液位控制的模糊内模PID控制器设计

本文介绍了液位过程模糊内模PID控制器的设计.利用机理分析和实验辨识相结合的方法建立了被控过程的数学模型,并依据内模控制原理设计了一种PID控制器,该控制器结构简单,只有一个可调参数.为了克服了内模控制器参数整定要在系统标称性能和鲁棒性之间进行折衷选择的局限性,利用模糊逻辑实现了控制器参数的在线自动整定.实验结果表明,模糊内模PID控制器能有效地改善系统的性能.     

预测函数控制的内模控制理论

内模控制是一种基于过程数学模型进行控制器设计的新型控制策略,是研究预测控制重要的理论基础。预测函数控制是一种控制量计算方程简单,实时控制效果好的新型预测控制算法。本文用内模控制理论研究预测函数控制,分析了系统的鲁棒性和稳定性,最后进行了参数设计和仿真研究。     

基于灰色预测的自适应内模PID双重控制器设计

针对一类非线性系统,提出一种基于灰色预测的自适应内模PID双重控制方法.把由系统的输入输出数据得到的灰色预测模型作为系统的内部模型,并在基本的内模控制结构上增加PID控制器,加快了跟踪误差收敛速度, 内模控制的性能明显改善.仿真结果表明,该控制方法简单而有效, 内模PID双重控制较单一内模控制具有更好的系统性能.     

内模控制研究进展

内模控制由于其本质鲁棒性的优势,被广泛应用于工程实际中.系统地评述了内模控制系统中控制器设计、滤波器改进、两自由度结构、单变量内模控制、多变量解耦内模控制等问题此外,内模控制与其他先进控制策略的结合是提升内模控制效果的重要途径,详细介绍了内模控制与预测控制、神经网络、模糊控制、自适应控制、最优控制等先进控制策略的结合,...     

一类工业过程预测控制的闭环分析

该文定量分析了一类典型工业过程预测控制系统的闭环性能,文中首先基于广义动态矩 阵控制系统的内模控制结构和控制器的最小化形式,导出了一阶惯性加时滞的典型对象预测 控制的闭环传递函数,在此基础上,给出了预测控制中主要设计参数与闭环动态响应和扰动抑 制时间的解析关系以及关于闭环系统鲁棒性的三个定理,提出了对增益或时滞失配允许范围 的搜索算法,从而为分析和设计预测控制系统提供了理论依据.     

基于内模控制的互耦水槽建模与仿真

研究工业控制器稳定控制问题,内模控制(IMC)结构和设计简便,只有一个整定参数,参数调整与系统动态品质和鲁棒性的关系明确,采用IMC原理可以提高PID控制器的设计水平.为保证水槽系统的稳定性和跟踪性,从IMC的基本结构出发,提出了一种简单的IMC控制器设计方法,使用一个单负反馈回路系统,对控制对象化简成一个简单的一阶加延迟模型,然后整定出所需控制器的参数,以达到控制要求.通过MATLAB上进行仿真,结果表明,所设计的控制器具有常规PID的优点,且跟踪调节性能好,对水槽控制具有较好的鲁棒性和动态性,证明IMC法具有广泛的适用性.     

内模强化学习型模型预测控制及其在人工胰脏上的应用

在学习型模型预测控制的框架里,迭代学习控制器被用来更新模型预测控制器的设定点.在已经发表的研究成果里,学习型模型预测控制用到的是比例型的学习率,这种学习率的学习能力有限,而且怎样设计学习增益仍然是一个开放性问题.在本文中,基于内模控制理论提出的PID型的迭代学习控制器被用来更新模型预测控制器的设定点.为了方便起见,本文提出的结合算法可称为内模强化学习型模型预测控制.本文提出的算法应用在(1)型糖尿病人的人工胰脏闭环控制上.仿真结果显示,本算法对比于比例学习型模型预测控制可以达到更好的收敛性能,而且对非重复干扰有很好的鲁棒性.     

基于IMC原理的电子节气门控制策略

发动机系统中的电子节气门是一种典型的非线性控制对象,特别是节气门运动过程中的弹簧扭矩和摩擦阻力十分复杂,其数学模型很难精确建立,参数不易获取.针对电子节气门的非线性因素,提出一种内模控制器的设计方法.首先分析电子节气门系统的数学模型,在Matlab/Simulink仿真平台上对模型的有效性进行验证,进而以内模控制结构为基础,建立电子节气门复域模型,分析系统的非线性干扰,设计针对时变参数的内模控制器.仿真结果显示,在模型较精确的情况下,内模控制器具有优于传统PID和一般滑模控制的控制性能,而在模型失配的情况下,内模控制器的鲁棒性能够保证它的控制性能仍然优于传统PID.在所提出的内模控制器设计方法中,前馈滤波器的设计并未用到任何系统参数,但仍然能够保证理想的稳态响应和扰动响应,因此所提出方法相比于很多针对具体模型的控制策略,具有更好的实用价值.     

基于Backstepping设计的不确定非线性系统的预测控制

本文的目的是针对一类带有不确定性的单输入单输出的仿射非线性系统,设计一种非线性预测控制器.用反步设计思想获得具有待定参数的控制器表达式,然后用预测控制在线优化获得控制器的参数.用这种方法设计的控制器更易使闭环系统稳定,且闭环系统具有良好的动态特性.连续发酵过程的仿真结果也验证了控制器是有效的.     

基于多步控制集的鲁棒预测控制器设计

针对有约束多胞不确定系统, 本文提出多步控制集的概念, 并将其作为终端集进而设计鲁棒预测控制器. 由于设计了一系列可变的反馈律, 鲁棒预测控制器可以得到更好的控制性能和更大的初始可行域. 另外, 利用多步控制集的特性, 本文提出了一种将预测控制器的在线计算量转移到离线完成的算法. 通过该算法, 可以有效地平衡鲁棒预测控制器的控制性能、在线计算量和初始可行域. 仿真算例验证了这些算法的有效性.     

Output constrained IMC controllers in control systems of electromechanical actuators

Electromechanical actuators are widely used in many industrial applications. There are usually some constraints existing in a designed system. This paper proposes a simple method to design constrained controllers for electromechanical actuators. The controllers merge the ideas exploited in internal model control and model predictive control. They are designed using the standard control system structure with unity negative feedback. The structure of the controllers is relatively simple as well as the design process. The output constraint handling mechanism is based on prediction of the control plant behavior many time steps ahead. The mechanism increases control performance and safety of the control plant. The benefits offered by the proposed controllers have been demonstrated in real-life experiments carried out in control systems of two electromechanical actuators: a DC motor and an electrohydraulic actuator.     

高超声速飞行器的调度离线预测控制

本文将调度预测控制的思想应用于离线鲁棒预测控制,设计了高超声速飞行器计算有效的调度离线预测控制器.首先在不同的平衡点离线设计一系列控制规则,实际实施时只需要在不同的控制器之间进行切换,避免进行在线优化,大幅度减少了在线计算时间.通过估计局部控制器的稳定域,保证了切换控制器的稳定性.另外在确保良好控制品质的同时,还能够保证所有输入和状态均在给定约束范围.仿真试验表明,提出的方法能实现速度和高度较大范围的指令跟踪,所有输入和状态均在给定约束范围内;相比于在线鲁棒预测控制方法,仿真运行时间减少,可以实现高超声速飞行器的实时控制.     

Distributed model predictive control of an experimental four-tank system

A distributed model predictive control (DMPC) framework is proposed. The physical plant structure and the plant mathematical model are used to partition the system into self-sufficient estimation and control nodes. Local measurements at the nodes are used to estimate the relevant plant states. This information is then used in the model predictive control calculations. Communication among relevant nodes during estimation and control calculations provides improvement over the performance of completely decentralized controllers. The DMPC framework is demonstrated for the level control of an experimental four-tank system. The performance of the DMPC system for disturbance rejection is compared with other control configurations. The results indicate that the proposed framework provides significant improvement over completely decentralized MPC controllers, and approaches the performance of a fully centralized design.     

The Mimo Predictive Pid Controller Design

This paper is concerned with the design of Multi‐Inputs and Multi‐Outputs (MIMO) predictive PID controllers, which have similar performance to that obtainable from model‐based predictive controllers. A new PID control structure is defined which incorporates the prediction of future outputs and uses future set point. A method is proposed to calculate the optimal values of the PID gains from generalised predictive control results. A decentralized version of the predictive PID controllers is presented and the stability of the closed loop system is studied. Simulation studies demonstrate the superior performance of the proposed controller compared with a conventional PID controller. The results are also compared with generalised predictive control solutions.     

基于模型预测控制的统一电能质量调节器

随着电力电子器件和装置在电力系统中广泛应用,电网中的非线性负荷不断增加,进而导致谐波畸变大量产生,电能质量问题日益严重.为了改善电网电能质量,提出了基于模型预测控制理论以及卡尔曼滤波方法的统一电能质量调节器的设计.首先介绍了统一电能质量调节器的基本结构和基本原理,并进行建模得到其状态空间模型,然后在此模型基础上,采用卡...     

基于自控网系统的混杂控制

混杂控制系统通常是复杂的非线性控制系统,难以用统一的模型进行建模. David和Alla提出的混杂Petri网,虽然可以解决一般混杂系统的建模问题,并得到了广泛的应用,但对于传统的如PID这类控制器,缺乏统一建模的能力.探讨了基于广义自控网系统的混杂控制方法,实现了对混杂控制器中监控器和数字控制器进行统一的Petri网建模.仿真实例设计了基于广义同步自控网系统的电加热炉控制系统,给出了可根据不同温度状态实施多种控制策略的变结构数字控制器模型,并详细分析了控制器的性能,证明了广义自控网系统具有十分强大的建模能力和广泛的应用前景.     

Robust distributed model predictive control of linear systems with structured time-varying uncertainties

In this work, synthesis of robust distributed model predictive control (MPC) is presented for a class of linear systems subject to structured time-varying uncertainties. By decomposing a global system into smaller dimensional subsystems, a set of distributed MPC controllers, instead of a centralised controller, are designed. To ensure the robust stability of the closed-loop system with respect to model uncertainties, distributed state feedback laws are obtained by solving a min–max optimisation problem. The design of robust distributed MPC is then transformed into solving a minimisation optimisation problem with linear matrix inequality constraints. An iterative online algorithm with adjustable maximum iteration is proposed to coordinate the distributed controllers to achieve a global performance. The simulation results show the effectiveness of the proposed robust distributed MPC algorithm.     

Tuning algorithms for fractional order internal model controllers for time delay processes

This paper presents two tuning algorithms for fractional-order internal model control (IMC) controllers for time delay processes. The two tuning algorithms are based on two specific closed-loop control configurations: the IMC control structure and the Smith predictor structure. In the latter, the equivalency between IMC and Smith predictor control structures is used to tune a fractional-order IMC controller as the primary controller of the Smith predictor structure. Fractional-order IMC controllers are designed in both cases in order to enhance the closed-loop performance and robustness of classical integer order IMC controllers. The tuning procedures are exemplified for both single-input-single-output as well as multivariable processes, described by first-order and second-order transfer functions with time delays. Different numerical examples are provided, including a general multivariable time delay process. Integer order IMC controllers are designed in each case, as well as fractional-order IMC controllers. The simulation results show that the proposed fractional-order IMC controller ensures an increased robustness to modelling uncertainties. Experimental results are also provided, for the design of a multivariable fractional-order IMC controller in a Smith predictor structure for a quadruple-tank system.     

机械手臂的多模型预测控制

针对机械手臂的非线性特点,提出了基于隶属度函数的多模型预测控制方法。该方法首先根据机械手臂的特点,选择合适的调度变量,将机械手臂的工作空间划分为若干个工作子空间,在每个子空间内的平衡点处对机械手臂进行线性化处理,得到相应的线性子模型,从而得到机械手臂的多模型表示;其次针对每个线性子模型设计局部预测控制器,使其在相应的子空间内达到控制要求;最后选择梯形隶属度函数与局部预测控制器进行加权求和,获得全局多模型预测控制器,以对机械手臂进行控制。仿真结果表明,当机械手臂的工作条件在大范围内变化时,全局多模型预测控制器的控制性能远优于常规PD控制器,达到了预期的控制目的。     

Optimal anti-windup synthesis for repetitive controllers

Repetitive controllers use internal models that provide very high gain at a selected fundamental frequency and its harmonics, additionally, some of the internal models may result unstable, as in the high order repetitive control approach. These characteristics make the repetitive control system susceptible to exhibit wind-up when actuator saturation occurs. This paper proposes an anti-windup scheme for repetitive control based on the model recovery anti-windup strategy. The proposed scheme provides low order, low computational burden and also isolation of the controller from the saturation effects. The anti-windup compensator is constructed from the plant model and provides an additional linear feedback path aimed at enhancing system performance. This feedback path is designed to obtain a deadbeat behaviour, which makes the system recovery faster. Finally, internal stability and deadbeat features are designed in a compact procedure based on linear matrix inequalities and an optimal linear quadratic design. Experimental validation of the proposed anti-windup compensator is provided using a mechatronic plant.