPPT algorithm using GA-based hybrid offline/online PID controller[J].Renewable and sustainable energy reviews,2015,49:1247-1260.