基于UKF算法的双酚a缩合React建模。
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ScienceDirect
IFAC-PapersOnLine 48-8 (2015) 827–830
ScienceDirect
Available online at www.sciencedirect.com
2405-8963 © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
Peer review under responsibility of International Federation of Automatic Control.
10.1016/j.ifacol.2015.09.071
Wentao Cang et al. / IFAC-PapersOnLine 48-8 (2015) 827–830
©
2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
Modeling of Bisphenol A Condensation Reaction
based on UKF Algorithm
Wentao Cang, Li Xie, Huizhong Yang
Key Laboratory of Advanced Process Control for Light Industry
(Ministry of Education), Jiangnan University, Wuxi 214122, PR
China (yhz_jn@163.com)
Abstract: The Bisphenol A concentration at the reactor outlet is a direct response to the production
quality index, and online soft measurement of Bisphenol A concentration is very necessary. Based on the
mechanism of Bisphenol A condensation process, the mechanism equations describing the dynamic
behavior of reactor are established, and the state equation and observation equation of Bisphenol A are
derived through simplification and derivation of the soft measurement model, and then an Unscented
Kalman Filtering is adopted to estimate the Bisphenol A concentration. Simulation results confirm that
the method is feasible and effective.
Keywords: Unscented Kalman Filtering; Condensation Reaction; Soft Sensor; Mechanism Model;
Bisphenol A
1. INTRODUCTION
Bisphenol A (BPA), an important common monomer for
production of many polymers such as polycarbonate and
epoxy resins, is manufactured by acid catalyzed condensation
of acetone and phenol. Industrial processes for BPA
production usually use fixed-bed reactors filled with strong
acid ion exchange resins as catalysts
[1]
. BPA synthesis
kinetics has been widely studied and reported in recent years.
Various BPA synthesis kinetics models have differences
because of the complexities of BPA synthesis. For example,
Chen Liangcheng
[2]
et al. proposed reaction kinetics of BPA
synthesis with strong acid conditions. Rahimi
[3]
studied
kinetics of BPA synthesis by condensation reaction. Bao-he
Wang
[4]
proposed reaction kinetics of BPA synthesis with
cyst amine modified resin catalyst. This paper focuses on soft
sensor development for online prediction of the BPA
concentration, which has important practical significance.
In a BPA reaction process, the BPA concentration at the
reactor outlet is the most important index, which directly
determines the production efficiency. However, the real-time
BPA concentration cannot be measured online in majority of
industrial fields. In order to solve this problem, this paper
establishes a nonlinear state-space model for the estimation
of BPA concentration by taking the temperature distribution
in the reactor and the acetone concentration at the reactor
inlet as the observation variables. Hence, the BPA synthesis
can be described by a nonlinear distributed parameter model.
As a nonlinear estimation method, the extended Kalman filter
(EKF) is widely used in state estimation. But the EKF has
some deficiencies, including the requirement of
differentiability of the state dynamics as well as susceptibility
to bias and divergence in the state estimates. On the contrary,
the unscented Kalman filter (UKF) can improve the effect of
nonlinear system filtering by approximating the probability
distribution of the nonlinear functions and the posterior
probability density of state based on a series of deterministic
samples
[5-9]
, and the UKF can use nonlinear model directly
instead of linearizing. In this paper, UKF is employed in state
estimation and the simulation results are provided to
demonstrate the effectiveness of the proposed method.
2. DYNAMIC MODEL OF BPA SYNTHESIS
2.1 Observation Equation of BPA Concentration
In industrial production, acetone and phenol are continuously
fed from the top of the reactor. The phenol is excessive in
order to improve the conversion rate of acetone and
reduce side reaction. The main reaction formula is
[10]
:
0
1
12
() ( )
k
k
A BH PH
where
A
,
B
,
P
denote acetone, BPA and by-product 2-
4’BPA, respectively. The dynamic characteristics of the
reaction process can be written as
[11]
:
Material balance equation:
1
(, )
A
C tz
uR
z
(1)
22
(, )
B
C tz
u RR
z
(2)
Energy balance equation:
2
1
(, ) (, )
c
S PS p i i c pc c
i
T
Ttz Ttz
C C u HR C u
tz z
(3)
where
/
10
E RT
A
R ke C
,
/
20
E RT
A
R ke C
,
/
21
E RT
B
R ke C
.
z
is the axial length of the reactor and
zL
. In the industrial
9th International Symposium on Advanced Control of Chemical Processes
June 7-10, 2015. Whistler, British Columbia, Canada
Copyright © 2015 IFAC 828
Modeling of Bisphenol A Condensation Reaction
based on UKF Algorithm
Wentao Cang, Li Xie, Huizhong Yang
Key Laboratory of Advanced Process Control for Light Industry
(Ministry of Education), Jiangnan University, Wuxi 214122, PR
China (yhz_jn@163.com)
Abstract: The Bisphenol A concentration at the reactor outlet is a direct response to the production
quality index, and online soft measurement of Bisphenol A concentration is very necessary. Based on the
mechanism of Bisphenol A condensation process, the mechanism equations describing the dynamic
behavior of reactor are established, and the state equation and observation equation of Bisphenol A are
derived through simplification and derivation of the soft measurement model, and then an Unscented
Kalman Filtering is adopted to estimate the Bisphenol A concentration. Simulation results confirm that
the method is feasible and effective.
Keywords: Unscented Kalman Filtering; Condensation Reaction; Soft Sensor; Mechanism Model;
Bisphenol A
1. INTRODUCTION
Bisphenol A (BPA), an important common monomer for
production of many polymers such as polycarbonate and
epoxy resins, is manufactured by acid catalyzed condensation
of acetone and phenol. Industrial processes for BPA
production usually use fixed-bed reactors filled with strong
acid ion exchange resins as catalysts
[1]
. BPA synthesis
kinetics has been widely studied and reported in recent years.
Various BPA synthesis kinetics models have differences
because of the complexities of BPA synthesis. For example,
Chen Liangcheng
[2]
et al. proposed reaction kinetics of BPA
synthesis with strong acid conditions. Rahimi
[3]
studied
kinetics of BPA synthesis by condensation reaction. Bao-he
Wang
[4]
proposed reaction kinetics of BPA synthesis with
cyst amine modified resin catalyst. This paper focuses on soft
sensor development for online prediction of the BPA
concentration, which has important practical significance.
In a BPA reaction process, the BPA concentration at the
reactor outlet is the most important index, which directly
determines the production efficiency. However, the real-time
BPA concentration cannot be measured online in majority of
industrial fields. In order to solve this problem, this paper
establishes a nonlinear state-space model for the estimation
of BPA concentration by taking the temperature distribution
in the reactor and the acetone concentration at the reactor
inlet as the observation variables. Hence, the BPA synthesis
can be described by a nonlinear distributed parameter model.
As a nonlinear estimation method, the extended Kalman filter
(EKF) is widely used in state estimation. But the EKF has
some deficiencies, including the requirement of
differentiability of the state dynamics as well as susceptibility
to bias and divergence in the state estimates. On the contrary,
the unscented Kalman filter (UKF) can improve the effect of
nonlinear system filtering by approximating the probability
distribution of the nonlinear functions and the posterior
probability density of state based on a series of deterministic
samples
[5-9]
, and the UKF can use nonlinear model directly
instead of linearizing. In this paper, UKF is employed in state
estimation and the simulation results are provided to
demonstrate the effectiveness of the proposed method.
2. DYNAMIC MODEL OF BPA SYNTHESIS
2.1 Observation Equation of BPA Concentration
In industrial production, acetone and phenol are continuously
fed from the top of the reactor. The phenol is excessive in
order to improve the conversion rate of acetone and
reduce side reaction. The main reaction formula is
[10]
:
0
1
12
() ( )
k
k
A BH PH
where
A
,
B
,
P
denote acetone, BPA and by-product 2-
4’BPA, respectively. The dynamic characteristics of the
reaction process can be written as
[11]
:
Material balance equation:
1
(, )
A
C tz
uR
z
(1)
22
(, )
B
C tz
u RR
z
(2)
Energy balance equation:
2
1
(, ) (, )
c
S PS p i i c pc c
i
T
Ttz Ttz
C C u HR C u
tz z
(3)
where
/
10
E RT
A
R ke C
,
/
20
E RT
A
R ke C
,
/
21
E RT
B
R ke C
.
z
is the axial length of the reactor and
zL
. In the industrial
9th International Symposium on Advanced Control of Chemical Processes
June 7-10, 2015. Whistler, British Columbia, Canada
Copyright © 2015 IFAC 828
Modeling of Bisphenol A Condensation Reaction
based on UKF Algorithm
Wentao Cang, Li Xie, Huizhong Yang
Key Laboratory of Advanced Process Control for Light Industry
(Ministry of Education), Jiangnan University, Wuxi 214122, PR
China (yhz_jn@163.com)
Abstract: The Bisphenol A concentration at the reactor outlet is a direct response to the production
quality index, and online soft measurement of Bisphenol A concentration is very necessary. Based on the
mechanism of Bisphenol A condensation process, the mechanism equations describing the dynamic
behavior of reactor are established, and the state equation and observation equation of Bisphenol A are
derived through simplification and derivation of the soft measurement model, and then an Unscented
Kalman Filtering is adopted to estimate the Bisphenol A concentration. Simulation results confirm that
the method is feasible and effective.
Keywords: Unscented Kalman Filtering; Condensation Reaction; Soft Sensor; Mechanism Model;
Bisphenol A
1. INTRODUCTION
Bisphenol A (BPA), an important common monomer for
production of many polymers such as polycarbonate and
epoxy resins, is manufactured by acid catalyzed condensation
of acetone and phenol. Industrial processes for BPA
production usually use fixed-bed reactors filled with strong
acid ion exchange resins as catalysts
[1]
. BPA synthesis
kinetics has been widely studied and reported in recent years.
Various BPA synthesis kinetics models have differences
because of the complexities of BPA synthesis. For example,
Chen Liangcheng
[2]
et al. proposed reaction kinetics of BPA
synthesis with strong acid conditions. Rahimi
[3]
studied
kinetics of BPA synthesis by condensation reaction. Bao-he
Wang
[4]
proposed reaction kinetics of BPA synthesis with
cyst amine modified resin catalyst. This paper focuses on soft
sensor development for online prediction of the BPA
concentration, which has important practical significance.
In a BPA reaction process, the BPA concentration at the
reactor outlet is the most important index, which directly
determines the production efficiency. However, the real-time
BPA concentration cannot be measured online in majority of
industrial fields. In order to solve this problem, this paper
establishes a nonlinear state-space model for the estimation
of BPA concentration by taking the temperature distribution
in the reactor and the acetone concentration at the reactor
inlet as the observation variables. Hence, the BPA synthesis
can be described by a nonlinear distributed parameter model.
As a nonlinear estimation method, the extended Kalman filter
(EKF) is widely used in state estimation. But the EKF has
some deficiencies, including the requirement of
differentiability of the state dynamics as well as susceptibility
to bias and divergence in the state estimates. On the contrary,
the unscented Kalman filter (UKF) can improve the effect of
nonlinear system filtering by approximating the probability
distribution of the nonlinear functions and the posterior
probability density of state based on a series of deterministic
samples
[5-9]
, and the UKF can use nonlinear model directly
instead of linearizing. In this paper, UKF is employed in state
estimation and the simulation results are provided to
demonstrate the effectiveness of the proposed method.
2. DYNAMIC MODEL OF BPA SYNTHESIS
2.1 Observation Equation of BPA Concentration
In industrial production, acetone and phenol are continuously
fed from the top of the reactor. The phenol is excessive in
order to improve the conversion rate of acetone and
reduce side reaction. The main reaction formula is
[10]
:
0
1
12
() ( )
k
k
A BH PH
where
A
,
B
,
P
denote acetone, BPA and by-product 2-
4’BPA, respectively. The dynamic characteristics of the
reaction process can be written as
[11]
:
Material balance equation:
1
(, )
A
C tz
uR
z
(1)
22
(, )
B
C tz
u RR
z
(2)
Energy balance equation:
2
1
(, ) (, )
c
S PS p i i c pc c
i
T
Ttz Ttz
C C u HR C u
tz z
(3)
where
/
10
E RT
A
R ke C
,
/
20
E RT
A
R ke C
,
/
21
E RT
B
R ke C
.
z
is the axial length of the reactor and
zL
. In the industrial
9th International Symposium on Advanced Control of Chemical Processes
June 7-10, 2015. Whistler, British Columbia, Canada
Copyright © 2015 IFAC 828
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