基于DSP鲁棒PID控制器的电液位置伺服系统电模拟仿真研究

设计了一种基于灵敏度函数的鲁棒PID控制器,并以DSPTMS320F2812加以实现。为了验证该控制器的鲁棒性能,根据电液位置伺服系统的数学模型,设计了研究对象的电模拟仿真器。通过鲁棒PID控制器对电液位置伺服系统进行电模拟仿真实验。仿真实验结果表明：该鲁棒PID控制器在电模拟仿真器电路参数发生一定的变化时,具有很好的鲁棒性能。     

低阶时滞过程的伪预测PI／PID控制

基于单位反馈控制结构,根据期望的闭环传递函数设计得到了一种伪预测PI/PID(ADQPI/ADQPID)控制器。这种控制器只有一个可调参数,可调参数与系统动态响应性能和鲁棒稳定性之间存在直接关系,只需单调的调节控制器参数,便可实现系统的动态响应性能与鲁棒稳定性之间的最佳折衷。仿真实例表明,这种控制器在扰动和模型失配的情况下仍然具有良好的控制性能和鲁棒稳定性,是一种值得在实际工程中推广运用的新型控制器。     

鲁棒PID控制器参数整定与仿真

介绍了一种基于最小-最大原理整定鲁棒PID控制器参数的方法,并应用MATLAB优化工具箱函数按非线性二次规划法搜索合理的PID参数。仿真结果表明,优化函数寻找最佳PID参数简便可靠;当模型在一定范围内变化时,按该方法整定的鲁棒PID控制器均能保证控制系统的动态性能良好。     

基于IMC的PID控制器参数确定

应用零极点相消法设计内模控制器，选取内模控制器的滤波系数，以满足预定不确定性下鲁棒性的要求。用PID规律逼近IMC控制来确定PID参数。仿真结果表明，所设计的控制器具有较好的动态性能和鲁棒稳定性，适用于大型工业过程。     

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。     

磁悬浮储能飞轮线性变参数鲁棒增益调度控制

针对强陀螺效应的磁悬浮储能飞轮转速快变引起的模型变化而带来的控制问题,设计了线性变参数增益调度鲁棒控制器.根据飞轮的线性变参数模型,设计的鲁棒增益调度控制器,能够保证其全转速范围内的鲁棒稳定性和性能.为降低控制器设计的保守性,在设计控制器时,可缩小转速区间,使控制性能得到提高.与按照非时变模型设计的鲁棒控制器相比,线性变参数鲁棒增益调度控制器可以实现以转速为参数的自适应调节,在全转速范围内,其鲁棒稳定性和性能均具有显著优势.仿真结果验证了此控制器的有效性和先进性.     

参数不确定时滞系统的鲁棒P ID 控制

提出一种简单而有效的参数不确定时滞系统鲁棒PID控制器设计方法．通过在kp-ki平面上绘制稳定边界线,确定稳定的PID控制器参数区域;推导了一阶不稳定时滞系统PI控制器和PID控制器的存在性条件;基于推广到时滞系统的棱边定理,确定所有鲁棒PID控制器参数集．仿真实例表明了该方法的优越性．     

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。     

参数不确定机器人分散鲁棒跟踪控制

提出了一种新的参数不确定机器人分散控制器设计方法．首先将关节子系统的动力学模型分解为人工标称模型和非线性时变不确定模型两部分；然后分别设计相应的标称控制器和鲁棒补偿器．标称控制器使得标称闭环系统具有理想的跟踪性能；鲁棒补偿器可以抑制参数不确定和关节间非线性耦合等因素的影响，实现鲁棒跟踪．所设计的控制器只需要局部关节的位置反馈，具有易于实现和可在线调整的优点．仿真结果说明了该方法的有效性．     

生物质锅炉主汽压系统的H_∞混合灵敏度控制

针对生物质锅炉主汽压对象模型的不确定性和燃烧工况变化较大的特点,采用混合灵敏度控制方法设计了H∞鲁棒控制器;选择了合理的加权函数,给出了加权函数的奇异值曲线;利用MATLAB/SIMULINK进行了仿真实验并与常规PID控制结果比较,结果表明,在对象模型参数发生较大变化时,H∞混合灵敏度控制仍具有良好的鲁棒稳定性和动态性能;研制了基于DCS的生物质锅炉主汽压实时监控系统,利用MCGS组态软件设计了上位机界面,并进行了初步试验研究;实验结果表明,H∞混合灵敏度控制的生物质锅炉主汽压系统响应时间约为10 s且基本无超调,具有一定的应用价值。     

模糊自适应PID控制的研究及应用仿真

传统PID控制器参数的整定是在获取对象数学模型的基础上,根据某一整定规则来确定的,难以适应复杂多变的控制系统。针对其参数整定不良、性能欠佳,对被控过程的适应性差等缺点采用模糊控制与自适应PID控制结合起来,设计了模糊自适应PID控制器。利用模糊推理方法实现对PID参数的在线自整定,进一步完善PID控制器的性能,提高系统的控制精度。仿真结果表明该模糊自适应PID控制器既具有PID控制器高精度的优点,又具有模糊控制器快速、适应性强的特点,使被控对象具有良好的动、稳态特性,有较好的工程应用前景。     

Real-time control of a water-gas shift reactor by a model-based fuzzy gain scheduling technique

A model-based fuzzy gain scheduling technique is proposed. Fuzzy gain scheduling is a form of variable gain scheduling which involves implementing several linear controllers over a partitioned process space. A higher-level rule-based controller determines which local controller is executed. Unlike conventional gain scheduling, a controller with fuzzy gain scheduling uses fuzzy logic to dynamically interpolate controller parameters near region boundaries based on known local controller parameters. Model-based fuzzy gain scheduling (MFGS) was applied to PID controllers to control a laboratory-scale water-gas shift reactor. The experimental results were compared with those obtained by PID with standard fuzzy gain scheduling, PID with conventional gain scheduling, simple PID and a nonlinear model predictive control (NMPC) strategy. The MFGS technique performed comparably to the NMPC method. It exhibited excellent control behaviour over the desired operating space, which spanned a wide temperature range. The other three PID-based techniques were adequate only within a limited range of the same operating space. Due to the simple algorithm involved, the MFGS technique provides a low cost alternative to other computationally intensive control algorithms such as NMPC.     

Fuzzy PID Control of a Five DOF Robot Arm

This paper studies the application of fuzzy logic control on a five degrees of freedom (DOF) robot arm, the Maker 100 of U.S. Robots. The elaboration of the fuzzy control laws is based on two structures of coupled rules fuzzy PID controllers. The fuzzy PID controllers are numerically simulated and the simulation results confirm the success of the fuzzy PID control in trajectory tracking problems. Seeking a performance optimization, a systematic study of the choice of tuning parameters of the controllers is done. The success of the proposed fuzzy control law is again affirmed by a comparative evaluation with respect to the computed torque control method and the direct adaptive control method, the last two controls being also numerically implemented using the same dynamic model of the robot arm.     

基于Fuzzy推理的自调整PID控制器*

本文提出一衙 新的基于Ｆｕｚｚｙ推理的ＰＩＤ自整定控制器。     

Structural analysis of fuzzy controllers with nonlinear input fuzzy sets in relation to nonlinear PID control with variable gains

The popular linear PID controller is mostly effective for linear or nearly linear control problems. Nonlinear PID controllers, however, are needed in order to satisfactorily control (highly) nonlinear plants, time-varying plants, or plants with significant time delay. This paper extends our previous papers in which we show rigorously that some fuzzy controllers are actually nonlinear PI, PD, and PID controllers with variable gains that can outperform their linear counterparts. In the present paper, we study the analytical structure of an important class of two- and three-dimensional fuzzy controllers. We link the entire class, as opposed to one controller at a time, to nonlinear PI, PD, and PID controllers with variable gains by establishing the conditions for the former to structurally become the latter. Unlike the results in the literature, which are exclusively for the fuzzy controllers using linear fuzzy sets for the input variables, this class of fuzzy controllers employs nonlinear input fuzzy sets of arbitrary types. Our structural results are thus more general and contain the existing ones as special cases. Two concrete examples are provided to illustrate the usefulness of the new results.     

Adaptive hierarchical tuning of fuzzy controllers

Fuzzy controller design includes both linear and non-linear dynamic analysis. The knowledge base parameters associated within the fuzzy rule base influence the non-linear control dynamics while the linear parameters associated within the fuzzy output signal influence the overall control dynamics. For distinct identification of tuning levels, an equivalent linear controller output and a normalized non-linear controller output are defined. A linear proportional-integral-derivative (PID) controller analogy is used for determining the linear tuning parameters. Non-linear tuning is derived from the locally defined control properties in the non-linear fuzzy output. The non-linearity in the fuzzy output is then represented in a graphical form for achieving the necessary non-linear tuning. Three different tuning strategies are evaluated. The first strategy uses a genetic algorithm to simultaneously tune both linear and non-linear parameters. In the second strategy the non-linear parameters are initially selected on the basis of some desired non-linear control characteristics and the linear tuning is then performed using a trial and error approach. In the third method the linear tuning is initially performed off-line using an existing linear PID law and an adaptive non-linear tuning is then performed online in a hierarchical fashion. The control performance of each design is compared against its corresponding linear PID system. The controllers based on the first two design methods show superior performance when they are implemented on the estimated process system. However, in the presence of process uncertainties and external disturbances these controllers fail to perform any better than linear controllers. In the hierarchical control architecture, the non-linear fuzzy control method adapts to process uncertainties and disturbances to produce superior performance.     

基于模糊推理的自整定PID控制器

设计了一种新的模糊PID控制器。用基于给定的相角裕度和幅值裕度的方法给出了PID控制器参数的初值。在运行过程中 ,用模糊控制器在线调整PID参数 ,使过程具有较高的控制品质     

模糊PID控制技术研究发展回顾及其面临的若干重要问题

简要回顾了模糊PID控制器的研究发展状况,系统地归纳了模糊PID控制器的 基本形式.讨论了阻碍模糊控制技术发展的几个重要理论问题,包括系统化设计方法,控制 性能优于传统PID控制器的模糊控制器设计,模糊控制器非线性逼近能力及其量化指标,模 糊系统的规则爆炸.文中试图对有关问题的内涵进行重新定义,以及探求解决难题的关键. 如将模糊系统中的"规则爆炸"问题更正为"参数效率"问题.最后,提出了对模糊控制 理论与技术发展的思考,其中特别强调应把"简单性"作为智能控制器设计中的基本策略.     

一种新型模糊非线性PID控制器

采用一维输入一维输出的模糊映射关系与传统PID控制器相级联的方式，构成一个模糊非线性PID控制器以提高现有PID控制器的性能．一维模糊控制器无需选择与调整量化因子和比例因子，采用五条规则，易于实现．数值仿真和误差泛函积分评价指标表明，所提出的模糊非线性PID控制器比现有控制器具有更好的动静态性能．     

一种新型的二维PID模糊控制器

通过对常规PID控制器的结构分析,设计出一种新型的二维PID模糊控制器,其结构形式简称为fuzzy PD+ fuzzy ID型.根据模糊规则的图解分析,提出fuzzy ID控制嚣的输入变量(偏差和偏差变化加速率)与输出变量之间的控制结构,并确定两控制器的模糊控制规则的相似性.通过对该PID模糊控制器的结构分析,给出与常...