Improving disturbance rejection of PI controllers by means of the magnitude optimum method

The magnitude optimum (MO) method provides a relatively fast and nonoscillatory closed-loop tracking response for a large class of process models frequently encountered in the process and chemical industries. However, the deficiency of the method is poor disturbance rejection when controlling low-order processes. In this paper, the MO criterion is modified in order to optimize disturbance rejection performance, while the tracking performance has been improved by an integral set-point filtering PI controller structure. The new tuning rules, referred to as the disturbance rejection magnitude optimum (DRMO) method, were applied to several different two-degrees-of-freedom PI controllers. The DRMO method has also been tested on several different representatives of process models. The results of experiments have shown that the proposed tuning method with the integral set-point filtering PI controller is quite efficient in improving disturbance rejection performance, while retaining tracking performance comparable to the original MO method.     

Comparative study of decay ratios of disturbance-rejection magnitude optimum method for PI controllers

One of the key time-domain closed-loop performance requirements is the closed-loop response decay ratio. In this paper, the decay ratios of the disturbance-rejection magnitude optimum (DRMO) tuning method [Vranci? D, Strmcnik S, Kocijan J. Improving disturbance rejection of PI controllers by means of the magnitude optimum method. ISA Trans 2004; 43: 73-84; Vranci? D, Strmcnik S. Achieving optimal disturbance rejection by using the magnitude optimum method. In: Pre-prints of the CSCC'99 conference. 1999. p. 3401-6] are analyzed and compared to decay ratios of two other modern tuning methods, i.e. the Kappa-Tau tuning method (based on time-domain step-response characteristics) [Astr?m KJ, H?gglund T. PID controllers: Theory, design, and tuning. 2nd ed. Instrument Society of America; 1995] and the non-convex optimization tuning method (based on frequency response) [Panagopoulos H, Astr?m KJ, H?gglund T. Design of PI controllers based on non-convex optimization. Automatica 1998; 34: 585-601; Panagopoulos H, Astr?m KJ, H?gglund T. Design of PID controllers based on constrained optimisation. IEE Proc Control Theory Appl 2002; 149 (1): 32-40]. It is shown that the DRMO method results in such a closed-loop response that the decay ratio is within a relatively narrow interval when compared to the other two methods.     

Explicit analytical tuning rules for digital PID controllers via the magnitude optimum criterion

Analytical tuning rules for digital PID type–I controllers are presented regardless of the process complexity. This explicit solution allows control engineers 1) to make an accurate examination of the effect of the controller's sampling time to the control loop's performance both in the time and frequency domain 2) to decide when the control has to be I, PI and when the derivative, D, term has to be added or omitted 3) apply this control action to a series of stable benchmark processes regardless of their complexity. The former advantages are considered critical in industry applications, since 1) most of the times the choice of the digital controller's sampling time is based on heuristics and past criteria, 2) there is little a–priori knowledge of the controlled process making the choice of the type of the controller a trial and error exercise 3) model parameters change often depending on the control loop's operating point making in this way, the problem of retuning the controller's parameter a much challenging issue. Basis of the proposed control law is the principle of the PID tuning via the Magnitude Optimum criterion. The final control law involves the controller's sampling time T_s within the explicit solution of the controller's parameters. Finally, the potential of the proposed method is justified by comparing its performance with the conventional PID tuning when controlling the same process. Further investigation regarding the choice of the controller's sampling time T_s is also presented and useful conclusions for control engineers are derived.     

On the centrality of disturbance rejection in automatic control

In this paper, it is shown that the problem of automatic control is, in essence, that of disturbance rejection, with the notion of disturbance generalized to symbolize the uncertainties, both internal and external to the plant. A novel, unifying concept of disturbance rejector is proposed to compliment the traditional notion of controller. The new controller–rejector pair is shown to be a powerful organizing principle in the realm of automatic control, leading to a Copernican moment where the model-centric design philosophy is replaced by the one that is control–centric in the following sense: the controller is designed for a canonical model and is fixed; the difference between the plant and the canonical model is deemed as disturbance and rejected.     

Enhanced disturbance rejection for open-loop unstable process with time delay

The present study suggests a disturbance estimator design method for application to a recently published, two-degree-of-freedom, control scheme for open-loop, unstable processes with time delay. A simple PID controller cascaded with a lead-lag filter replaces the high-order disturbance estimator for enhanced performance. A new analytical method on the basis of the IMC design principle, featuring only one user-defined tuning parameter, is developed for the design of the disturbance estimator. Several illustrative examples taken from previous works are included to demonstrate the superiority of the proposed disturbance estimator. The results confirm the superior performance of the proposed disturbance estimator in both nominal and robust cases. The proposed method also offers several important advantages for industrial process engineers: it covers several classes of unstable process with time delay in a unified manner, and is simple and easy to design and tune.     

Tuning PID controllers for higher-order oscillatory systems with improved performance

In this paper, model based design of PID controllers is proposed for higher-order oscillatory systems. The proposed method has no limitations regarding systems order, time delays and oscillatory behavior. The reduced model is achieved based on third-order modeling and selection of coefficients through the use of frequency responses. The tuning of the PID parameters are obtained from a reduced third-order model; the procedure seems to be simple and effective, and improved performance of the overall system can be achieved. Three simulation examples and one real-time experiment are included to demonstrate the effectiveness and applicability of the proposed method to systems with oscillatory behavior.     

模糊规则调整微分作用的PID控制方法

PID控制器广泛应用于工业过程控制中 ,但对于非线性、时变不确定性的系统 ,常规 PID控制器难以获得满意效果。随着模糊控制理论的不断发展 ,利用其非线性特征 ,将其与 PID控制相结合 ,能有效改善 PID控制效果。设定值权系数的模糊逻辑整定 PID控制器 (FSW)方法在固定设定值权系数的基础上 ,用模糊推理方式计算“动态”的权系数 ,取得了一定的效果 ,但是仍存在一些问题。针对阶跃响应的上升及调整时间长、第一次超调后的反向振幅较大的缺点 ,采用模糊逻辑规则调整微分作用的改进方法 ,可以弥补上述不足。对一些典型对象进行仿真 ,结果表明该方法明显优于 Z- N方法 ,固定设定值权系数 b方法和 FSW方法     

温度控制系统的模糊PID控制方法研究

温度系统具有滞后现象严重等非线性特点,很难建立精确的数学模型,基于数学模型的控制方法很难实现高精度的温度控制。为此,本文提出了一种不依赖数学模型的基于模糊控制的PID温度控制方法。通过在MATLAB Simulink环境中利用Fuzzy工具箱建立仿真系统,并进行仿真实验研究,其结果表明采用模糊PID控制方法的系统的动、静态性能和精度得到明显提高。     

PID控制器参数快速整定的新方法

本文分析了影响控制器参数整定的几个基本问题（控制目标、优化准则和被控过程的特性），提出了精确地确定被控过程模型参数的方法。通过计算机仿真，系统地提出了可适用于多容过程的ＰＩＤ控制器参数快速整定新方法。     

基于分布种群遗传算法的二自由度PID控制器参数优化整定

利用一种基于分布种群的遗传算法,对整定困难的二自由度PID控制器的参数进行优化整定,并给出了该遗传算法的数学描述。该算法将寻优空间划分为多个不相交子空间,分别对在各子空间内的种群进行遗传操作,评价种群适应度,细化解空间,达到在较小的范围做精细搜索的目的,兼顾了搜索的广度和深度,提高了寻优的搜索性能,克服了常规遗传算法易陷入局部极值的缺陷。仿真试验证明了其有效性。     

基于自抗扰控制的变速非圆车削技术研究

为了抑制非圆截面工件加工时的颤振,将变速加工应用于非圆截面车削中,设计了变速车削系统结构,分析了变速车削抑制颤振、提高稳定性的机理,设计了适于变速非圆车削的直线伺服单元,单元控制采用自抗扰控制技术.车床控制系统采用PMAC(Programmable multi-axis controller)时基控制法,实现刀具驱动进给和工件变速旋转的协调控制,完成非圆截面的变速车削.结果表明,直线伺服单元能很好地跟踪刀具目标值,非圆截面车削加工精度和稳定性得到了提高.     

一种模糊规范化PID控制器混沌优化设计

基于混沌变量,提出了一种FNPID参数混沌优化设计。文中将混沌动力学特性与退火策略结合起来实现混沌优化搜索,体现出具有更强的FNPID参数全局最优值的搜索能力。仿真实验表明能有效地实现FNPID控制器参数优化,控制结果具有稳定、无振荡、无超调、响应快、调节时间短的优点,算法结构简单,编程容易。     

基于遗传算法的PID控制器参数优化研究

本文提出了一种基于遗传算法的PID控制器参数优化设计。在参数整定与优化过程中。考虑了过程控制系统的参数整定特点和寻优精度。通过仿真研究表明：该方法比一般PID参数整定方法具有更好的控制性能指标。     

基于自抗扰技术的风扇磨直吹锅炉主汽压力控制系统的研究

文章针对由于被控对象的时变和非线性特性给风扇磨直吹式锅炉主汽压力自动调节带来的控制品质恶化问题,采用了自抗扰控制(ADRC)策略,这种控制算法只需被控对象的输入输出信息就能很好的估计出系统的实时内外扰动总和、并将其加以补偿,该控制器具有结构简单、响应快、鲁棒性强等优点.仿真表明这种控制器能有效改善该类系统的控制品质.     

Calculation of PID controller parameters by using a fuzzy neural network

In this paper, we use the fuzzy neural network (FNN) to develop a formula for designing the proportional-integral-derivative (PID) controller. This PID controller satisfies the criteria of minimum integrated absolute error (IAE) and maximum of sensitivity (Ms). The FNN system is used to identify the relationship between plant model and controller parameters based on IAE and Ms. To derive the tuning rule, the dominant pole assignment method is applied to simplify our optimization processes. Therefore, the FNN system is used to automatically tune the PID controller for different system parameters so that neither theoretical methods nor numerical methods need be used. Moreover, the FNN-based formula can modify the controller to meet our specification when the system model changes. A simulation result for applying to the motor position control problem is given to demonstrate the effectiveness of our approach.     

基于遗传算法优化的汽车半主动悬架PID控制仿真研究

PID控制器在汽车半主动悬架应用中存在参数确定的问题,针对这一问题设计了一种基于遗传算法优化整定PID参数的方法.该方法利用遗传算法的全局优化能力,以半主动悬架的性能指标为目标函数对PID参数进行优化设计.应用该方法进行汽车半主动悬架平顺性仿真.仿真结果表明,基于遗传算法优化的PID控制器的汽车半主动悬架相对于PID控制主动悬架以及被动悬架而言,改善了车身垂向加速度和悬架动行程.同时在充分利用PID控制器优势的基础上,改善了其参数确定过程中存在的问题.     

智能PID控制在中央空调冷水系统中的仿真研究

针对中央空调冷水系统是典型的非线性、大滞后、时变性、大惯性及强耦合的复杂系统,其中参数未知或变化缓慢;带有延时或随机干扰,无法获得较为精确的数学模型或模型非常粗糙。常规PID控制器因其对精确模型的依赖性,且难以在线进行PID参数整定,故难以达到满意的控制效果。文章在传统PID的基础上,结合模糊控制原理,提出了基于模糊推理方法对PID控制器参数进行整定,设计出相应的模糊PID控制器。最后,运用MATLAB仿真研究表明,模糊自整定PID控制器既具有常规PID高精度的优点,又具有模糊控制快速、适应性强的特点,使被控对象具有良好的动、稳态特性。     

航空用活塞式发动机节气门自适应脉动PID控制器研究

结合某型航空用活塞式发动机节气门自动控制问题,建立了节气门系统数学模型;通过系统分析给出了自适应脉动PID控制算法,在系统数字仿真基础上确定控制器的参数;通过发动机实验,实现了节气门的较为精确控制。实验结果表明,与传统PID控制算法相比,自适应脉动PID控制在小阶跃信号输入下响应时间提高了10%以上,稳态误差减小了16%以上。     

无人旋翼机线性自抗扰航向控制

研究无人旋翼机器人在干扰情况下的航向控制问题.无人旋翼机航向动力学包含输入非线性、时变参数和主-尾旋翼之间的强耦合,难以建立精确的数学模型,并且易受外部扰动影响,很难达到良好的控制性能.针对这一问题提出基于线性自抗扰控制(linear adaptive disturbance rejection control,LADRC)的航向控制方法,通过设计扩张线性状态观测器对未知模型和外界干扰进行实时估计并进行在线补偿.以自主研制的无人旋翼机为例,建立其航向动力学方程,把通道间的交叉耦合影响视为不确定扰动,将其与外部干扰作为扩张状态,利用观测器带宽确定观测器增益,设计线性扩张状态观测器来跟踪各阶扩张状态变量,为说明LADRC的有效性,选用PD控制为非线性状态误差反馈控制律实现航向控制.仿真以及试验结果表明在外部扰动或模型结构参数发生变化时控制器仍可获得理想的动态性能,具有很好的适应性和鲁棒性.     

两种数字PID算法在电锅炉温度控制系统中的应用比较

在数字PID算法中,为了避免传统PID控制器算法中积分累积所造成的系统较大超调和不稳定,甚至是积分饱和,人们常常会使用积分分离PID算法加以改进.本文又提出了变速积分PID算法,并以电锅炉温度控制系统为例,基于MATLAB并运用仿真分析手段,对两种不同算法的控制效果进行了比较,得出了积分分离算法的上升时间tr较短,而变...