System for on line inference of physical and chemical properties and system for on line

• US 6,718,234 B1
• Filed: 12/04/2001
• Issued: 04/06/2004
• Est. Priority Date: 10/08/1998
• Status: Expired due to Term

• Current Assignee: Braskem SA
• Original Assignee: Braskem SA
• Inventors: Axelrud, Celso, De Oliveira, Autur Toledo Martins, Demoro, Esdras Piraguacy
• Primary Examiner(s): Soderquist, Arlen
• Assistant Examiner(s): GAKH, YELENA G
• Application Number:
  US09/806,933
• Time in Patent Office: 854 Days
• Field of Search: 700/269, 700/29-34
• US Class Current: 700/269
• CPC Class Codes: B01J 19/0033 Optimalisation processes, i.e. processes with adaptive control systems adaptive control systems per se G05B13/00
• CPC Class Codes: C08F 110/06 Propene
• CPC Class Codes: C08F 2/00 Processes of polymerisation
• CPC Class Codes: C08F 2400/02 Control or adjustment of polymerization parameters
• CPC Class Codes: G05B 17/02 electric
• CPC Class Codes: G05B 23/0297 Reconfiguration of monitoring system, e.g. use of virtual sensors; change monitoring method as a response to monitoring results

Abstract

A system for on line inference and control of physical and chemical properties of polypropylene and its copolymers is described. The system comprises models for the inference of physical and chemical properties that are not continuously measured and relevant models to control these properties as well as production rate, density of the reaction medium and other process variables of interest. The described control system allows to maximize production rate as well as catalyst yield in the producing process.

Claims

1. A method for on line control of a polymerization plant, that uses a multivariable non linear constrained model predictive control algorithm and inferred values for polymer properties which measurements are not continuously available, said inferred values being calculated by mathematical models of the process and periodically corrected by laboratory tests which use polymer samples collected from the production line, said method being directed to control the production of polypropylene and its copolymers in a plant comprising at least one loop reactor and, optionally, one or more gas-phase reactors disposed in a serial conformation with the loop reactor(s) preceding the gas-phase reactor(s), said method using preferably but not exclusively three layer feed-forward neural networks as process models, the method comprising:

simultaneous calculation by the multivariable non linear constrained model predictive control algorithm of the sequence of adjustments to be effected on a set of manipulated variables (1) comprising;

the ratio of cocatalyst flow rate to electron donor flow rate;

the hydrogen concentration in the feed stream of each loop reactor;

the flow rate of the catalyst fed to the reactor arrangement;

the flow rate of propylene fed to the loop reactor(s); and

the flow rate of comonomer(s) fed to the loop reactor(s); and

in case one or more gas-phase reactors are used;

the ratio of hydrogen concentration to comonomer(s) concentration within gas-phase reactors;

the ratio of each comonomer concentration to the sum of propylene concentration and comonomer(s) concentration within each gas-phase reactor; and

the flow rate of each comonomer fed to each gas-phase reactor,

so as to bring the values of a set of controlled variables (8) close to the set points established for these variables, said set of controlled variables comprising

the production rate of the arrangement of loop reactors;

the production rate of each loop reactor,

the ratio between the production rate of each loop reactor and the production rate of the arrangement of loop reactors;

the density of the reaction medium within loop reactors;

the melt flow index of the polymer produced in the arrangement of loop reactors;

the melt flow index of the polymer produced in each loop reactor, and

the percentage(s) of comonomer(s) incorporated in polymer in the arrangement of loop reactors;

and in case one or more gas-phase reactors are used;

the melt flow index of the polymer produced in the arrangement of loop and gas-phase reactors;

the percentage(s) of comonomer(s) incorporated in polymer in each loop reactor;

the percentage(s) of comonomer(s) incorporated in the polymer produced in the arrangement of loop and gas-phase reactors;

the percentage(s) of comonomer(s) incorporated in the fraction of the polymer produced in gas-phase reactors; and

the intrinsic viscosity of the polymer;

without violating the rate of change (ROC) limits imposed on manipulated variables (1) and the limits imposed for a set of constrained controlled variables (6) comprising;

the power of the pump that promotes the circulation of the reaction medium within each loop reactor;

the opening of the valve that controls the temperature of each loop reactor, and

the difference between the reactor temperature and the bubble point of the liquid within each loop reactor,

and in case one or more gas-phase reactors are used;

the pressure of each gas-phase reactor; and

the opening of the valve that controls the temperature of each gas-phase reactor,

taking into consideration the following variables as disturbances (7);

density of the reaction medium within the loop reactor(s);

the temperature of loop reactor(s); and

the production rates of loop reactor(s);

and in case one or more gas-phase reactors are used;

the bed level in the gas-phase reactor(s);

the flow rate of the stream that returns from the cormonomer/propylene separation tower; and

on-line calculation of inferred values for a set of variables comprising;

the melt flow index of the polymer produced in loop reactors;

the percentage(s) of comonomer(s) incorporated in polymer in loop reactors; and

the percentage of xylene-soluble matter; and

in case one or more gas-phase reactors are used;

the melt flow index of the polymer produced in the arrangement of loop and gas-phase reactors;

the percentage(s) of comonomer(s) incorporated in the polymer produced in the arrangement of loop and gas-phase reactors;

the percentage(s) of comonomer(s) incorporated in the fraction of the polymer produced in gas-phase reactors;

the intrinsic viscosity of the polymer; and

the percentage of xylene-soluble matter.

2. The method according to claim 1, wherein the relationships among measured process inputs (1,2) and outputs (4,5,6) are described by a control matrix comprising the following models:

model for flow index of polypropylene and its copolymers produced in loop reactors using the following input variables;

the hydrogen concentration in the feed stream(s) of the reactor(s);

the flow rate of catalyst fed to the reactor(s);

the flow rate of propylene fed to the reactor(s);

the flow rate of comonomer(s) fed to the reactor(s);

the ratio of flow rate of cocatalyst to electron donor flow rate; and

the temperature of the reactor(s);

model for flow index of polypropylene and its copolymers produced in gas-phase reactors using the following input variables;

the hydrogen concentration in the feed stream(s) of the loop reactor(s) preceding the gas phase reactor;

flow of comonomer(s) fed to gas-phase reactor;

the flow rate of catalyst fed to the reactor(s); and

the temperature of the reactor(s);

model for intrinsic viscosity of polypropylene and its copolymers using the following input variables;

the ratio of hydrogen concentration to comonomer(s) concentration inside the gas-phase reactor as input variable;

model for percentage(s) of comonomer(s) incorporated in the polymer produced in loop reactors using the following input variables;

flow of comonomer(s) fed to the reactor;

production rate of the reactor;

flow of comonomer(s) fed to the preceding reactor(s); and

production rate of the preceding reactor(s);

model for production rate of loop reactors using the following input variables;

the ratio of electron donor flow rate to cocatalyst flow rate;

the hydrogen concentration in feed stream(s) of loop reactor(s);

the flow rate of catalyst fed to loop reactor(s);

the flow rate of propylene fed to loop reactor(s);

the flow rate comonomer(s) fed to loop reactor(s); and

the temperature of the loop reactor(s);

model for the opening of the temperature control valve of loop reactors using the following input variables;

the ratio of flow rate of electron donor to flow rate of cocatalyst that comprise catalytic system;

the hydrogen concentration in feed stream(s) of loop reactor(s) and gas-phase reactor(s);

the flow rate of catalyst fed to loop reactor(s);

the flow rate of propylene fed to loop reactor(s);

.

the flow rate comonomer(s) fed to loop reactor(s); and

the temperature of loop reactor(s);

model for density of reaction medium within loop reactors using the following input variables;

the flow rate of monomer fed to loop reactor;

the production rate of the loop reactor; and

the density of reaction medium of the preceding loop reactor;

model for the power of the recirculation pump of loop reactors using the following input variables;

the flow rate of Monomer fed to loop reactor;

the production rate of the loop reactor, and

the density of reaction medium of the preceding loop reactor;

model for the difference between the temperature and the bubble point of the liquid within loop reactors using the following input variables;

the hydrogen concentration in feed stream(s) of loop reactor(s) and gas-phase reactor(s);

the flow rate of propylene fed to loop reactor(s);

the flow rate comonomer(s) fed to loop reactor(s);

the temperature of the loop reactor; and

the production rate of the loop reactor(s)

model for the ratio between the production rates of two consecutive loop reactors using the following input variables;

the ratio of flow rate of electron donor to flow rate of cocatalyst that comprise catalytic system;

the hydrogen concentration in feed stream(s) of loop reactor(s) and gas-phase reactor(s);

the flow rate of catalyst fed to loop reactor(s);

the flow rate propylene fed to loop reactor(s);

the flow rate comonomer(s) fed to loop reactor(s); and

the temperature of loop reactor(s);

model for the percentage(s) of comonomer(s) incorporated in the polymer produced in gas-phase reactors using the following input variables;

the hydrogen concentration in the feed stream(s) of the loop reactor(s) preceding the gas phase reactor;

flow of comonomer(s) fed to gas-phase reactor;

the flow rate of catalyst fed to the reactor(s); and

the temperature of the reactor(s);

model for the percentage(s) of comonomner(s) incorporated in bipolymer using the following input variables;

the ratio of the concentration of a given comonomer to the sum of comonomer(s) concentration and propylene concentration inside a gas-phase reactor,

model for the pressure of gas phase reactors using the following input variables;

the flow rate of catalyst fed to the reactor(s);

the density of reaction medium of the loop reactor(s);

the flow rate comonomer(s) fed to the gas phase reactor;

the gas-phase reactor bed level; and

the flow rate of gas returning from separation tower;

model for the opening of the temperature control valve of gas phase reactors using the following input variables;

the flow rate of catalyst fed to the reactor(s);

the density of reaction medium of the loop reactor(s);

the flow rate comonomer(s) fed to the gas phase reactor; and

the gas-phase reactor bed level.

3. The method according to claim 1, wherein the mathematical model for inference of the melt flow index of the polymer produced in loop reactors involves the following input variables:

the hydrogen concentration in the feed stream(s) of the reactor(s);

the flow rate of catalyst fed to the reactor(s);

the flow rate of propylene fed to the reactor(s);

the flow rate of comonomer(s) fed to the reactor(s);

the ratio of flow rate of cocatalyst to electron donor flow rate; and

the reactor(s) temperature.

4. The method according to claim 1 or 2, wherein the mathematical model for inference of the melt flow index of the polymer produced in gas-phase reactors involves the following input variables;

the hydrogen concentration in the feed stream(s) of the loop reactor(s) preceding the gas phase reactor;

flow of comonomer(s) fed to gas-phase reactor;

production rate of gas phase reactor, and

production rate of the reactor(s) preceding the gas phase reactor.

5. The method according to claim 1 or 2, wherein the mathematical model for inference of the intrinsic viscosity of polypropylene and its copolymers involves the ratio of hydrogen concentration to comonomer(s) concentration within the gas-phase reactor as input variable.

6. The method according to claim 1 or 2, wherein the mathematical model for inference of the percentage of xylene-soluble matter in the polymer produced in loop reactors involves the following input variables:

the flow rate of the comonomer(s) fed to the reactor(s);

the ratio of flow rate of cocatalyst to flow rate of electron donor;

the reactor(s) temperature; and

the density of reaction medium within the reactor(s).

7. The method according to claim 1 and 2, wherein the mathematical model for inference of the percentage of xylene-soluble matter in the polymer produced in gas-phase reactors involves the following input variables:

the percentage of xylene-soluble matter of the polymer fed to the gas-phase reactor(s);

the percentage of comonomer(s) in xylene-soluble matter of polymer, and

the percentage of comonomer(s) in polymer.

9. The method according to claim 1 or 2, wherein the mathematical model(s) for inference of percentage(s) of comonomer(s) incorporated in the polymer produced gas-phase reactors involves(involve) the following input variables:

flow of comonomer(s) fed to gas-phase reactor,

production rate of said gas phase reactor, and

production rate of the reactor(s) preceding the gas phase reactor.

10. The method according to claim 1 or 2, wherein the mathematical model(s) for inference of percentage(s) of comonomer(s) incorporated in bipolymer uses(use) the ratio of the concentration of a given comonomer to the sum of comonomer(s) concentration and propylene concentration within the gas-phase reactor(s) as input variable.

11. The method according claim 1, wherein the mathematical models may be empirical or rigorous or a combination of rigorous and empirical models.

12. A process for the production of polypropylene and its copolymers, wherein the propylene is polymerized in a plant comprising at least one loop reactor and optionally, one or more gas-phase reactors disposed in a serial conformation with the loop reactor(s) preceding the gas-phase reactor(s), in polymerization conditions, in the presence of hydrogen, a Ziegler-Natta catalyst and, optionally, one or more olefin comonomers including ethylene;

1-butene;

2-methyl propylene;

1-pentene;

1-hexene;

1-heptene;

1-octene;

1-decene;

3-methyl 1-butene;

4-methyl 1-pentene, and cyclopentene, wherein the polymerizaton process is controlled by the method of claim 1.

8. The method, according to claim l or 2, wherein the mathematical model(s) for inference of percentage(s) of comonomer(s) incorporated in the polymer produced in loop reactors involves(involve) the following input variables:

the flow of comonomer(s) fed to the reactor;

the production rate of the reactor;

the flow of comonomer(s) fed to the preceding reactor(s); and

the production rate of the preceding reactor(s).