积分分离法调节器直流调速系统研究

系统控制中调节器的结构和参数直接影响系统的性能指标.在性能要求较高的系统中,仅仅靠调整PI调节器的参教难以同时满足性能指标.本文提出了一种新的调节器--积分分离法调节器,成功地减小了超调量及缩短了过渡过程时间.利用MATLAB工具软件对双闭环直流调速系统进行了仿真研究,同时指出了一些现有调节器仿真模型的不足之处,证明积分分离法调节器比传统PI调节器性能优越,并给出了实现的基本思路.     

直流电机双闭环调速系统

采用工程设计方法对双闭环直流调速系统进行辅助设计,选择调节器结构,进行参数计算和近似校验.并建立起制动、抗电网电压扰动和抗负载扰动的Simulink仿真模型.分析转速和电流的仿真波形,并进行调试,使双闭环直流调速系统趋于完善、合理。     

某型航空涡轴发动机燃油调节器建模与仿真

根据某型航空涡轴发动机燃油调节器的结构原理图,分析了该型燃油调节器的调节规律以及调节器基本工作原理.进而结合该型燃油调节器在试验台上得到的部分试验数据,在MATLAB软件的SIMULINK平台上采用LookUp-Table模块构建系统非线性环节,以模拟系统的非线性特性,进而建立了该型燃油调节器的简易数学模型.对建立的燃油调节器模型进行的静态校验结果表明,调节器模型满足了该型燃油调节器的各项性能指标的要求.并结合该型涡轴发动机的数学模型进行了动态联合仿真,通过对动态仿真结果的分析,获得了影响该型调节器性能的关键结构参数及将该型调节器数字化时的采样周期范围.     

一类结构适应式自校正调节器

本文在给出一类变阶式算法的基础之上,提出了一种结构适应式自校正调节器,该算法能自动改变模型的阶段,该调节器能在线改变结构和参数。对工业电炉的实际控制表明,该调节器具有优良的性能。     

基于参考模型法的双闭环调速系统参数优化

调节器是双闭环调速系统的核心,传统的工程设计方法不仅烦琐、复杂,而且不够精确.为解决上述问题,提出了基于参考模型法的调节器参数优化方法:首先根据系统指标要求选择典型的最佳模型作为参考,然后以改进单纯形法为优化算法,通过比较控制系统和参考模型在同一输入信号下的输出偏差对调节器参数进行优化,使得在某种意义下偏差尽可能小,实现控制系统的输出响应跟踪或逼近参考模型特征.实验表明,方法不仅使设计工作大为简化,并且使控制系统较好地复现参考模型的特征,有效地提高了系统的性能.     

基于CARIMA模型的自适应预测PID调节器的自适应递推算式的推导

本文针对ＰＩＤ调节器参数整定的困难性问题，提出了基于ＣＡＲＩＭＡ模型的自适应预测ＰＩＤ调节器的结构，并推导了一套相应的自适应递推算式，使ＰＩＤ的参数随着对象特性和环境条件的变化而变化。从而极大地提高了ＰＩＤ调节器的自适应性。     

基于遗传算法的EHA调速系统设计与优化

电机调速系统是飞机电静液作动器(EHA)的关键部分,直接影响着机载作动系统的可靠性.EHA对调速系统鲁棒性,快速性有着较高的性能要求,传统的试凑法设计调速系统的调节器难以满足性能的要求.首先针对EHA的实际工作原理,建立了EHA调速控制的模型,用PID调节器设计双闭环负反馈控制系统,然后采用遗传算法对PID调节器参数寻优整定,最后根据实际工作情况与性能要求进行了仿真分析.仿真结果表明,利用遗传算法寻优设计PID调节器控制EHA所采用的大功率无刷直流电机,可以获得良好的稳定性、鲁棒性和动态性能.     

基于遗传算法的无刷直流电机控制参数优化

基于Simulink平台建立无刷直流电机双闭环控制系统仿真模型,对其双闭环均采用带限幅输出的积分分离PI调节器,利用基于实数编码的改进遗传算法对传统试凑法得出的转速环的准最优PI参数进行优化,其适应度函数充分考虑了系统的误差及控制量,得出了最优的PI参数.解决了不能准确用数学方法来描述的系统,在Matlab中可以用遗传算法实现其控制.经仿真分析表明,应用遗传算法可以快速的得到控制模型的最优参数,比传统方法相比具有更快的动态响应和更高的调节精度.     

基于模式识别的自整定控制及应用

本文提出一种基于模式识别的自整定控制方法,以模式表示和模式分类来描述系统的动态特性和调节器的结构,用模式识别优化方法求取调节器的参数,当系统动态模型参数未知时,这种自整定方法是建立在系统测量数据序列基础上的。该方法在实验性二元精馏塔上用IBM-PC微机获得成功应用。其结果优于常规PID调节器。     

连续控制系统中调节器的快速自动设计

本文运用实际系统向二阶模型逼近的方法,导出了求解调节器参数的矩阵方程,并编制了 相应的计算机辅助设计的程序.利用此程序,只要输入所期望的指标和系统固有的参数,就可 自动快速地完成调节器的设计和仿真检验.     

模块多变量自校正调节器

从约束控制的角度出发,将模块多变量控制与自校正调节器相结合,构造出一种新的 多变量自校正调节器,并对此进行了仿真研究.     

A multivariable selftuning regulator to control a double effect evaporator

A multivariable selftuning regulator has been applied in control of a pilot plant double effect evaporator. The selftuning regulator consists of a recursive least squares algorithm combined with a single step optimal control strategy which minimizes a quadratic criterion. The algorithm is very fast and can be adjusted by an external operator in order to obtain satisfactory stationary regulator performance.     

State controllability and optimal regulator control of time-delayed systems

An important recent advance in the solution of the optimal regulator control problem for time-delayed systems is extended here to multivariable systems and to systems which exhibit multiple time delays. The state equations are partitioned into discrete and continuous portions through a state transformation such that the solution of the optimal regulator problem reduces to finding a steady-state controller gain based on both a discrete and continuous Riccati matrix. The discrete Ricatti matrix is found independently of the continuous solution due to the partitioning of the state equations, and it is not necessary to solve the system of partial differential Riccati equations which arise in the traditional solution of the linear quadratic regulator (LQR) problem for time-delayed systems. In addition, through this state transformation it becomes possible to extend the standard state controllability tests to time-delayed systems. It is shown that the controllability of the transformed state space is necessary for a feasible solution to the optimal regulator problem for time-delayed systems. This is an important test to determine the practicality of various time-delayed system realizations. Numerical examples illustrate the application of the technique to systems exhibiting multiple time delays, multivariable systems and time-series models. It is shown that the classic Wood-Berry distillation model realization does not possess state controllability properties which explains why this system has been historically difficult to control using feedback techniques.     

特征结构下多变量预测控制系统的闭环反馈结构及其应用

文献[1]把多变量频域设计方法和单变量预测控制结合起来,提出了在特征结构下的多变量预测控制算法。本文在此基础上提出了特征结构下多变量预测控制系统的闭环反馈结构。利用此反馈结构不仅可有效地减少多变量预测控制算法的计算量及所需的存贮空间,而且还可以方便地判别此类预测控制系统的闭环稳定性。文中以火力发电厂中带汽-汽换热器的20万千瓦火电机组汽温系统为例进行了预测控制的仿真,仿真结果表明,用本文所提出方法设计的多变量预测控制系统,具有良好的控制效果。     

具有积分环节的多变量极点配置自校正调节器及其在罩式退火炉上的应用

本文给出一种具有积分环节的多变量极点配置自校正控制算法。该算法能在过程参数缓变时直接在线估计控制器参数校正闭环极点于期望值上,且对阶跃输入信号系统静态无偏,此算法已用于某公司三输入三输出多变量轧辊罩式退火炉微机群控系统中。实控结果表明,炉温控制精度和炉内温度场均匀度皆优于仪表PID系统,文中还给出了算法的仿真结果、微机群控系统设计和研制中的有关问题。该系统已通过鉴定,实控运行情况良好。     

Further results on the design of multivariable regulators under structure and robustness constraints

Parameter optimization methods are known to be an efficient tool for synthesizing multivariable regulators, especially when constraints are present on both their structure and the robustness of the control system. However, most of the underlying numerical algorithms first require the selection of a regulator satisfying all the assigned constraints, which is often non-trivial. This paper aims at presenting some new results on this subproblem. Specifically, constructive sufficient conditions are given for the existence of simple low-gain centralized and decentralized regulators supplying the closed-loop system with asymptotic stability as well as robust zero-error regulation in the face of ramp-type exogenous signals. Next, solutions are presented to two design problems incorporating constraints on the robustness of the control system with respect to large plant parameter variations.     

A neural network regulator for turbogenerators

A neural network (NN) based regulator for nonlinear, multivariable turbogenerator control is presented. A hierarchical architecture of an NN is proposed for regulator design, consisting of two subnetworks which are used for input-output (I-O) mapping and control, respectively, based on the back-propagation (BP) algorithm. The regulator has the flexibility for accepting more sensory information to cater to multi-input, multioutput systems. Its operation does not require a reference model or inverse system model and it can produce more acceptable control signals than are obtained by using sign of plant errors during training I-O mapping of turbogenerator systems using NNs has been investigated and the regulator has been implemented on a complex turbogenerator system model. Simulation results show satisfactory control performance and illustrate the potential of the NN regulator in comparison with an existing adaptive controller.     

Self-tuning adaptive control of cement raw material blending

A new, modified self-tuning (ST) minimum variance (MV) regulator algorithm developed for multiple input multiple output (MIMO) systems is presented with required average for finite time (RAFT). This control strategy has been developed for the self-tuning optimal control of cement raw material blending. After a brief survey of the technological background the algorithm of MIMO-ST-MV-RAFT control strategy is derived. A self-tuning blending control system is described with real-time experimental results illustrating the efficiency of the new multivariable regulator.     

带观测器的不确定多变量线性系统的反馈控制器

本文基于线性二次调节理论和李雅普诺夫稳定性理论,用带观测器的状态反馈实现了对满足匹配条件的参数不确定的多变量线性系统的鲁棒稳定控制,这个方法要解两个代数Riccati方程,不确定参数可以为时变的,但要求范数有界。     

不确定性多变量系统的变结构最终滑动模态控制方案

为了改善多变量变结构控制系统的瞬态性能，本文提出了一个变结构最终滑动模态控制方案。文中方案克服了由于多变量变结构控制中存在多个滑动模态，而带一的因采递阶控制方案导致控制结构复杂程序增加的缺点，有效地改善了系统进入最终滑动的动态品质，并对于参数摄动具有较强的鲁棒性。