复合控制器及其在连消中的应用

由于常规PID控制方式对非线性、大滞后对象难以进行有效的控制,模糊控制具有很好的动态特性,所以结合常规PID和模糊控制的优势设计了参数自调整Fuzzy-PID复合控制器。通过模糊推理实现参数自调整,以使控制器能够适应不同对象和对象的不同状态。采用模糊推理的方法完成两种控制方式的平稳过渡。对某制药厂连消温度的控制表明,该控制器可以大幅度提高控制精度和缩短系统响应时间,从而避免了染菌事故的发生,提高了发酵单位。     

一种比例因子自调整的模糊预测函数控制

针对由主、副被控对象级联而成的大纯滞后系统,提出一种内回路采用PI控制、外回路采用具有比例因子自调整的模糊增量型预测函数控制策略,它将预测函数控制和具有比例因子自调整的模糊控制进行综合来共同控制由内回路和主被控对象构成的广义被控对象。大量的仿真实验表明:本方法较其他方法控制效果更好,即使在模型严重失配时,本方法仍具有很强的鲁棒性和抗干扰能力。     

Self-tuning PID controllers based on the Lyapunov approach

In this paper, a self-tuning PID controller using just-in-time learning (JITL) technique is proposed. A set of linear models obtained by the JITL provides the information required to adjust the parameters of PID controller. The self-tuning algorithm for the PID parameters is derived by a rigorous analysis based on the Lyapunov method such that the JITL's predicted tracking error converges asymptotically. Simulation results are presented to illustrate the proposed self-tuning PID controller and a comparison with its conventional counterparts is made.     

MULTIVARIABLE CONTROL OF CATALYTIC CRACKING PROCESSES

Simple, explicit and physically intuitive Feedforward and Feedback control policies are designed for Fluidized Catalytic Cracking Processes. The Feedforward (FF) control algorithm compensates for changes in the feed rate and feed coking tendency by the use of the air flow and catalyst circulation rates as control variables to maintain the conversion and the reactor temperature at fixed levels. Through steady state and dynamic simulations the FF controller is shown to be very effective. To improve the dynamic response of the process and to account for the process/model mismatch a feedback (FB) controller is also designed to complement the FF action. The FB action is designed by use of the transformation related to the physical modes which correspond to the extensive variables of the process. It is shown that the required control structure consists of two loops. One uses the air flow rate to control the total sensible heat content of the reactor and regenerator solid phases. The other loop controls the regenerator enthalpy by changes in the catalyst circulation rate. The air flow rate controller includes an integral action to avoid reactor temperature offsets, while the catalyst circulation rate controller requires a nonlinear static observer to predict the coke concentration on the regenerated catalyst from dense bed and flue gas regenerator temperatures. The performance of the controller for changes on the oil feed rate, caking tendency of the feed, as well as for reactor temperature set point changes is faster and smoother than Kurihara's scheme.     

基于模糊自整定PID燃气锅炉仿真研究

针对燃气热水锅炉具有非线性、大惯性及多变量等特点,借助经验公式分析并用MATLAB系统辨识工具箱完成了系统数学模型的辨识,确定了燃气锅炉温度控制系统的模型结构可等效为一阶惯性加滞后环节,在此基础上确立了基于MATLAB的系统SIMULINK仿真框图,设计了模糊自整定PID控制器.通过模糊自整定PID与常规PID算法的仿真对比分析,得出模糊自整定PID不仅在调节时间、超调量等动态性能上的控制效果明显优于常规PID控制效果,而且增强了系统的鲁棒性和适应性,具有良好的动、静态性能.     

MULTIRATE MULTIVARIABLE SELF-TUNING CONTROL OF DISTILLATION COLUMNS USING KALMAN PREDICTOR

A novel method for designing Kalman Predictor (KP) based multivariable self-tuning controllers for Multi Input Multi Output (MIMO) systems has been proposed, and also applied to the control of two distillation columns. The objective is to maintain constant terminal compositions despite disturbances entering the system even when the controlled variables are not measured at the same sampling rate. The KP generates minimum variance estimates of the output variables. Simulation results show that KP based multirate multivariable self-tuning controller exhibits better performance than the earlier reported multirate controller for set point tracking, even in the presence of nonstationary disturbances. KP based self-tuning controller is, therefore, suitable for industrial applications.     

Modeling, simulation and control of a methanol synthesis fixed-bed reactor

In this paper, the dynamic behavior and control of the low pressure methanol synthesis fixed bed reactor have been investigated. For simulation purpose, a heterogeneous one-dimensional model has been developed. First, the reactor simulation is carried out under steady-state condition and the effects of several parameters such as shell temperature, feed composition (especially CO₂ concentration) and recycle ratio on the methanol productivity and reactor temperature profile are investigated. Using the steady state model and a trained feedforward neural network that calculates the effectiveness factor, an optimizer which maximizes the reactor yield has been developed. Through the dynamic simulation, the system open loop response has been obtained and the process dynamic is approximated by a simple model. This model is used for the PID controller tuning and the performances of fixed and adaptive PID controllers are compared for load rejection and set point tracking. Finally the proposed optimizer is coupled with a controller for online optimization and hot spot temperature protection.     

自校正P ID算法在再热器中的应用

针对再热器的温度控制问题,设计了一种极点配置PID控制器。给出了CARMA模型,引入带遗忘因子的最小二乘实时参数估计算法和带数字滤波器的增量式PID控制算法,同时给出了极点配置自校正PID的整定方法过程,建立PID参数与系统参数及控制性能指标之间的关系式,并进行了MATLAB仿真。     

IDENTIFICATION AND ROBUST CONTROL OF AN INDUSTRIAL STEAM REFORMER

The dynamic behaviour of a methane fired steam reformer is studied in an industrial environment. A system identification approach is used to determine transfer functions linking coil outlet temperature and fuel rate. All models have in common an unstable zero and large gain fluctuation over different operating conditions. A statistical clustering technique was used to determine the reactor dynamic model, for different operating conditions. To counteract the impact of gain fluctuation, a minimax error process model selection was used to determine a nominal model for the design of an IMC controller. The tuning of the controller was shown to be equivalent to the tuning of the time constant of the robustness filter. Improved temperature regulation can be used to increase the operating temperature of the reactor, thus leading to reducing the steam to carbon ratio and in turn improving process ecconomics.     

Demonstration of a control system for combustion of lean hydrocarbon emissions in a reverse flow reactor

In this work, the performance of a simple logic-based controller for a reverse flow reactor (RFR) has been tested experimentally. The controller is a hybrid system using the inside reactor temperature as the controlled variable, and the switch of the flow direction as the manipulated variable. Three different control logic rules (depending on the point selected to measure the inside reactor temperature) have been compared for the catalytic combustion of methane in a bench-scale RFR unit. A procedure for tuning the controllers was established. The controller that measures the temperature in the middle of the reactor showed the best performance, as it provided complete methane conversion with high capacity to overcome both low and high feed concentration disturbances.     

CONTROL OF MOLECULAR WEIGHT IN A BATCH POLYMERIZATION REACTOR USING LONG-RANGE PREDICTIVE CONTROL METHODS

Recently two powerful control algorithms, namely, dynamic matrix control (DMC) and extended self-tuning regulator (ESTR), have been advocated for the design of robust industrial controllers. The present paper demonstrates the application of DMC and ESTR algorithms to a bulk methyl methacrylate batch polymerization reactor operating under strong diffusional limitations of termination and propagation reactions. A realistic mathematical model is employed to simulate the strong nonlinear, time-varying dynamics of the polymerization process. The general control objective is to maintain the monomer conversion and number-average molecular weight along some desired state trajectories despite the presence of process disturbances in the total initiator concentration. It is shown that both controllers can satisfactorily control the monomer conversion and number-average molecular weight by manipulating the polymerization temperature. The similarities and the main operating features of the two controllers are examined and their closed-loop performance is directly compared to the performance of a conventional linear quadratic controller (LQC). Finally the effects of DMC and ESTR tuning parameters on the calculated control action are investigated.     

A logic-based controller for the mitigation of ventilation air methane in a catalytic flow reversal reactor

The control system of a catalytic flow reversal reactor (CFRR) for the mitigation of ventilation air methane was investigated. A one-dimensional heterogeneous model with a logic-based controller was applied to simulate the CFRR. The simulation results indicated that the controller developed in this work performs well under normal conditions. Air dilution and auxiliary methane injection are effective to avoid the catalyst overheating and reaction extinction caused by prolonged rich and lean feed conditions, respectively. In contrast, the reactor is prone to lose control by adjusting the switching time solely. Air dilution exhibits the effects of two contradictory aspects on the operation of CFRR, i.e., cooling the bed and accumulating heat, though the former is in general more prominent. Lowering the reference temperature for flow reversal can decrease the bed temperature and benefit stable operation under rich methane feed condition.     

Temperature control of highly exothermic batch polymerization reactors

In this article a highly exothermic batch polymerization reactor is considered. The reactor is simplified as a mixing tank with the internal heat generation treated as a disturbance. A fuzzy-hybrid-PID-feedback (FH-PID) control structure is developed in which the output of fuzzy hybrid portion is used to adjust the set point of a PID controller to compensate for the effect of the major disturbance, the heat of reaction. In this way, the hybrid portion of the controller does not influence the stability of the original PID control system. A fuzzy model was constructed to estimate the heat of reaction inside the fuzzy hybrid block. The fuzzy parameters of the hybrid portion do not depend on the process model and can be estimated from the transient response obtained with a conventional PID controller. This FH-PID control strategy has been applied to the temperature control of batch solution and batch inverse emulsion polymerizations of acrylamide in a 1 gallon pilot scale reactor. The results show that this fuzzy hybrid—PID-feedback control strategy improves the control performance of the batch polymerization reactor.     

Hierarchical control of a train of continuous polymerization reactors

A multilayer control scheme is synthesized for a series of polymerization stirred tank reactors to control the monomer conversion over the reactor line. In this work two layers of control are implemented. In the' first level digital PI or self-tuning regulators (STR) are used to control the reaction temperature of each reactor in the series by manipulating the flowrates of the coolant streams. In the second layer, a locally linear state space model, that can predict the monomer concentration in each reactor, is derived based on steady-state energy balances. A quadratic performance index is then minimized to obtain the optimal reaction profile that will bring the monomer distribution over the reactor line to its desired target value.     

基于DRNN神经网络的石油钻机自动送钻系统智能控制研究

针对钻井过程的非线性、不确定性和实时性要求,采用基于对角神经网络(DRNN)的控制方案,能在线自适应的调整P ID控制器的3项参数。以自动送钻实验系统模型为被控系统进行仿真实验,仿真结果表明可以达到较为理想的控制结果,基于DRNN神经网络控制器结构简单,易于实现,效果明显优于传统的P ID控制器。     

模糊自整定PID控制器的设计与仿真

制浆碱回收蒸发工段第一步就是通过蒸汽将黑液进行浓缩,蒸汽的温度控制效果对后续燃烧工段和苛化工段起着举足轻重的作用。主管道蒸汽温度控制通常具有大惯性、大延迟、时变等特性,采用常规的PID控制难以获得满意的控制效果。为此,提出一种模糊自整定PID控制器的串级控制算法,该算法很大程度上提高了主蒸汽温度的控制品质。针对隶属度函数对模糊推理模型的精度影响和控制算法的特点编写了模糊规则,并且根据动态性要求的不同,分两种情况进行比较。仿真表明,模糊自整定PID串级控制算法在整体性能上要优于传统PID串级控制。     

Generalization of Takagi-Sugeno Fuzzy Controller and its Application to Control of MMA Batch Polymerization Reactor

In this research a generalization of Takagi-Sugeno fuzzy controllers is presented. In this generalization all or some of the inputs of the fuzzy controllers are fuzzy numbers. Also, it is proved that this generalization is well defined, which means that if the inputs of a generalized Takagi-Sugeno fuzzy controller are singleton fuzzy sets, then the generalized Takagi-Sugeno fuzzy controller will be reduced to a Takagi-Sugeno fuzzy controller. This controller was applied to temperature control of a methyl methacrylate (MMA) batch polymerization reactor, which uses jacket temperature error in addition to reactor temperature error. But the desired jacket temperature is affected by noise and disturbance. Therefore, there is uncertainty in the desired value of this variable. Fuzzy numbers are applied to model this uncertainty and a fuzzy trajectory was achieved for jacket desired temperature. After that an adaptation mechanism was designed. Experimental results present the fine performance of this controller in temperature control of solution polymerization of methyl methacrylate.     

A thermal‐flywheel approach to distributed temperature control in microchannel reactors

Microchannel reactors are a promising route for monetizing distributed natural gas resources. However, intensification and miniaturization represent a significant challenge for reactor control. Focusing on autothermal methane‐steam reforming reactors, a novel microchannel reactor temperature control strategy based on confining a layer of phase‐change material (PCM) between the reactor plates is introduced. Melting‐solidification cycles, which occur with latent heat exchange at constant temperature, allow the PCM layer to act as an energy storage buffer—a “thermal flywheel”—constituting a distributed controller that mitigates temperature excursions caused by fluctuations in feedstock quality. A novel stochastic optimization algorithm for selecting the PCM layer thickness (i.e., distributed controller “tuning”) is introduced. Furthermore, a hierarchical control structure, whereby the PCM layer is complemented by a supervisory controller that addresses persistent disturbances, is proposed. The proposed concepts are illustrated in a comprehensive case study using a detailed two‐dimensional reactor model. © 2013 American Institute of Chemical Engineers AIChE J, 59: 2051–2061, 2013     

A new constrained self-tuning pid controller

A new constrained self-tuning PID controller is developed based on Clarke and Gawthrop's (1975) generalized minimum variance (GMV) controller. Convergence properties for the new algorithm are derived and the effect of the constraint parameter is evaluated. Extension of the controller to include more than the usual three PID parameters occurs naturally. No process model information is required for our algorithms except the dead time. This is an improvement over other algorithms which impose severe constraints on the process structure. The controller algorithm is tested on a variety of models using simulation as well as under experimental conditions. The algorithm is easy to implement and compares favourably with the more complex GMV controller.     

流化床反应器中气相丙烯聚合反应的动力学和预测控制(英文)

A two-phase dynamic model, describing gas phase propylene polymerization in a fluidized bed reactor, was used to explore the dynamic behavior and process control of the polypropylene production rate and reactor temperature. The open loop analysis revealed the nonlinear behavior of the polypropylene fluidized bed reactor, jus- tifying the use of an advanced control algorithm for efficient control of the process variables. In this case, a central- ized model predictive control （MPC） technique was implemented to control the polypropylene production rate and reactor temperature by manipulating the catalyst feed rate and cooling water flow rate respectively. The corre- sponding MPC controller was able to track changes in the setpoint smoothly for the reactor temperature and pro- duction rate while the setpoint tracking of the conventional proportional-integral （PI） controller was oscillatory with overshoots and obvious interaction between the reactor temperature and production rate loops. The MPC was able to produce controller moves which not only were well within the specified input constraints for both control vari- ables, but also non-aggressive and sufficiently smooth for practical implementations. Furthermore, the closed loop dynamic simulations indicated that the speed of rejecting the process disturbances for the MPC controller were also acceotable for both controlled variables.