改进型Fuzzy—Smith控制在再热器中的应用

针对再热器温度控制系统具有不确定性,大迟延和大惯性等特点,基于Smith预估器结构,提出一种改进方案。在Smith预测控制的基础上引入了模糊自整定方案,仿真和试验结果表明,新的控制方案不仅具有满意的控制性能,而且具有较强鲁棒性和抗干扰性能,对时变大滞后对象具有良好的控制效果。     

温湿度解耦的模糊PID-自适应Smith控制

工业空调PID控制系统的温湿度控制具有大时滞、非线性、时变性和耦合性,难以建立精确的数学模型。提出前馈补偿解耦、模糊PID与自适应Smith预估补偿算法相结合的控制方案,以弥补常规PID控制在温湿度控制系统的不足。仿真结果表明:该方案既解决了温湿度耦合问题又提高了控制的精度和稳定性,增强了系统的鲁棒性和适应性,具有较好的动、静态性能。     

基于Smith预估器的PID自适应控制及其应用

针对大时滞时变对象 ,把Smith补偿控制原理和PID参数的自适应调整方法结合起来 ,提出了基于BP神经网络整定Smith PID控制算法 ,即在Smith预估补偿控制系统中 ,利用BP神经网络在线自学习整定PID参数 ,使PID参数实现最佳的非线性组合 ,以适应对象特性的变化 ,从而克服了常规PID算法不适应大时滞系统控制和常规Smith算法过于依赖模型精度的缺陷。仿真研究和实际应用表明 ,本文算法具有很强的鲁棒性和良好的控制品质 ,工程应用控制效果令人满意。     

1GW超超临界机组主汽温控制策略的仿真

对谏壁电厂1GW超超临界机组主汽温控制的过热汽温控制系统运用改进的Smith预估控制实现,有效地解决了超超临界机组的大延迟和大惯性问题.AnySimu仿真结果表明,改进的Smith预估补偿控制策略消除了主汽温控制过程中的惰性区,控制回路的调节速度加快,具有较好的控制性能.     

论一种完全抗干扰Smith预估控制方案的可用性

研究了完全抗干扰Smith预估控制方案的应用实现问题。用理论分析和仿真试验的方法证明了完全抗干扰Smith预估控制方案存在的可实现性问题和稳定性问题。其可实现性问题可以通过两环节串接后实现的方式避开,但是系统稳定性缺陷将导致整个方案的不可用。     

一种改进的Smith预估控制系统

提出一种改进的Smith预估器 ,在常规Smith预估器的基础上增加了两个控制器 ,内环控制器用来稳定积分和不稳定过程 ,反馈控制器对干扰进行抑制 ,并把主控制器设为设定值加权PI控制器。仿真结果表明 ,该方案不仅可行 ,而且在模型失配的条件下 ,控制品质比常规的Smith预估控制有很大的改善。     

Smith预估-模糊控制在硝酸氧化炉自设定氨空比控制中的应用

硝酸生产氧化炉温度控制系统具有大惯性、非线性及时变等特点,采用常规控制方法对温度进行控制难以获得满意的效果。因此,提出一种新的基于模糊控制的氨空比自动设定方案,通过模糊控制器输出氨空比修正值,实现了氨空比的自动设定;同时,将Smith预估控制应用于主回路进行温度补偿,减小了时滞的不利影响。仿真结果显示:该方案自动设定的氨空比能够很好地调节氧化炉温度,较常规控制方法超调量小、调节时间短。     

改进型Smith-专家PID算法在烘缸温度串级系统上的应用

针对少烘缸或单烘缸纸机的干燥过程具有滞后大、惯性大且非线性的缺点,提出专家PID结合Smith预估器的算法,设计了少烘缸纸机或单烘缸纸机的烘缸温度和蒸汽流量串级控制系统。主控制器是改进的专家PID控制器,利用基于专家经验的知识库在线调整PID参数;对主回路采用改进型Smith预估器,以克服纯滞后对系统稳定性的影响,也解决了Smith预估器对数学模型精确要求的问题。利用MATLAB进行仿真,结果表明:改进型Smith-专家PID算法具有良好的控制品质,具有超调小及响应速度快等动态特性。     

自适应控制在聚乙烯调温水系统中的应用

含有时滞的聚乙烯调温水串级控制系统是复杂的非线性时变系统,系统存在较大的纯滞后,采用模型参考自适应控制结合PID控制方法,使自适应控制器能够在线调整PID参数以匹配Smith预估器,使Smith预估器不受被控对象参数变化的影响。仿真结果表明:该控制方案有效减少了控制系统的超调量和调节时间。     

基于Smith预估器的抄纸过程水分定量控制

针对抄纸过程水分定量系统具有时变性、非线性和大纯滞后的特征，提出了基于Smith预估器的抄纸过程水分定量控制方法。该方法通过在线测量纯滞后时间，使Smith预估器的特点得到充分的发挥，有效地克服了纯滞后对控制系统稳定性及性能指标的影响。实际运行结果表明，该方法具有较好的鲁棒性。     

Development of MBPLS based control for serial operation processes

A control scheme based on the multiblock PLS (MBPLS) model for multi-stage processes (or serially connected processes) is developed. MBPLS arranges a large number of variables into meaningful blocks for each stage of the large-scale system. Two control design strategies, course-to-course (CtC) and within-stage (WS) controls, are proposed for the re-optimization design in the whole multistage course. In CtC, MBPLS control and optimization are done by applying feedback from the finished output quality when one course for all stages is done. It utilizes the information from the current course to improve quality of the next one. In WS, the MBPLS-based re-optimization strategy is developed to explore the possible adjustments of the future inputs at the rest of the stages in order to fix up the disturbances just in time and to maintain the product specification when the current course is finished. The proposed technique is successfully applied to two simulated industrial problems, including a photolithography sequences and a reverse osmosis desalination process, and the advantages of the proposed method are demonstrated.     

ADAPTIVE MULTIVARIABLE PID CONTROLOF A DISTILLATION COLUMN WITH UNKNOWN AND VARYING DEAD TIME

A new, reliable, and easy-to-use adaptive control strategy has been developed to overcome the long-existing difficulties in adaptive control practice caused by unknown and varying process dead time. A self-tuning PID control algorithm is adopted to control a distillation column possessing second-order-plus-dead-time dynamics. The self-tuning strategy is based on recursive least-squares estimation of process parameters. U-D factorization is applied to stabilize the parameter estimation calculations. A variable forgetting factor is used to alleviate wind-up in the estimator. A simulation study and an experimental evaluation demonstrate the capability of the adaptive algorithm.     

PLC在塑料挤出机温度控制系统中的应用

介绍了SIMATIC S7－300可编程控制器在塑料挤出机温度控制系统中的应用，控制回路采用PID参数自整定和脉宽调功法，控制系统把传统的PID控制和PLC的逻辑判断指令结合起来，使PID控制更为灵活，能满足生产过程的要求。详细描述了系统的工作原理和PLC的硬件组成、软件编制，简单介绍了上位机的组态软件WinCC。     

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

This paper aims at providing a framework for detection and diagnosis of the performance of a combinational feedforward (FF) and cascade (CC) control system. It is the extension of our previous work [1,2]. The main idea is to extract the only CC effect and the combination of FF with CC effects, respectively. In the only CC effect, the output variances of the primary and the secondary loops can be turned into the cascade-invariant and cascade-dependent terms, respectively. The combination of FF with CC effect can also be decomposed into the cascade/feedforward invariant term, the cascade-invariant/feedforward-dependent term and the cascade/feedforward dependent term. The diagnosis tree based on these decomposition terms is proposed to assess the performance of the FF/CC control system. The sequence of the statistical inference system is developed to diagnose fault causes. The capability of the proposed method is demonstrated via a cascade control system with the feedforward loops and multiple faults.     

Polymer property control in a continuous styrene polymerization reactor using model-on-demand predictive controller

The model-on-demand (MoD) framework was extended to the model predictive control (MPC) to design a multiple variable model-on-demand predictive controller (MoD-PC). This control algorithm was applied to the property control of polymer product in a continuous styrene polymerization reactor. For this purpose, a local auto-regressive exogenous input (ARX) model was constructed with a small portion of data located in the region of interest at every sample time. With this model an output prediction equation was formulated to calculate the optimal control input sequence. Jacket inlet temperature and conversion were chosen as the elements of regressor state vector in data searching step. Simulation studies were conducted by applying the MoD-PC to MIMO control problems associated with the continuous styrene polymerization reactor. The control performance of the MoD-PC was then compared with that of a nonlinear MPC based on the polynomial auto-regressive moving average (ARMA) model for disturbance rejection as well as for setpoint-tracking. As a result, the MoD-PC was found to be an effective strategy for the production of polymers with desired properties.     

APPLICATION OF FUZZY ADAPTIVE CONTROLLER IN NONLINEAR PROCESS CONTROL

In general, physical processes are usually nonlinear and control system design based on the linearization technique cannot control the process well for a wide range of operation. Use of the variable transformation method may not always solve the problem. In this paper, a fuzzy adaptive controller is proposed to control the nonlinear process. The CSTR control problem has also been considered. The results are compared with the method of nonlinear model predictive control (NMPC) with constrained and unconstrained control variables. A fuzzy model-following control system scheme is also proposed. The results show that the proposed controller is a feasible control structure for a nonlinear or parameter-variations process control.     

Model predictive control for the reactant concentration control of a reactor

The reactant concentration control of a reactor using Model Predictive Control (MPC) is presented in this paper. Two major difficulties in the control of reactant concentration are that the measurement of concentration is not available for the control point of view and it is not possible to control the concentration without considering the reactor temperature. Therefore, MIMO control techniques and state and parameter estimation are needed. One of the MIMO control techniques widely studied recently is MPC. The basic concept of MPC is that it computes a control trajectory for a whole horizon time minimising a cost function of a plant subject to a dynamic plant model and an end point constraint. However, only the initial value of controls is then applied. Feedback is incorporated by using the measurements/estimates to reconstruct the calculation for the next time step. Since MPC is a model based controller, it requires the measurement of the states of an appropriate process model. However, in most industrial processes, the state variables are not all measurable. Therefore, an extended Kalman filter (EKF), one of estimation techniques, is also utilised to estimate unknown/uncertain parameters of the system. Simulation results have demonstrated that without the reactor temperature constraint, the MPC with EKF can control the reactant concentration at a desired set point but the reactor temperator is raised over a maximum allowable value. On the other hand, when the maximun allowable value is added as a constraint, the MPC with EKF can control the reactant concentration at the desired set point with less drastic control action and within the reactor temperature constraint. This shows that the MPC with EKF is applicable to control the reactant concentration of chemical reactors.     

Prediction and quality control of the melt index during production of high-density polyethylene

In polyolefin processes the melt index (MI) is the most important control variable indicating product quality. Because of the difficulty in the on-line measurement of MI, a lot of MI estimation and correlation methods have been proposed. In this work a new dynamic MI estimation scheme is developed based on system identification techniques. The empirical MI estimation equation proposed in the present study is derived from the 1 ^st -order dynamic models. Effectiveness of the present estimation scheme was illustrated by numerical simulations based on plant operation data including grade change operations in high density polyethylene (HDPE) processes. From the comparisons with other estimation methods it was found that the proposed estimation scheme showed better performance in MI predictions. The virtual sensor model developed based on the estimation scheme was combined with the virtual on-line analyzer (VOA) to give a quality control system to be implemented in the actual HDPE plant. From the application of the present control system, significant reduction of transition time and the amount of off-spec during grade changes was achieved     

利用DCS计算模块实现焦油搅拌的控制

焦油原料槽循环搅拌控制系统结构较复杂,维护量大,我们借助DCS硬件设备,用I/A Series计算模块实现了循环搅拌控制功能。输入/输出以及运行状态都可以在操作站的监视画面自动显示出来,系统维护量很小。