CN103389746B  The waste plastic oilrefining pyrolysis furnace hearth pressure control method that Predictive function control is optimized  Google Patents
The waste plastic oilrefining pyrolysis furnace hearth pressure control method that Predictive function control is optimized Download PDFInfo
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 CN103389746B CN103389746B CN201310310052.4A CN201310310052A CN103389746B CN 103389746 B CN103389746 B CN 103389746B CN 201310310052 A CN201310310052 A CN 201310310052A CN 103389746 B CN103389746 B CN 103389746B
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Abstract
The invention discloses the waste plastic oilrefining pyrolysis furnace hearth pressure control method that a kind of Predictive function control is optimized.First the inventive method sets up the model of furnace pressure object based on the step response data of pyrolysis furnace furnace pressure object, excavate basic plant characteristic; Then to go to adjust according to the characteristic of Predictive function control the parameter of corresponding PI controller; Finally implement PI to pyrolysis furnace furnace pressure object to control.The performance of Predictive function control is assigned to PI and controls by the present invention, effectively improves the performance of traditional control method, also promotes the application of advanced control method simultaneously.
Description
Technical field
The invention belongs to technical field of automation, relate to a kind of waste plastic oilrefining pyrolysis furnace fire box temperature proportional integral (PI) control method optimized based on Predictive function control.
Background technology
In the control of actual industrial object, due to the restriction of the aspects such as hardware, cost, enforcement difficulty, although some advanced control methods obtain application to a certain degree, the PID that is still accounting for main flow at present controls.Oil refining pyrolysis furnace is the important device in petrochemical production process, and wherein furnace pressure has very important impact to cracking process, and furnace pressure is excessive may bring danger, and the too low meeting of furnace pressure causes lysis efficiency stepdown.Because advanced control method application is limited, the usual adoption rate integration (PI) of control of current pyrolysis furnace furnace pressure controls.Predictive function control is as the one of advanced control method, in the control of pyrolysis furnace furnace pressure, compare PI control to have better control performance, if the performance of Predictive function control can be assigned to PI to control, that will advance the application of advanced control method further, also can obtain better Actual Control Effect of Strong simultaneously.
Summary of the invention
The object of the invention is the application weak point for existing advanced control method, provide a kind of pyrolysis furnace furnace pressure PI control method optimized based on Predictive function control, to obtain better working control performance.The method, by controlling in conjunction with Predictive function control and PI, obtains a kind of PI control method with Predictive function control performance.The method also ensures while inheriting Predictive function control premium properties that form is simple and meets the needs of actual industrial process.
First the inventive method sets up the model of furnace pressure object based on the step response data of pyrolysis furnace furnace pressure object, excavate basic plant characteristic; Then to go to adjust according to the characteristic of Predictive function control the parameter of corresponding proportion integral controller; Finally implement PI to pyrolysis furnace furnace pressure object to control.
Technical scheme of the present invention is set up by data acquisition, model, predicted the means such as mechanism, optimization, establishes a kind of PI control method optimized based on Predictive function control, utilize the method effectively can improve precision and the stability of control.
The step of the inventive method comprises:
Step (1). set up the model of controlled device by the realtime step response data of pyrolysis furnace furnace pressure object, concrete grammar is:
A. the pi controller of process is rested on manual operation state, operation driver plate makes it export a Spline smoothing, by the output valve of recorder record real process, by real process output valve y
_{p}k the response curve of () converts Dimensionless Form y to
_{p} ^{*}(k), specifically:
y
_{p} ^{*}(k)＝y
_{p}(k)/y
_{p}(∞)
Wherein, y
_{p}(∞) be that the output of pi controller has real process during Spline smoothing to export y
_{p}the steadystate value of (k).
B. choose and meet y
_{p} ^{*}(k
_{1})=0.39 and y
_{p} ^{*}(k
_{2}two calculation level k of)=0.63
_{1}and k
_{2}, according to the model parameter K of following formula computation process object
_{m}, T and τ:
K
_{m}＝y
_{p}(∞)/q
T
_{m}＝2(k
_{1}k
_{2})
τ＝2k
_{1}k
_{2}
The transport function of the process object finally obtained is:
Wherein, q is the Spline smoothing amplitude that the pi controller of process exports, and G (s) is the transport function of furnace pressure process, and s is Laplace transform operator, K
_{m}for the gain coefficient of furnace pressure process model, T
_{m}for the time constant of furnace pressure process model, τ is parameter retardation time of furnace pressure process model.
Step (2). the pi controller of design process object, concrete grammar is:
A. to the transport function obtained at sampling time T
_{s}under add a zeroorder holder discretize, obtaining discrete model is
y
_{m}(k)＝a
_{m}y
_{m}(k1)+K
_{m}(1a
_{m})u(k1L)
Y
_{m}k process object model prediction that () is the k moment exports,
u (k1L) is the control inputs of the furnace pressure process model in (k1L) moment, and L is the time lag of discrete transfer function model, L=τ/T
_{s}.
B. computation process object removes the P step prediction output of purely retarded later under Predictive function control, and form is as follows:
y
_{mav}(k)＝a
_{m}y
_{mav}(k1)+K
_{m}(1a
_{m})u(k1)
y
_{mav}(k+P)＝a
_{m} ^{P}y
_{mav}(k)+K
_{m}(1a
_{m} ^{P})u(k)
Wherein, P is prediction step, y
_{mav}(k+P) for the k moment removes the P step prediction output of furnace pressure process model under Predictive function control of purely retarded, y
_{mav}k furnace pressure process model that () removes purely retarded for the k moment exports.
C. the actual output revising current time obtains the new process border output valve comprising future anticipation information, and form is as follows:
y
_{Pav}(k)＝y
_{P}(k)+y
_{mav}(k)y
_{mav}(kL)
Wherein, y
_{pav}k () comprises the new the output of process value of future anticipation information for correcting the k moment obtained, y
_{p}k () is the real output value in k moment.
D. the reference locus y of predictive functional control algorithm is chosen
_{r}(k+P) and objective function J, form is as follows:
y
_{r}(k+P)＝β
^{P}y
_{p}(k)+(1β
^{P})c(k)
J＝min(y
_{r}(k+P)y
_{mav}(k+P)e(k))
^{2}
e(k)＝y
_{pav}(k)y
_{mav}(k)
Wherein, β is reference locus softening coefficient, and c (k) is the setting value in k moment, and e (k) is the error amount of k time correction.
E. solve the parameter in pi controller according to the objective function in steps d, here stack damper aperture controlled quentity controlled variable u (k) of furnace pressure process converted:
u(k)＝u(k1)+K
_{p}(e
_{1}(k)e
_{1}(k1))+K
_{i}e
_{1}(k)
e
_{1}(k)＝βy
_{p}(k1)+(1β)c(k1)y
_{p}(k)
Further abbreviation is:
u(k)＝u(k1)+w(k)
^{Τ}E(k)
w(k)＝[w
_{1}(k),w
_{2}(k)]
^{Τ}
w
_{1}(k)＝K
_{p}+K
_{i},w
_{2}(k)＝K
_{p}
E(k)＝[e
_{1}(k),e
_{1}(k1)]
^{Τ}
Wherein, K
_{p}, K
_{i}be respectively the ratio of pi controller, integral parameter, e
_{1}(k) for the error between k moment reference locus value and real output value, Τ be transpose of a matrix symbol.
In conjunction with abovementioned formula, can be in the hope of:
Can obtain further:
K
_{p}＝w
_{2}(k)
K
_{i}＝w
_{1}(k)K
_{P}
F. the parameter K of pi controller is obtained
_{p}, K
_{i}later formation controlled quentity controlled variable u (k) acts on controlled device, u (k)=u (k1)+K
_{p}(e
_{1}(k)e
_{1}(k1))+K
_{i}e
_{1}(k).
G. at subsequent time, continue to solve the new parameter K of pi controller according to the step in b to f
_{p}, K
_{i}, circulate successively.
The performance of Predictive function control is assigned to PI and controls by a kind of waste plastic oilrefining pyrolysis furnace furnace pressure PI control method based on Predictive function control optimization that the present invention proposes, effectively improve the performance of traditional control method, also promote the application of advanced control method simultaneously.
Embodiment
For the process control of waste plastic oilrefining pyrolysis furnace furnace pressure:
Pyrolysis furnace furnace pressure is the important parameter in pyrolysis furnace cracking process, and regulating measure adopts the aperture of stack damper.
Step (1). set up the model of controlled device by the realtime step response data of pyrolysis furnace furnace pressure object, concrete grammar is:
A. the pi controller of pyrolysis furnace furnace pressure process is rested on manual operation state, operation driver plate makes it export a Spline smoothing, by the real output value of recorder record furnace pressure process, by real output value y
_{p}k the response curve of () converts Dimensionless Form y to
_{p} ^{*}(k), specifically:
y
_{p} ^{*}(k)＝y
_{p}(k)/y
_{p}(∞)
Wherein, y
_{p}(∞) be the output of pi controller furnace pressure the output of process y when having a Spline smoothing
_{p}the steadystate value of (k).
B. choose and meet y
_{p} ^{*}(k
_{1})=0.39 and y
_{p} ^{*}(k
_{2}two calculation level k of)=0.63
_{1}and k
_{2}, the model parameter K of furnace pressure process is calculated according to following formula
_{m}, T and τ:
K
_{m}＝y
_{p}(∞)/q
T
_{m}＝2(k
_{1}k
_{2})
τ＝2k
_{1}k
_{2}
The transport function of the process model finally obtained is:
Wherein, q is the Spline smoothing amplitude that the pi controller of furnace pressure process exports, and G (s) is the transport function of furnace pressure process, and s is Laplace transform operator, K
_{m}for the gain coefficient of furnace pressure process model, T
_{m}for the time constant of furnace pressure process model, τ is parameter retardation time of furnace pressure process model.
Step (2). the pi controller of design furnace pressure process, concrete grammar is:
A. to the transport function of the furnace pressure process model obtained at sampling time T
_{s}under add a zeroorder holder discretize, obtaining discrete model is
y
_{m}(k)＝a
_{m}y
_{m}(k1)+K
_{m}(1a
_{m})u(k1L)
Y
_{m}k furnace pressure process model prediction that () is the k moment exports,
u (k1L) is the control inputs of the furnace pressure process model in (k1L) moment, and L is the time lag of discrete transfer function model, L=τ/T
_{s}.
B. calculate furnace pressure process model and remove the P step prediction output of purely retarded later under Predictive function control, form is as follows:
y
_{mav}(k)＝a
_{m}y
_{mav}(k1)+K
_{m}(1a
_{m})u(k1)
y
_{mav}(k+P)＝a
_{m} ^{P}y
_{mav}(k)+K
_{m}(1a
_{m} ^{P})u(k)
Wherein, P is prediction step, y
_{mav}(k+P) for the k moment removes the P step prediction output of furnace pressure process model under Predictive function control of purely retarded, y
_{mav}k furnace pressure process model that () removes purely retarded for the k moment exports.
C. the furnace pressure process real output value revising current time obtains the new the output of process value comprising future anticipation information, and form is as follows:
y
_{Pav}(k)＝y
_{P}(k)+y
_{mav}(k)y
_{mav}(kL)
Wherein, y
_{pav}k () comprises the new the output of process value of the furnace pressure process of future anticipation information for correcting the k moment obtained, y
_{p}k furnace pressure process real output value that () is the k moment.
D. the reference locus y of predictive functional control algorithm is chosen
_{r}(k+P) and objective function J, form is as follows:
y
_{r}(k+P)＝β
^{P}y
_{p}(k)+(1β
^{P})c(k)
J＝min(y
_{r}(k+P)y
_{mav}(k+P)e(k))
^{2}
e(k)＝y
_{pav}(k)y
_{mav}(k)
Wherein, β is reference locus softening coefficient, the setting value of the furnace pressure process that c (k) is the k moment, and e (k) is the error amount of k time correction.
E. solve the parameter in pi controller according to the objective function in steps d, here stack damper aperture controlled quentity controlled variable u (k) of furnace pressure process converted:
u(k)＝u(k1)+K
_{p}(e
_{1}(k)e
_{1}(k1))+K
_{i}e
_{1}(k)
e
_{1}(k)＝βy
_{p}(k1)+(1β)c(k1)y
_{p}(k)
Further abbreviation is:
u(k)＝u(k1)+w(k)
^{Τ}E(k)
w(k)＝[w
_{1}(k),w
_{2}(k)]
^{Τ}
w
_{1}(k)＝K
_{p}+K
_{i},w
_{2}(k)＝K
_{p}
E(k)＝[e
_{1}(k),e
_{1}(k1)]
^{Τ}
Wherein, K
_{p}, K
_{i}be respectively the ratio of furnace pressure process pi controller, integral parameter, e
_{1}error between k reference locus value that () is k moment furnace pressure process and real output value, Τ is transpose of a matrix symbol.
In conjunction with abovementioned formula, can be in the hope of:
Can obtain further:
K
_{p}＝w
_{2}(k)
K
_{i}＝w
_{1}(k)K
_{P}
F. the parameter K of pi controller is obtained
_{p}, K
_{i}later formation controlled quentity controlled variable u (k) acts on the stack damper aperture valve of pyrolysis furnace burner hearth, u (k)=u (k1)+K
_{p}(e
_{1}(k)e
_{1}(k1))+K
_{i}e
_{1}(k).
G. at subsequent time, continue to solve the new parameter K of pyrolysis furnace furnace pressure process pi controller according to the step in b to f
_{p}, K
_{i}, circulate successively.
Claims (1)
1. the waste plastic oilrefining pyrolysis furnace hearth pressure control method of Predictive function control optimization, is characterized in that the concrete steps of the method are:
Step (1). set up the model of controlled device by the realtime step response data of pyrolysis furnace furnace pressure object, concrete grammar is:
I. the pi controller of pyrolysis furnace furnace pressure process is rested on manual operation state, and operation driver plate makes it export a Spline smoothing, by the real output value of recorder record pyrolysis furnace furnace pressure process, by real output value y
_{p}k the response curve of () converts Dimensionless Form y to
_{p} ^{*}(k), specifically:
y
_{p} ^{*}(k)＝y
_{p}(k)/y
_{p}(∞)
Wherein, y
_{p}(∞) be the real output value y of the output of pi controller pyrolysis furnace furnace pressure process when having a Spline smoothing
_{p}the steadystate value of (k);
II. choose and meet y
_{p} ^{*}(k
_{1})=0.39 and y
_{p} ^{*}(k
_{2}two calculation level k of)=0.63
_{1}and k
_{2}, the model parameter K of pyrolysis furnace furnace pressure process is calculated according to following formula
_{m}, T
_{m}and τ:
K
_{m}＝y
_{p}(∞)/q
T
_{m}＝2(k
_{1}k
_{2})
τ＝2k
_{1}k
_{2}
The transport function of the pyrolysis furnace furnace pressure process finally obtained is:
Wherein, q is the Spline smoothing amplitude that the pi controller of pyrolysis furnace furnace pressure process exports, and G (s) is the transport function of pyrolysis furnace furnace pressure process, and s is Laplace transform operator, K
_{m}for the gain coefficient of pyrolysis furnace furnace pressure process model, T
_{m}for the time constant of pyrolysis furnace furnace pressure process model, τ is parameter retardation time of pyrolysis furnace furnace pressure process model;
Step (2). the pi controller of design pyrolysis furnace furnace pressure process, concrete grammar is:
A. to the transport function obtained at sampling time T
_{s}under add a zeroorder holder discretize, obtaining discrete model is
y
_{m}(k)＝a
_{m}y
_{m}(k1)+K
_{m}(1a
_{m})u(k1L)
Y
_{m}k pyrolysis furnace furnace pressure process model prediction that () is the k moment exports,
u (k1L) is the control inputs of the pyrolysis furnace furnace pressure process model in (k1L) moment, and L is the time lag of discrete transfer function model, L=τ/T
_{s};
B. calculate pyrolysis furnace furnace pressure process model and remove the P step prediction output of purely retarded later under Predictive function control, form is as follows:
y
_{mav}(k)＝a
_{m}y
_{mav}(k1)+K
_{m}(1a
_{m})u(k1)
y
_{mav}(k+P)＝a
_{m} ^{P}y
_{mav}(k)+K
_{m}(1a
_{m} ^{P})u(k)
Wherein, P is prediction step, y
_{mav}(k+P) for the k moment removes the P step prediction output of pyrolysis furnace furnace pressure process model under Predictive function control of purely retarded, y
_{mav}k pyrolysis furnace furnace pressure process model that () removes purely retarded for the k moment exports;
C. the actual output revising current time obtains the new pyrolysis furnace furnace pressure the output of process value comprising future anticipation information, and form is as follows:
y
_{Pav}(k)＝y
_{P}(k)+y
_{mav}(k)y
_{mav}(kL)
Wherein, y
_{pav}k () comprises the new pyrolysis furnace furnace pressure the output of process value of future anticipation information for correcting the k moment obtained, y
_{p}k () is the real output value in k moment;
D. the reference locus y of predictive functional control algorithm is chosen
_{r}(k+P) and objective function J, form is as follows:
y
_{r}(k+P)＝β
^{P}y
_{p}(k)+(1β
^{P})c(k)
J＝min(y
_{r}(k+P)y
_{mav}(k+P)e(k))
^{2}
e(k)＝y
_{pav}(k)y
_{mav}(k)
Wherein, β is reference locus softening coefficient, and c (k) is the setting value in k moment, and e (k) is the error amount of k time correction;
E. solve the parameter in pi controller according to the objective function in steps d, here stack damper aperture controlled quentity controlled variable u (k) of pyrolysis furnace furnace pressure process converted:
u(k)＝u(k1)+K
_{p}(e
_{1}(k)e
_{1}(k1))+K
_{i}e
_{1}(k)
e
_{1}(k)＝βy
_{p}(k1)+(1β)c(k1)y
_{p}(k)
Further abbreviation is:
u(k)＝u(k1)+w(k)
^{Τ}E(k)
w(k)＝[w
_{1}(k),w
_{2}(k)]
^{Τ}
w
_{1}(k)＝K
_{p}+K
_{i},w
_{2}(k)＝K
_{p}
E(k)＝[e
_{1}(k),e
_{1}(k1)]
^{Τ}
Wherein, K
_{p}, K
_{i}be respectively the ratio of pi controller, integral parameter, e
_{1}(k) for the error between k moment reference locus value and real output value, Τ be transpose of a matrix symbol;
In conjunction with abovementioned formula, can be in the hope of:
Can obtain further:
K
_{p}＝w
_{2}(k)
K
_{i}＝w
_{1}(k)K
_{P}
F. the parameter K of pi controller is obtained
_{p}, K
_{i}later formation controlled quentity controlled variable u (k) acts on the stack damper aperture valve of pyrolysis furnace burner hearth,
u(k)＝u(k1)+K
_{p}(e
_{1}(k)e
_{1}(k1))+K
_{i}e
_{1}(k)；
G. at subsequent time, continue to solve the new parameter K of pyrolysis furnace furnace pressure process pi controller according to the step in b to f
_{p}, K
_{i}, circulate successively.
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CN104317321A (en) *  20140923  20150128  杭州电子科技大学  Coking furnace hearth pressure control method based on statespace predictive functional control optimization 
CN105807635A (en) *  20160511  20160727  杭州电子科技大学  Predictive fuzzy control optimized control method for waste plastic oil refining cracking furnace chamber pressure 
CN106444362A (en) *  20161206  20170222  杭州电子科技大学  Distributed PID (Proportion Integration Differentiation) predictive function control method for furnace box temperature of waste plastic cracking furnace 
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