Nonlinear control of polymerization reactor

In this work, nonlinear model based control was applied to the free radical solution polymerization of styrene in a jacketted batch reactor and its performance was examined to reach the required monomer conversion and molecular weight. Optimal temperature profiles for the properties of polymer quality were evaluated using the Hamiltonian optimization method. Total simulation program having mass and energy balances of the jacketed polymerization reactor was used to calculate the optimal trajectories. For control purposes, several experimental and theoretical dynamic studies have been made to observe the validity of simulation program. Experimental and theoretical nonlinear model based control have been investigated to track the temperature at the optimal trajectory Two types of parametric and nonparametric models were evaluated to achieve the temperature control. For this purpose, reaction curve was obtained to calculate the system dynamic matrix as a nonparametric model. In all control work, heat input to the reactor was chosen as a manipulated variable. Nonlinear auto regressive moving average exogenous (NARMAX) giving a relation between heat input and reactor temperature was chosen to represent the system dynamic and this model was used to describe the related control system as a parametric model. NARMAX model parameters were determined by using Levenberg Marquard algorithm. A pseudo random binary sequence (P.R.B.S.) signal was employed to disturb the system. Total simulation program was used to calculate the system and control parameters. Several types and orders were used to construct the NARMAX models. The efficiency and the performance of the nonlinear model based control with the NARMAX model and dynamic matrix were tested to calculate the best model. Nonlinear model based control system was used to control the reactor temperature at desired temperature trajectory experimentally and theoretically. Theoretical simulation results were compared with experimental control data. It was concluded that the control simulation program represents the behavior of the controlled reactor temperature well. In addition, nonlinear model based control keeps the reactor temperature of optimal trajectory satisfactorily.     

状态估计技术及其在聚合反应器控制中的应用

介绍了在线检测技术和状态估计技术,及利用状态估计技术获取单体转化率、聚合物相对分子质量分布和组成等产品特性,实现聚合反应器的在线控制的应用。     

Long range predictive control of a polymerization reactor

This paper examines the application of generalized predictive control (GPC), one in the class of long-range predictive algorithms, to the control of conversion of methyl methacrylate (MMA) monomer in a simulated CSTR, and to the control of temperature in a pilot plant batch polymer reactor. The control objective is regulation in the presence of (i) stochastic disturbances due to impurities (in the case of the CSTR), and (ii) pulse disturbances from the addition of cold solvent and initiator (in the case of the batch reactor). The role of the observer polynomial as a detuning parameter for trading off performance against variability in the control action is emphasized. Also, the role of data prefiltering, prior to model parameter estimation, is examined. A frequency domain interpretation of the least squares estimation algorithm is used to clarify the role of the filter.     

Adaptive pole removal control for a batch polymerization reactor

A systematic method of controller design is introduced to determine the overall charcteristic behaviour developed on process pole removal. The time delay compensation is automatically incorporated in the proposed control law. The implemented tuning parameters in the law are confined to the range between 0 and 1 to guarantee the stability of the overall control system. Subsequently, the fixed and adaptive control strategies are implemented to simulate a batch PVC reaction system. The adaptive control scheme provides good, roubust control of this simulated reactor notwithstanding the wide range of operating conditions and non-linear dynamics of the system. However, the fixed control scheme performs well only for a noise-free system. In addition, two limiting control laws, derived from the proposed method, are also used to simulate the reactor. The results indicate that these laws are not suitable for this non-linear reaction system.     

Nonlinear temperature control of a batch suspension polymerization reactor

This paper concerns nonlinear temperature control of a batch polymerization reactor where suspension polymerization of methyl methacrylate (MMA) takes place. For this purpose, four control algorithms, namely, a fix proportional‐integral (PI) controller, an adaptive proportional‐integral‐derivative (PID) controller and two globally linearizing control (GLC) schemes, one for known kinetic model (GLC‐I) and the other for unknown kinetic model (GLC‐II), are selected. The performances of these controllers are compared through simulation and real‐time studies in the presence of different levels of parameter uncertainty. The results indicate that GLCI and GLC‐II have better performances than fix PI and adaptive PID, especially in case of strong gel effect. The worst performance belongs to adaptive PID because of rapid model changes in gel effect region. GLC‐II has a simpler structure than GLC‐I and can be used without requiring the kinetic model. In implementation of GLC‐I the closed loop observer should be used because of model uncertainties.     

LMI-based robust model predictive control for a continuous MMA polymerization reactor

A linear matrix inequality (LMI)-based robust model predictive control (MPC) is applied to a continuous stirred-tank reactor for the polymerization of methyl methacrylate (MMA). The polytopic model is constructed to predict the responses to various control input sequences by using Jacobians of uncertain nonlinear model at several operating points and the controller design is characterized as the problem of minimizing an upper bound on the ‘worst-case’ infinite horizon objective function subject to constraints on the control input and plant output. Simulation studies under different conditions are conducted to validate the feasibility of the optimization problem and evaluate the applicability of such a control scheme. Simulation results show that, despite the model uncertainty, the LMI-based robust model predictive controller performs quite satisfactorily for the property control of the continuous polymerization reactor and guarantees the robust stability.     

Suspension polymerization of styrene with circular loop reactor

A circular loop reactor was devised and applied to the suspension polymerization of styrene. The transient droplet diameter distribution and the final particle size distribution are measured by changing widely the impeller speed, the dispersed phase volume fraction, and the stabilizer concentration. The effects of these conditions on the size distribution and mean size of the final polymer particle are investigated. An expression correlating the mean particle size with the operating conditions is derived. The circular loop reactor is found to be superior to the production of the polymer particle of uniform size.     

Integrated run-to-run and on-line model-based control of particle size distribution for a semi-batch precipitation reactor

The dynamics of particle size distribution (PSD) in a precipitation process are represented by a population balance (PB) and related differential–algebraic equations. The control of PSD is studied by using a closed-form solution of the PB. Batch-to-batch control and on-line single batch control strategies are investigated for controlling a semi-batch reactor. A systematic integration of the two strategies is shown to have a complementary effect on the control performance.     

Dynamic simulation and control of auto-refrigerated CSTR and tubular reactor for bulk styrene polymerization

Dynamic simulation and control of a two-stage continuous bulk styrene polymerization process is developed to predict the performance of auto-refrigerated CSTR and tubular reactors. The tubular reactor is subdivided into three temperature-control jacket zones. In this paper temperature control of auto-refrigerated continuous stirred tank reactor and tubular reactor are carried out, simultaneously. Two strategies are proposed for the control of tubular reactor. At the first strategy the controlled variable is jacket temperature and in the second strategy the controlled variable is the reactor temperature at the exit of each section. The set points for polymer grade transition are obtained using optimization of reactors temperatures via genetic algorithm (GA). Simulation results show that both of the control strategies are successful but second strategy has better performance in the control of polymer properties in the presence of disturbance and model mismatch.     

Variable measurement structures for the control of a tubular reactor

The feasibility of the variable measurements structure is investigated within the framework of controlling a tubular chemical reactor. An on-line sequential analysis of the temperature measurements along the length of the reactor, allows a fast and time-adaptive selection of the best measurements to be used in a low order, simple and robust control scheme. The approach has been developed for both static and dynamic cases. It is based on a recursive computation of the state estimate errors. Its theoretical and computational simplicity makes it attractive for on-line implementation. The procedure has been applied for the adaptive tubular reactor under pseudo-steady state and dynamic conditions with very encouraging results.     

精馏塔性能参数的自动测定和自动控制

通过对精馏塔实验的研究，将计算机应用精馏塔中，实现了精馏塔性能参数的自动剩定和自动控制。     

高粘搅拌聚合反应装置

评述了高粘搅拌混合技术在聚合反应工程领域应用的新进展,分析了宽粘度域搅拌叶轮,卧式自清洁搅拌机构和立式搅拌釜等一系列用于处理高粘液体搅拌混合装置的特点和应用,指出聚合装置的研究开发有助于聚合反应工程的发展,大的有效反应体积,具有自清洁特性的高效高粘流体混合装置是研究开发的方向。     

4万t/a PVC悬浮聚合生产过程自动控制

介绍了锦化化工 (集团 )有限责任公司 4万t/aPVC悬浮聚合生产装置 ,采用Fisher集散过程控制系统—PROVOXDCS系统进行生产工艺流程控制与控制系统资源管理。优秀的控制策略和完善的控制算法可实现PVC生产过程的批次操作、配方调整、数据监测与信息通讯。PROVOXDCS系统的可靠运行为PVC聚合装置大通量、高负荷生产提供了先进的控制手段和必要保证。     

Application of experimental non-linear control based on generic algorithm to a polymerization reactor

The dynamics of free radical polymerization of styrene and on-line control of temperature in a cooling jacketed batch polymerization reactor is investigated. The benzoyl peroxide initiator is introduced into the reactor once at the beginning of the reaction to obtain the desired monomer conversion and the desired average chain length in a minimum reaction time. The optimal constant set temperature, which is generally realized in industrial applications, and the set profile are used as two different optimal operating conditions. The temperature control of the polymerization reactor is achieved experimentally and theoretically. The control of nonlinear systems has progressed considerably, and various nonlinear process model based control techniques have appeared in the literature. The problem is how to tune the controller in order to obtain comparable closed loop responses. Generic model control (GMC) is applied and the performance of the control results are compared with the previously published control results.     

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.     

Multirate multivariable generalized predictive control and its application to a slurry reactor for ethylene polymerization

This study presents closed-loop results regarding the production of high-density polyethylene with Ziegler-Natta and Phillips catalysis. The multivariable control algorithm based on the generalized predictive control approach is adopted. Additional features are employed to consider multiple sampling rates and desired trajectory for the output constraints in the cases of grade transition. Results show a significant improvement in the output profiles such as melt index and density. This work provides an extension in the predictive control practice applied to polymerization reactors and presents a new approach for the generalized predictive control algorithm capable to control outputs measured at different rates.     

On-line measurement and control of penicillin V production in a tower loop reactor

Penicillin V was produced in a 98-dm³ tower loop reactor using a production strain of Penicillium chrysogenum in pellet form. By using control devices, the aeration, the only energy input in a tower loop reactor, decreased by an average of 75%. The amounts of precursor substance (phenoxyacetic acid), acid, base, ammonium sulfate and urea, added during the penicillin fermentation process, were reduced by applying an automatic analysing system to the process.