ROBUST NONLINEAR PREDICTIVE CONTROL USING A DISTURBANCE ESTIMATOR

A robust nonlinear predictive control strategy using a disturbance estimator is presented. The disturbance estimator is comprised of two parts: one is the disturbance model parameter adaptation and the other is future disturbance prediction. A linear discrete model is proposed as a disturbance model which is formulated by using process inputs and available process measurements. The recursive least square (RLS) method with exponential forgetting is used to determine the uncertain disturbance model parameters and for the future disturbance prediction, future disturbances projected by the future process inputs are used. Two illustrative examples: a jacketed CSTR as a SISO system: an adiabatic CSTR as a MIMO system, and experimental results of the distillation column control are presented. The results indicate that a substantial improvement in nonlinear predictive control performance is possible using the disturbance estimator.     

基于高速局域网的连续搅拌反应釜(CSTR)控制系统

提出基于客户－服务器模式的连续搅拌反应釜（CSTR）控制系统。系统充分利用网络设备和技术，扩大了实时控制设备的应用范围和资源利用率，方便了学生学习和巩固基本的控制理论和技术。本系统可提供的操作（控制策略）有PID控制和鲁棒控制，同时还提供传输可执行文件和反馈执行结果的功能，以便测试实验者自行编写的算法程序。     

连续搅拌釜式反应器的鲁棒最优控制

针对一类带不确定性的连续搅拌釜式反应器,提出基于滑模控制理论的鲁棒最优控制算法。输入输出线性化方法用于线性化对象模型,假设系统的不确定因素有界,滑模面采用积分型滑模面以确保系统稳态误差为零,将线性二次型理论用于等效控制律的设计中,保证了系统的性能指标最优,自适应滑模切换控制增益的选取在降低系统抖振的前提下补偿了系统的不确定因素及外部扰动,实现了控制器的鲁棒最优。通过仿真实验表明,提出的控制器对匹配的不确定性因素及外部扰动具有鲁棒性,且闭环系统的性能指标最优。     

PVC反应釜釜温自抗扰控制器设计

针对反应釜釜温过程控制中存在时变性、非线性、不确定性和多干扰性的问题,在分析自抗扰技术的基础上,采用PD控制器代替非线性反馈部分对补偿后的串联积分式对象进行控制的方法,设计了反应釜釜温动态模型的自抗扰控制器。仿真结果表明：在缺乏对象精确数学模型的情况下,该系统表现出良好的静、动态品质。同时,通过Monte—Carlo实验方法验证了系统具有较强的鲁棒性。     

连续搅拌反应釜系统的非线性鲁棒控制

基于非线性鲁棒控制理论,针对一类单输入单输出连续搅拌反应釜（CSTR）模型设计了具有高增益观测器的非线性鲁棒控制器（ONRC）,并提出了一种简单的控制器参数整定方法。与非线性鲁棒控制器（NRC）和滑模控制方法（SMC）的仿真结果比较表明,ONRC对系统不确定性和干扰具有更好的抑制作用,通过Monte-Carlo试验检验显示,ONRC在模型参数摄动时具有更好的性能鲁棒性。     

过程预测控制中约束可行性研究与在线调整

化工过程控制中,普遍存在着各种对输入和输出变量的约束条件。系统与约束之间的矛盾有可能造成约束预测控制的优化问题不可行,为生产带来负面影响。基于线性系统离散状态空间的动态模型,从凸多面体距离角度,对有约束预测控制的可行性分析和不可行时的约束处理问题进行讨论,提出在每步求解约束预测控制律之前进行必要的可行性分析和合理的约束调整的在线滚动算法,从而使约束条件在整个时域得到满足,并且保证系统的控制性能。通过CSTR模型的控制仿真实验证明了该算法的有效性。     

Conditions for offset elimination in state space receding horizon controllers: A tutorial analysis

An offset-free control is one that drives the controlled outputs to their desired targets at steady state. In the linear model predictive control (MPC) framework, the elimination of steady-state offset may seem a little obscure, since the closed-loop optimization tends to hide the integral action. Theoretically, implementing a well-posed optimization problem and having unbiased steady-state predictions are sufficient conditions to eliminate the output offset. However, these basic conditions are not always achieved in practical applications, especially when state-space models are used to perform the output predictions. This paper presents a detailed practical analysis of the existing strategies to eliminate offset when using linear state-space models with moderated uncertainties. The effectiveness of these strategies is demonstrated by simulating three different control problems: a linear SISO system where the effect of using the estimation of the control variable is highlighted, a continuous stirred tank reactor (CSTR) with non-linear dynamics and the consequent model uncertainty and, a 2 × 2 system representing a distillation column that verifies the consistency of previous results and extends the conclusions to higher dimension systems.     

模糊PID控制系统设计及MATLAB仿真

在工业生产中,PID控制不适合时变系统,其参数调整也更为复杂。模糊PID控制利用专家经验得出的模糊规则,通过模糊控制器近似推理实时修正PID参数,使控制效果良好。选取双关节机械手为研究对象,利用模糊控制规则确定隶属度函数和推理方法,在Simulink中搭建模型进行仿真分析。实验结果表明,模糊PID控制在各方面均优于PID控制系统。     

A delay‐dependent robust fuzzy MPC approach for nonlinear CSTR

Based on Takagi–Sugeno (T–S) fuzzy models, a robust fuzzy model predictive control (MPC) algorithm is presented for a class of nonlinear time‐delay systems with input constraints. Delay‐dependent sufficient conditions for the robust stability of the closed‐loop system are derived, and the condition for the existence of the fuzzy model predictive controller is formulated in terms of nonlinear matrix inequality via the parallel distributed compensation (PDC) approach. By using a novel matrix transform technique, a receding optimization problem with linear matrix inequality (LMIs) constraints is constructed to design the desired controllers with an on‐line optimal receding horizon guaranteed cost. Finally, an example of continuous stirred tank reactors (CSTR) is given to demonstrate the effectiveness of the proposed results.     

ADAPTIVE CONTROL OF A CSTR WITH INPUT CONSTRAINTS

Control of a nonisothermal CSTR with input constraints has been developed. The control system is a multivariable nonlinear one. Indirect adaptive control is applied. An algorithm based on an output direction vector is proposed for determining the constrained input vector. By using the proposed method, it is possible to operate the reactor at an unstable steady state within a stable limit cycle.