CONTROL OF A CONTINUOUS POLYMERIZATION REACTOR BY WIENER INPUT/OUTPUT DATA-BASED PREDICTIVE CONTROLLER WITH DIRECT INVERSE IDENTIFICATION

This article reports an experimental study for the identification and predictive control of a continuous methyl methacrylate (MMA) solution polymerization reactor. The Wiener model was introduced to identify the polymerization reactor in a more efficient manner than the conventional methods of Wiener model identification. In particular, the method of subspace identification was employed and the inverse of the nonlinear part was directly identified. The input variables in this work were the jacket inlet temperature and the feed flow rate, while the monomer conversion and the weight average molecular weight were selected as the output variables. On the basis of the identified model a Wiener-type input/output data-based predictive controller was designed and applied to the property control of polymer product in the continuous MMA polymerization reactor by conducting an on-line digital control experiment with online densitometer and viscometer. Despite the complex and nonlinear characteristics of the polymerization reactor, the proposed controller was found to perform satisfactorily for property control in the multiple-input multiple-output system with input constraints for both set-point tracking and disturbance rejection. This was also confirmed by simulation results.     

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.     

APPLICATION OF ADAPTIVE PID CONTROL WITH GENETIC ALGORITHM TO A POLYMERIZATION REACTOR

This article describes the application of adaptive PID control with genetic algorithm (GA) to a jacketed batch polymerization reactor. This method was used to keep the polymerization reactor temperature at the desired optimal path, which was determined by the Hamiltonian maximum principle method. The reactor was simulated and the model equations of this jacketed polymerization reactor were solved by means of Runge-Kutta-Felthberg methods. A genetic algorithm can be a good solution for finding the optimum PID parameters because unlike other techniques it does not impose many limitations and it is simple. In this research, suitability of these parameters was checked by the integral absolute error (IAE) criterion. The control parameters in the PID algorithm were changed with time during the control of a polymerization reactor. It was seen that the genetic algorithm was able to tune the PID controller used in this system in terms of higher robustness and reliability by changing the parameters continuously.     

EXPERIMENTAL APPLICATION OF GENERALIZED PREDICTIVE CONTROL OF THE TEMPERATURE IN A POLYSTRENE POLYMERIZATION REACTOR

The performance of generalized predictive control (GPC) was examined and compared with conventional control applied to the temperature of as free radical solution polymerization of styrene in a jacketed batch reactor. Optimal conditions were obtained at different initiator concentrations by applying Lagrange's multiplier to the relevant polymerization reactor. The use of the polynomial ARIMAX model related with reactor temperature and heat input was emphasized. Model parameters were determined using the Kalman algorithm. A pseudo random binary sequence (PRBS) signal was employed in order to operate the system. The GPC control method was based on the ARIMAX model. The performance criteria of GPC in evaluating the temperature control results were the required monomer conversion and molecular weight.     

ADAPTIVE POLE-PLACEMENT CONTROL OF A CONTINUOUS POLYMERIZATION REACTOR

A simulation of the polymerization of methylmethacrylate in a CSTR is adaptively controlled by two types of pole-placement algorithms. The strongly nonlinear polymerization process, exhibiting multiple steady states, presents difficult control problems for conventional feedback controllers. The performance of an adaptive explicit SISO controller and that of an adaptive implicit multivariable controller are compared and evaluated as applied to this process. The plant is identified by a recursive least squares estimator. Modifications made to the estimation algorithm help to maintain adequate closed-loop results. A simple warm-up procedure is introduced that successfully initializes the controller and estimator during plant start-up. Good servo and regulatory control are achieved by both pole-placement schemes.     

GLOBAL STABILIZATION OF A BIOLOGICAL REACTOR BY LINEAR FEEDBACK CONTROL

A classical substrate inhibition model for biological reactors with PI controllers is subjected to a rigorous nonlinear analysis. The operating conditions and control settings that ensure global stability of the set-point are derived from bifurcation studies of the solution branches with the controller gains as the bifurcation parameters. The global stability of the set-point can be destroyed by co-existing extraneous attracting states, both steady and time-dependent, which may be introduced by the controllers that are designed to stabilize the set-point locally.     

GLOBAL STABILIZATION OF A BIOLOGICAL REACTOR BY LINEAR FEEDBACK CONTROL

A classical substrate inhibition model for biological reactors with PI controllers is subjected to a rigorous nonlinear analysis. The operating conditions and control settings that ensure global stability of the set-point are derived from bifurcation studies of the solution branches with the controller gains as the bifurcation parameters. The global stability of the set-point can be destroyed by co-existing extraneous attracting states, both steady and time-dependent, which may be introduced by the controllers that are designed to stabilize the set-point locally.     

ROBUSTNESS ANALYSIS OF EXPONENTIAL TRACKING WITH DISTURBANCE ATTENUATION BY OUTPUT FEEDBACK (ETDAOF) WITH TIME DELAY IN THE PROCESS INPUT

This article considers exponential tracking with disturbance attenuation by output feedback (ETDAOF) control for systems with time delay in the process input. It is shown that the stability of such systems can be analyzed through a small-gain theorem. This robust stability analysis method is helpful in making decisions in controller synthesis. The analysis method is used to synthesize an ETDAOF controller for a highly nonlinear pH neutralization process. Simulation results are presented.     

OPTIMIZATION OF THE OPERATION IN A REACTOR WITH CONTINUOUS CATALYST CIRCULATION IN THE GASEOUS BENZYL ALCOHOL POLYMERIZATION

Polymerization of gaseous benzyl alcohol was studied on a commercial zeolite (MZ-7P supplied by Akzo-Chemie) in a jet spouted bed reactor which is an original gas-solid contact technique whose use in this type of processes has not yet been described in relevant literature.

Properties of the catalyst-particles-bed and polymer production are calculated by a simulation routine as a function of the following operating variables: the partial pressure of the benzyl alcohol fed into the reactor and the average residence time of the catalyst particles in the reactor. The simulation method and the kinetic equations used have been checked by experimental data.

An analysis of the effect or the operating conditions is carried out, thus determining the values which enable maximum production.     

PROCESS AUTOMATION USING COMBINATIONS OF PROCESS AND MACHINE CONTROL TECHNOLOGIES WITH APPLICATION TO A CONTINUOUS DISSOLVER

Operation of a continuous rotary dissolver, designed to leach uranium-plutonium fuel from chopped sections of reactor fuel cladding using nitric acid, has been automated. The dissolver is a partly continuous, partly batch process that interfaces at both ends with batchwise processes, thereby requiring synchronization of certain operations. Liquid acid is fed and flows through the dissolver continuously, whereas chopped fuel elements are fed to the dissolver in small batches and move through the compartments of the dissolver stagewise. Sequential logic (or machine control) techniques are used to control discrete activities such as the sequencing of isolation valves. Feedback control is used to control acid flowrates and temperatures. Expert systems technology is used for on-line material balances and diagnostics of process operation.     

MODELING OF THE TRANSIENT AND STEADY STATE OPERATION OF A FLUIDIZED BED REACTOR WITH ADAPTIVE CONTROL OF TEMPERATURE

This paper concerns modeling of the transient and the steady state operation of a fluidized bed reactor for the catalytic ammoxidation of propylene to acrylonitrile. To maintain constant the temperature of the reaction in order to facilitate the phenomenological study as well as to avoid risks of destruction of the catalyst, a self tuning P.I.D. controller has been used. The controller derived from a discrete P.I.D. regulator is based on pole assignment. It uses a recursive parameter estimator based on the least square method. The reactor has been interfaced with an Apple II micro-computer. The results obtained illustrates the inherent capability of self adaptive control to adapt the change of the environment where conventional control fails

Modeling of the reactor is based on the Kato and Wen bubble assemblage model corrected by including the wake of the bubbles with their clouds, as proposed hy Stergiou. This modified model gives good predictions of the operation of the reactor for steady as well as transient operation.     

A PARAMETER PLANE METHOD FOR THE PID CONTROL OF A MULTIRATE, SAMPLED-DATA CHEMICAL REACTOR SYSTEM WITH A TRANSPORTATION LAG

The control of a multirate sampled-data, stirred-tank chemical reactor system using a parameter plane method is considered. Due to wide acceptance of proportional-plus-integral-plus-derivative (PID) control in the chemical process industries, a PID controller with a “slow-fast”multirate scheme is used for the chemical reactor system. Based on two related stability equations and using the PID gains as the adjustable parameters, the set of all possible PID gains to maintain the chemical reactor system's stability, and at the same time, to make the system having a specified gain margin, phase margin, damping ratio, and damping factor is determined. The effects of changing the integer N (which is the ratio of the sampling rates between a slow- and a fasl-samplcr)and (he basic sampling period Ton the set of PID gains satisfying the specifications are examined. The results for single-rate and multirate cases are also studied.