基于控制性能比较的非线性不对称系统预测控制

生产过程某些非线性系统常常表现出不对称动态特性,相对于其在工业工程中经常出现的理论研究特别是控制方法研究则十分有限。本文针对基于正反方向上的两个线性模型分别设计PID控制器的缺陷,提出根据正反方向上的线性模型分别设计相应的状态反馈预测控制器。在每一步的控制率计算中,正反方向的控制器分别计算控制作用,并通过比较正反控制器的控制性能指标来确定最终采用的控制作用。通过pH值控制的仿真实验证明其对非线性不对称系统的控制效果明显优于传统的在正反方向分别采用PID控制的控制效果。     

化工过程强非线性系统的变模型自适应预测控制

提出一种变模型自适应预测控制算法 ;基于非线性状态空间模型 ,通过每步在当前工作点 (非平衡点 )线性化获得线性化子模型 ,以此进行状态反馈预测控制 ,线性化子模型随工作点变化 ,且不限于平衡点。通过pH值控制的对比仿真实验 ,证明其对强非线性过程的控制效果优于传统的多模型预测控制。最后分析讨论了该控制算法存在的几个重要问题 ,并指出与之相关的未来研究方向     

模糊预测控制在循环水加药控制中的应用

针对模糊控制和预测控制的特点.提出了一种模糊预测控制方法,利用模糊逻辑实现被控对象模糊化,解决被控对象难以建立的问题;利用预测控制,根据系统当前信息预测出系统未来的变化趋势,解决被控对象滞后问题.以火电厂循环水加药控制为例,对该控制方法进行了仿真和实际应用研究.结果表明,该系统能有效地避免纯滞后环节在控制系统中带来的振荡现象,工程应用取得了理想的控制效果,为纯滞后、大惯性、模型不确定系统的控制提供了很好的解决方法.     

网络调度与保性能控制的协同设计

为了分析NCS中调度对控制性能的影响,研究了控制与调度协同设计时的保性能控制.首先,建立了输入、反馈端都具有通信约束的NCS调度模型,并利用通信序列来表示调度情况,将NCS中的不确定离散系统转化为不确定离散切换系统.在静态调度下,利用切换系统中的多Lyapunov函数方法,对系统的状态反馈保性能控制展开分析,并以LMI形式给出系统保性能控制律存在的充分条件.仿真表明,该方法可以用于分析不同调度情况对NCS保性能控制的影响.     

基于LPV模型的燃料电池空气进气系统控制

质子交换膜燃料电池是一种通过氢气和氧气的电化学反应将化学能直接转化为电能的装置。提出一种改进的四阶燃料电池进气系统模型,分析了系统的约束性。针对系统模型所具有的非线性特性,提出建立线性变参数（LPV）模型用于对系统的控制。针对状态变量不可测的问题引入卡尔曼滤波器,同时通过可观性分析得出系统所需测量的最佳变量。在符合约束条件下设计基于线性变参数模型的状态空间模型预测控制器,控制空压机的工作电压保证氢气燃料的充分反应。仿真结果表明,基于LPV模型的模型预测控制器能够对空气进气系统进行有效的控制,且满足空压机喘振和阻塞边界等约束条件,与单模型预测控制相比具有更好的控制效果。     

模型预测控制及在粮食干燥过程的应用研究

从模型预测、滚动优化及反馈校正三方面简要介绍了模型预测控制（MPC）方法,归纳了MPC的优点;概述了粮食干燥控制的发展动态、我国粮食干燥控制研究概况以及国外的粮食干燥MPC研究状况;通过具体实例,详细介绍了美国研发的适用于横流式谷物干燥杌的MPC系统,以期为我国的同类研究提供借鉴和参考。     

自校正内模控制器

提出了设计自校正内模控制的新方法。该方法把输出预测误差划分为有规律和无规律误差两部分。通过在线辨识建立有规律误差的预报模型，由此模型对误差值进行自适应预报，达到对内模控制器的在线校正，而对无规律的误差只作闭环反馈修正，最后达到消除系统的稳态余差，本方法比通常自校正内模控制算法的运算量大大减少，而在对象参数在一定范围内漂移时，同样能取到自校正效果。     

前馈变量对预测控制可行域的影响分析

实际生产过程中,预测控制因其解耦性能和强鲁棒性得以广泛使用。在预测控制的研究中大都忽略控制过程中的干扰作用。对于控制过程中存在的可测且变化规律已知的干扰作用,干扰对输出的影响具有一定的可预见性,可通过在预测控制器中引入前馈的方法加以利用。前馈变量的引入会对系统的控制效果产生影响,如果不先对其影响进行分析而直接求解优化,最终结果不能反映预测控制的实际效果。本文从可行域的角度出发,通过几何表现形式,直观分析前馈变量的引入造成的可行域变化;进一步使用了凸空间的思想,通过求解可行域的顶点集合来确定可行域的大小,进而得出前馈变量对系统可行域的影响效果,通过仿真验证了本文方法的有效性。     

基于广义预测控制为主的综合控制算法构成控制器的开发与应用

提出一种以广义预测控制算法为主,以由Smith预估参数组成的无模型控制律为辅,以多变量状态反馈为前馈的综合控制算法控制器,其中广义预测控制算法在PC机中实现并通过与DCS通讯完成数据交换,而Smith预估控制、无模型控制率、多变量状态反馈算法均在DCS中实现。此种控制器克服了广义预测控制抗干扰能力弱的缺点,在加热炉控制应用中其优越性得到充分体现,解决了加热炉自动控制的难题,保证了工艺指标。     

基于状态预测的塑料薄膜张力反馈控制器设计

塑料薄膜工业生产过程中,张力控制系统存在明显的非线性和滞后性,严重影响了塑料薄膜产品的质量。为了提高塑料薄膜张力控制系统的控制精度以及动态性能,基于神经网络对系统进行状态预测,并利用预测的系统状态设计了反馈控制器。通过神经网络在线辨识动态非线性模型,构建了神经网络动态辨识器;运用泰勒级数展开法计算预测未来时刻的神经网络权值,并建立状态预测器;根据预测状态设计了塑料薄膜张力系统的反馈控制器;通过对比仿真实验验证了所设计反馈控制器能够明显改善塑料薄膜张力控制系统的控制精度及控制性能。     

Controlled output variance based diagnosis tree for feedforward/feedback control systems

A diagnosis tree based on the controlled output variance is proposed to assess a feedforward/feedback control performance. It is used for diagnosing and removing its fault causes. Based on the controlled output, the current output variance of the feedback/feedforward system is contributed by the feedback-only effect and the combination of feedback with feedforward effects, respectively. The feedback loop variance can be further expressed as the sum of the feedback invariant (FBI) term and the feedback-dependent (FBD) term. The feedforward loop variance can also be decomposed into the feedback/feedforward invariant (FBI/FFI) term, the feedback-invariant/feedforward-dependent (FBI/FFD) term and the feedback/feedforward-dependent (FBD/FFD) term. These effect variations are systematically conducted by a sequence of the statistic hypothesis testing procedures and the isolation strategy to compare the current control performance and the achievable benchmark operating one. Without the traditional complex physical model and/or any external input to change the current operating process, the diagnosis tree with hierarchical structure is constructed. The capability of the proposal is illustrated through two simulation cases with multiple faults.     

Two-degree-of-freedom output feedback controllers for nonlinear processes

In this work, a nonlinear output feedback control algorithm is proposed, in the spirit of model-state feedback control. The structure provides state estimates using a process model, the measured output, and the residual between the model output and the measured output. These estimates will track the process states at a rate determined by a set of tunable parameters. An algebraic transformation of the state estimates is incorporated in the control structure to ensure that the input/output gain of the observer matches the model upon which the static state feedback control law is based. The transformed states are then used in the control law. This leads to a controller of minimal order possessing integral action. The control structure is shown to have the same properties as the standard model-state feedback structure. The resulting algorithm is a two-degree of freedom control law, in the sense that the control action is not a function of the error only, but the output and the set point are processed in different ways. Finally, a simulation example using an exothermic CSTR operating at an open-loop unstable steady state is used to demonstrate the closed-loop performance of the proposed method.     

汽油产品质量先进控制与工程应用

针对催化裂化装置主分馏塔汽油产品质量先进控制系统，从实时控制应用出发，建立了塔顶塔段汽油产品质量先进控制的简化收态空间数学模型。使用实测状态变量反馈和可测干扰变量前馈的状态反馈预测控制方法，提高控制系统的性能及抗干扰能力，使模型的适应范围大大增强，并且不需要对实际运行装置进行测试建模，减少对生产过程的干扰影响。     

基于区域协调分析的约束内模控制方法与研究

针对多变量系统控制输入变量受到约束的严格限制时,一般工业上都是用预测控制来显式的处理这些约束条件和变量之间的关联耦合作用,而用内模控制来解决这方面的问题还处在探索中这一现状,初步性地利用内模控制的思想,用静态优先级来协调变量之间的耦合关联,并结合模型预测理论知识,利用区域分析法判断,使控制量处在约束范围内。仿真结果表明这种设计方法对控制效果具有一定的可实现性和意义。     

基于PID对角优势补偿阵的过程多变量控制系统设计

化工过程一般为多变量系统,输入输出变量之间往往存在耦合作用,常规分散PID控制系统难以保证控制质量。为了削弱多变量系统的耦合作用,基于对角优势的设计准则,通过在若干频率点加权优化,设计PID动态预补偿阵。然后利用正Nyquist阵列设计法对补偿后的系统设计控制器,基于对角优势系统的Nyquist稳定判据,通过绘制优势度曲线和Gershgorin带判断系统的优势程度,初步确定反馈矩阵的稳定参数范围,再按照单输入单输出系统设计动态补偿器,使得系统满足动态控制品质要求。最后通过示例说明,该方法设计的集中控制系统与分散控制相比,控制性能具有一定的优势,且方法简便,容易实现。     

基于定量反馈理论的多变量解耦预测控制及其在CSTR化学过程中的应用

1 INTRODUCTION Many multi-input and multi-output (MIMO) sys- tems worldwide are regarded as linear invariants, but there are still some difficulties in controlling these systems. The challenges arise from the need to achieve both robust stability and control performance when the plants to be controlled are highly uncer- tain[1―3]. Quantitative feedback theory (QFT) is a fre- quency domain design technique[4], which is perhaps the only known method that deals with highly uncer- tain pla…     

Two-degree-of-freedom output feedback controllers for discrete-time nonlinear systems

A discrete-time, model-based output feedback control structure for nonlinear processes is developed in the present work. The structure makes use of a closed-loop observer, while at the same time it guarantees that the overall feedback controller possesses integral action. An algebraic transformation is applied on the observer states to insure that the input/output gain of the observer matches the model upon which the static state feedback control law is based. The resulting control algorithm is a two-degree-of-freedom control law, in the sense that the output and the set point are processed in different ways. The control structure is shown not only to have the same properties as the standard model-state feedback structure, but also that it emerges from a model algorithmic control framework. Finally, a simulation example using an exothermic CSTR operating at an open-loop unstable steady state is used to evaluate the closed-loop performance of the proposed method.     

Economic model predictive control of nonlinear time‐delay systems: Closed‐loop stability and delay compensation

Closed‐loop stability of nonlinear time‐delay systems under Lyapunov‐based economic model predictive control (LEMPC) is considered. LEMPC is initially formulated with an ordinary differential equation model and is designed on the basis of an explicit stabilizing control law. To address closed‐loop stability under LEMPC, first, we consider the stability properties of the sampled‐data system resulting from the nonlinear continuous‐time delay system with state and input delay under a sample‐and‐hold implementation of the explicit controller. The steady‐state of this sampled‐data closed‐loop system is shown to be practically stable. Second, conditions such that closed‐loop stability, in the sense of boundedness of the closed‐loop state, under LEMPC are derived. A chemical process example is used to demonstrate that indeed closed‐loop stability is maintained under LEMPC for sufficiently small time‐delays. To cope with performance degradation owing to the effect of input delay, a predictor feedback LEMPC methodology is also proposed. The predictor feedback LEMPC design employs a predictor to compute a prediction of the state after the input delay period and an LEMPC scheme that is formulated with a differential difference equation (DDE) model, which describes the time‐delay system, initialized with the predicted state. The predictor feedback LEMPC is also applied to the chemical process example and yields improved closed‐loop stability and economic performance properties. © 2015 American Institute of Chemical Engineers AIChE J, 61: 4152–4165, 2015