基于GLBest-PSO算法的CSTR系统鲁棒PID控制

连续搅拌反应釜(CSTR)系统是一类具有多变量、强非线性和多工作点的复杂工业过程,对外界扰动及内部参数变化较为敏感。针对常规PID控制器参数整定困难,难以取得满意效果,本文提出了一种基于改进粒子群优化算法的CSTR系统鲁棒PID控制方法。通过对优化目标的分析,将鲁棒PID控制器的参数整定问题转化成一个求解最大-最小问题,在对粒子群优化算法进行改进的基础上,引入合作进化思想对该最大-最小问题进行求解,获得了基于优化性能指标最优的鲁棒PID控制器参数。针对实例的仿真结果表明,利用此方法整定得到的鲁棒PID控制器具有良好的鲁棒性,性能指标优于其它方法得到的鲁棒PID控制器,当过程对象操作范围发生大的变化时,利用本文方法设计得到的鲁棒PID控制器能获得满意的结果。     

喷雾干燥过程分析及其PID控制仿真

本文研究背景源自实际喷雾干燥过程控制的工程项目。从对喷雾干燥过程的工艺流程、干燥机理的研究分析入手,讨论了喷雾干燥过程的控制思想、控制指标和要求,利用飞升曲线法拟合被控对象的数学模型,阐述了喷雾干燥过程PID控制算法的应用及系统仿真,通过ITSE最优整定法进行了参数整定。从实验仿真和实际运行的结果证明,所设计的控制系统能够满足干燥工艺和控制指标的要求,所采用的PID控制算法实现方便、控制效果较好,具有一定的稳定性和鲁棒稳定性。     

典型工业过程鲁棒PID控制器的整定

提出一阶迟延过程、积分迟延过程、不稳定迟延过程和二阶迟延过程等典型工业过程的鲁棒PID整定公式.本文从抗干扰性能和鲁棒性能两方面综合考虑,把鲁棒PID控制器的设计问题转化为求解一个带鲁棒性能约束的绝对误差积分指标(IAE)优化问题.鉴于该问题是非凸的,本文采用遗传算法来求解,并通过曲线拟合得到典型工业过程的PID控制器的整定公式.仿真结果表明本文的PID整定公式有效,且控制器具有良好的抗干扰能力和频域鲁棒性.     

一种时滞过程内模PID控制器鲁棒整定方法

针对典型的一阶时滞（FOPTD）、二阶时滞（SOPTD）以及一阶时滞积分（FODI）过程,提出了一种简便的内模PID控制器设计和参数整定方法。 用一阶泰勒级数逼近系统模型的时滞项,导出内模PID控制器参数表达式,且仅有一个可调参数β,该可调参数与系统的动态性能和鲁棒性直接相关。基于控制系统的鲁棒性能指标给出了控制器可调参数β进行鲁棒整定的解析表达式。仿真结果表明,该方法可使系统同时获得良好的设定值跟踪特性、扰动抑制特性和克服参数变化的鲁棒性。        

强时变时滞系统的鲁棒PID继电自整定控制技术

文章对于工业过程中常见的大时变时滞过程,提出了一种数字鲁棒PID控制器参数继电自整定控制策略和技术,应用这种整定方法整定的PID控制器,闭环不确定系统可具有大时变时滞鲁棒镇定性,且完全抑制负载干扰,具有很好的动静态性能,在造纸工业现场应用效果良好。     

导弹鲁棒分数阶PID自动驾驶仪设计

由于分数阶PID继承了传统PID的优点,并且具有更好的控制品质及更强的鲁棒性,因此针对导弹飞行过程中变参数、受环境干扰及快速稳定的特点,设计了鲁棒分数阶PID自动驾驶仪.基于最优Oustaloup数字算法建立框图式分数阶控制系统模型,结合IAE时域性能指标寻优及鲁棒性能量度,综合考虑时域性能及频域性能来整定分数阶PID...     

聚丙稀反应过程鲁棒PID自整定系统的研究

针对聚丙稀反应过程的温度控制,提出了一种简单而鲁棒性较强的鲁棒PID控制算法．即将模型输出上下界和统计的方法,分别应用到聚丙稀反应过程带有滞后环节对象的鲁棒辨识中,再利用Minmax算法对稳定的PID控制器参数进行整定。最后使用UML建立了鲁棒PID控制器参数自整定系统的模型,对其进行了分析、设计和实现。实践表明:该系统能有效地控制聚丙稀反应过程的温度。     

基于微粒群算法的PID控制器优化研究

研究PID控制器性能优化中,由于被控对象具有高阶、非线性等特点,而在工业生产过程中,传统的PID参数整定方法易出现超调和震荡问题,使系统响应特性差。为改善系统性能,提出一种改进粒子群算法的智能优化策略,将PID控制器参数作为粒子群中的粒子,以控制误差时间积分函数作为优化目标,进行PID控制参数的并行优化。利用MATLAB仿真软件进行仿真,并通过与传统整定方法(Z-N法)进行比较。结果表明,粒子群的PID参数整定法可提高控制器性能,并能够实现目标的最优整定,为PID控制器性能优化提供依据。     

一类工业过程的PID控制器整定方法

PID调节器具有结构简单、适应性强、不依赖于被控对象的精确模型、鲁棒性较强等优点。控制器的性能直接关系到生产过程的平稳高效运行以及产品的最终质量。针对一类可用带有纯时间延迟的一阶对象来近似描述的工业过程,本文通过对工业过程现场采集的数据,利用Levenberg-Marquardt最小二乘拟合法辨识出被控对象的数学模型,进而根据典型PID控制器的参数整定方法求出PID控制器的参数。通过对一个典型工业对象的仿真研究,结果表明所提出的方法简单有效。     

基于H∞回路成形的鲁棒PID参数整定

积分过程在工业过程控制中经常遇到,采用常规的PID参数整定方法很难得到理想的控制效果。本文采用基于H∞回路成形的鲁棒PID参数整定方法,实现对积分过程的有效控制。通过Simulink软件的仿真结果表明该方法的有效性。     

PID参数自整定算法及仿真

提出了一种简单有效的PID参数自整定算法,以最优准则ISTE为目标函数,模拟工程PID参数整定的策略和步骤,实现对PID参数的整定寻优.仿真结果表明该算法是有效的,适合于工程实际应用.     

Robust PID controller tuning based on the constrained particle swarm optimization

This paper proposes a novel tuning strategy for robust proportional-integral-derivative (PID) controllers based on the augmented Lagrangian particle swarm optimization (ALPSO). First, the problem of PID controller tuning satisfying multiple H_∞ performance criteria is considered, which is known to suffer from computational intractability and conservatism when any existing method is adopted. In order to give some remedy to such a design problem without using any complicated manipulations, the ALPSO based robust gain tuning scheme for PID controllers is introduced. It does not need any conservative assumption unlike the conventional methods, and often enables us to find the desired PID gains just by solving the constrained optimization problem in a straightforward way. However, it is difficult to guarantee its effectiveness in a theoretical way, because PSO is essentially a stochastic approach. Therefore, it is evaluated by several simulation examples, which demonstrate that the proposed approach works well to obtain PID controller parameters satisfying the multiple H_∞ performance criteria.     

一种PID参数整定的粒子群优化算法

提出了一种PID控制器参数整定的粒子群优化算法。该方法首先通过定义一个包含系统超调量、上升时间和稳态误差指标项的适应度函数,并根据系统的实际控制要求对各指标项适当加权。之后由带收缩因子的粒子群算法对PID进行多目标寻优,从而实现PID控制器的自动参数整定。仿真结果表明,该方法优化得到PID控制器的综合性能优于常规方法得到的PID控制器。     

Robust PID tuning for Smith predictor in the presence of model uncertainty

This paper presents robust PID tuning for the Smith predictor in the presence of model uncertainty. The concept of the equivalent gain plus time delay (EGPTD) is introduced to incorporate robust stability in PID tuning of the Smith predictor. In particular, an application is developed for the robust tuning of the first order plus time delay (FOPTD) system and the second order plus time delay (SOPTD) system because the systems have been used extensively to describe chemical processes. The proposed tuning method can cope with simultaneous uncertainties in all parameters of the model in an efficient manner. Another important and attractive feature of the method is that it can utilize many currently available PID tuning rules. Simulation results are provided to demonstrate the availability of the method.     

基于粒子群优化算法的PID控制器参数整定

PID控制器的性能完全依赖于其参数的整定和优化，但参数的整定及在线自适应调整对常规的PID控制器是难以解决的问题。根据粒子群算法具有对整个参数空间进行高效并行搜索的特点，提出了一种基于粒子群优化算法整定PID控制器参数的设计方法，并定义了一种新的性能指标函数来评价PID控制器的性能。现以二阶的船舶控制装置为研究对象，运用粒子群优化方法对PID控制器参数进行了寻优研究。仿真结果表明，该方法比一般PID参数整定方法具有更好的控制性能指标，有着一定的工程应用价值。     

PID auto-tuning using new model reduction method and explicit PID tuning rule for a fractional order plus time delay model

In this paper, a new model reduction method and an explicit PID tuning rule for the purpose of PID auto-tuning on the basis of a fractional order plus time delay model are proposed. The model reduction method directly fits the fractional order plus time delay model to frequency response data by solving a simple single-variable optimization problem. In addition, the optimal tuning parameters of the PID controller are obtained by solving the Integral of the Time weighted Absolute Error (ITAE) minimization problem and then, the proposed PID tuning rule in the form of an explicit formula is developed by fitting the parameters of the formula to the obtained optimal tuning parameters. The proposed tuning method provides almost the same performance as the optimal tuning parameters. Simulation study confirms that the auto-tuning strategy based on the proposed model reduction method and the PID tuning rule can successfully incorporate various types of process dynamics.     

Developments of fuzzy PID controllers

Abstract: This paper describes the development and tuning methods for a novel self-organizing fuzzy proportional integral derivative (PID) controller. Before applying fuzzy logic, the PID gains are tuned using a conventional tuning method. At supervisory level, fuzzy logic readjusts the PID gains online. In the first tuning method, fuzzy logic at the supervisory level readjusts the three PID gains during the system operation. In the second tuning method, fuzzy logic only readjusts the proportional PID gain, and the corresponding integral and derivative gains are readjusted using the Ziegler–Nichols tuning method while the system is in operation. For the compositional rule of inferences in the fuzzy PID and the self-organizing fuzzy PID schemes two new approaches are introduced: the min implication function with the mean of maxima defuzzification method, and the max-product implication function with the centre of gravity defuzzification method. The fuzzy PID controller, the self-organizing fuzzy PID controller and the PID controller are all applied to a non-linear revolute-joint robot arm for step input and path tracking experiments using computer simulation. For the step input and path tracking experiments, the novel self-organizing fuzzy PID controller produces a better output response than the fuzzy PID controller; and in turn both controllers exhibit better process output than the PID controller.     

Revisiting the Ziegler–Nichols step response method for PID control

The Ziegler–Nichols step response method is based on the idea of tuning controllers based on simple features of the step response. In this paper this idea is investigated from the point of view of robust loop shaping. The results are: insight into the properties of PI and PID control and simple tuning rules that give robust performance for processes with essentially monotone step responses.