CN108628173A - A kind of chemical industry batch time-lag process Robust Iterative Learning Control method - Google Patents
A kind of chemical industry batch time-lag process Robust Iterative Learning Control method Download PDFInfo
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Abstract
The invention discloses a kind of chemical industry batch time-lag process Robust Iterative Learning Control methods.The present invention establishes input/output model by acquiring inputoutput data first, then it chooses suitable state variable and establishes state-space model, the state-space model after conversion is further established according to state-space model and output error, controller is designed finally by the performance indicator that can meet system control requirement is chosen, and then design optimal more new law, the control method leaned on.System model is converted into two-dimentional time delay converting system model, in conjunction with iterative learning control and feedback control, system is finally made to obtain better control performance by introducing system output tracking error between batch different from traditional control method.
Description
Technical field
The invention belongs to automatic industrial process control fields, are related to a kind of chemical industry batch time-lag process robust iteration
Practise control method.
Background technology
In industrial processes, batch processed process is very universal, such as food production, automobile production.To ensure to criticize
Secondary process output quality, the high-precision control ever more important during batch processed, the whole high-precision of stablizing of batch process are controlled
System, is that batch production process needs key problems-solving.A kind of good control method is designed, batch production system anti-interference is enhanced
Property, it is anti-when ductility, ensure the whole complete high-precision control of batch production, be highly desirable, and traditional method, be only applicable in
In single phase batch processed, multistage batch processed is not adapted to.Therefore, it is proposed to which a kind of chemical industry batch time-lag process robust changes
For learning control method, batch processed system is enable all to keep real-time tracking performance and robustness in different batches different phase
Performance realizes the stabilization high-precision control of batch production process entirety.
Invention content
Purpose of the present invention is to improve the when ductility and anti-interference of control system in chemical industry batch process, it is proposed that a kind of
Chemical industry batch time-lag process Robust Iterative Learning Control method.
The present invention establishes input/output model by acquiring inputoutput data first, then chooses suitable state variable
State-space model is established, the state-space model after conversion is further established according to state-space model and output error, most
Afterwards by choosing the performance indicator design controller that can meet system control and require, and then optimal more new law is designed, is leaned on
Control method.
The present invention method and step include：
Step 1, the state-space model for establishing controlled device in batch process, comprise the concrete steps that：
1-1. acquires the real-time running data of batch process first, establishes a batch process system model.It will be indefinite
Batch process system model under interference is described as follows：
Wherein k and t indicates batch and the batch time of running, x (t+1, k+1), x (t, k+1), x (t-d (t), k+1) respectively
It is k+1 batch t+1 moment, t moment, the system mode at t-d (t) moment respectively, d (t) is the state delay of system t moment, y
(t,k+1)∈RlIt is the system output of k+1 batch t moments, dimension Rl, u (t, k+1) ∈ RmBe k+1 batch t moments system it is defeated
Enter, dimension Rm, l, m are system output and input order respectively.ρ (t, k) indicates the technique rank at t moment k batch systems
Section.Cρ(t,k)It is appropriate dimensional systems matrix respectively.It is the appropriate dimensional systems with state delay d
Matrix. Point
It is not system disturbance matrix, ωρ(t,k)(t, k) is unknown disturbance outside t moment k batches, and x (0, k+1) is k+1 batch systems
Original state, initial value are set as x0,k+1。
1-2. is as follows in the batch process system model in the i-th stage：
Wherein i=1,2 ..., q are natural numbers, and i indicates the operation stage of batch process, xi(t+1,k+1)、xi(t,k+1)、
xi(t, k+1) is t+1 moment the i-th stage of k+1 batches, t moment, the system mode at t-d (t) moment, u respectivelyi(t, k+1) is k+1
The system of i-th stage of batch t moment inputs, yi(t, k+1) is the system output of the i-th stage of k+1 batches t moment,Ci
It is the sytem matrix of the i-th stage appropriate dimension respectively.It is the sytem matrix of the i-th stage appropriate dimension with state delay d.Be respectively the i-th stage not
Know uncertain system disturbance matrix, ωi(t, k) is unknown disturbance outside t moment k the i-th stages of batch.
1-3. determines the input of batch process system model, inputs following form description：
Wherein ui(t, 0) is to start the i-th stage of batch t moment system initial input, uiWhen (t, k) is the i-th stage of k batches t
The system at quarter inputs, ri(t,k+1)∈RmIt is the i-th stage of k+1 batches t moment iteration more new law, T is indicated sometime.
1-4. combination steps 1-2, the i-th stage batch process system output errors ei(t, k+1) is defined as follows:
WhereinIndicate that the i-th stage with delay d gives desired trajectory, ei(t, k+1) is the i-th stage of k+1 batches t
The system output errors at moment.
1-5. combination step 1-2 to 1-4, obtain following primitive formula：
Wherein δ is the backward difference operator of batch, ei(t+1, k) is that the system output at t+1 moment the i-th stage of k batches is missed
Difference, ei(t+1, k+1) is the system output errors at t+1 moment the i-th stage of k+1 batches.uiWhen (t, k) is the i-th stage of k batches t
The system at quarter inputs, xi(t-d (t), k) is the system mode at k batches the i-th stage t-d (t) moment.
Two-dimensional transformations model final 1-6. is indicated in the form of following：
WhereinIt is k+1 batch t+1 moment, t moment, t-d (t) respectively
The system mode that moment expands,It is the system mode expanded at the k batch t+1 moment, Z (t, k+1) is k+1 batch t moments
The system output of expansion,Expression is defined as. RespectivelyMiddle d takes matrix when 1,2.It is k+1 batches t
The external unknown disturbance that moment expands.For the matrix of the i-th stage appropriate dimension.
Step 2, the batch process controller for designing controlled device, specifically：
2-1. is based on step 1, and robust performance ensures that the optimal iteration more new law form under control is as follows：
Wherein For the gain matrix that the i-th stage is different.It is that the i-th stage of k+1 batches t moment is expanded
System mode,It is the system mode expanded the t+1 moment the i-th stage of k batches time.To meet system item
The matrix of part, dimension are (n+l) × (n+l),To meet the matrix of system condition, dimension is m × (n+l).
For 2-2. under repeatability and non-repeatability disturbance, the form that gain matrix control law can be obtained is as follows：
Iteration more new law r is can be obtained in conjunction with step 1-6i(t, k+1) can be obtained optimal system in conjunction with step 1-3
Input ui(t,k)。
2-3. repeats step 1.6 to 2.2 and continues to solve new optimal system input u in subsequent timei(t, k) is acted on
Control object, and recycle successively.
Beneficial effects of the present invention：Different from traditional control method, missed by introducing system output tracking between batch
System model is converted to two-dimentional time delay converting system model by difference, in conjunction with iterative learning control and feedback control, finally make be
System obtains better control performance.The technical scheme is that passing through data acquisition, model foundation, prediction mechanism, optimization
Etc. means, establish a kind of controller design method of batch chemical process, using this method can effectively ensure that system stablize and
Optimal control performance and the stabilization high-precision control for realizing batch processed process entirety.
Specific implementation mode
By taking injection molding process as an example：
Here it with the major parameter of filling process in injection molding process, i.e., is described for injection speed, adjusts hand
Section is to control the valve opening of proportioning valve.
Step 1, the state-space model for establishing proportioning valve in injection molding process, comprise the concrete steps that：
1-1. acquires the real-time running data of injection molding process first, establishes an injection molding process system model.
Injection molding process system model under indefinite interference is described as follows：
Wherein k and t indicates the batch in injection molding process and the batch time of running, x (t+1, k+1), x (t, k+ respectively
1), x (t-d (t), k+1) be respectively the k+1 batch t+1 moment, t moment, t-d (t) moment injection molding processes system mode, d
(t) be t moment in injection molding process state delay, y (t, k+1) ∈ RlIt is the note of k+1 batch t moment injection molding processes
Firing rate degree, dimension Rl, u (t, k+1) ∈ RmIt is the valve opening of k+1 batch t moment injection molding processes, dimension Rm, l, m
It is injection speed and the order of valve opening respectively.ρ (t, k) indicates the technique rank at k batch t moment injection molding processes
Section.Cρ(t,k)It is the appropriate dimensional systems matrix in injection molding process respectively.It is to carry state delay d
Appropriate dimensional systems matrix. It is system disturbance matrix, ω respectivelyρ(t,k)(t, k) is unknown disturbance outside k batches t moment, x (0, k
+ 1) be k+1 batch injection molding processes original state, initial value is set as x0,k+1。
1-2. is as follows in the injection molding process system model in the i-th stage：
Wherein i=1,2 ..., q are natural numbers, and i indicates the operation stage of injection molding process, xi(t+1,k+1)、xi(t,k
+1)、xi(t, k+1) be respectively the t+1 moment the i-th stage of k+1 batches, t moment, t-d (t) moment injection molding processes system shape
State, ui(t, k+1) is the valve opening of the i-th stage of k+1 batches t moment injection molding process, yi(t, k+1) is k+1 batches i-th
The injection speed of stage t moment injection molding process,CiIt is the appropriate dimension in the i-th stage in injection molding process respectively
The sytem matrix of degree.It is the sytem matrix of the i-th stage appropriate dimension with state delay d in injection molding process. It is that the i-th stage is unknown respectively
The system disturbance matrix of uncertain injection molding process, ωi(t, k) is the i-th stage of k batches t moment injection molding process
External unknown disturbance.
1-3. determines the input of injection molding process system model, inputs following form description：
Wherein ui(t, 0) is the initial valve opening for starting the i-th stage of batch t moment injection molding process, ui(t, k) is k
The valve opening of i-th stage of batch t moment injection molding process, ri(t,k+1)∈RmIt is the injection molding of the i-th stage of k+1 batches t moment
The iteration of forming process more new law, T are indicated sometime.
1-4. combination steps 1-2, the injection speed error e of the i-th stage injection molding processi(t, k+1) is defined as follows:
WhereinIndicate that the i-th stage with delay d of injection molding process gives the desired trajectory of injection speed, ei
(t, k+1) is the injection speed error of the i-th stage of k+1 batches t moment injection molding process.
1-5. combination step 1-2 to 1-4, obtain following primitive formula：
Wherein δ is the backward difference operator of the batch of injection molding process, eiWhen (t+1, k) is the i-th stage of k batches t+1
Carve the injection speed error of injection molding process, ei(t+1, k+1) is k+1 batches t+1 the i-th stage, injection molding processes moment
Injection speed error.
ui(t, k) is k batches i-th
StagetThe valve opening of moment injection molding process, xi(t-d (t), k) is the i-th stage t-d (t) the moment injection moldings of k batches
The system mode of journey.
The two-dimensional transformations model of injection molding process final 1-6. is indicated in the form of following：
WhereinIt is k+1 batch t+1 moment, t moment, t-d (t) respectively
The system mode that moment injection molding process is expanded,It is the system shape that k batch t+1 moment injection molding processes are expanded
State, Z (t, k+1) are the injection speeds that k+1 batch t moment injection molding processes are expanded,Expression is defined as.Respectively
ForCorresponding matrix in injection molding process when middle d takes 1,2.It is that k+1 batch t moment injection molding processes are expanded
External unknown disturbance.For the matrix of the i-th stage appropriate dimension of injection molding process.
The injection molding process controller of step 2, design proportion valve, specifically：
2-1. is based on step 1, and robust performance ensures the optimal iteration more new law form of the injection molding process under control such as
Under：
Wherein For the different gain matrixs of the i-th stage injection molding process.It is the i-th rank of k+1 batches
The system mode that section t moment injection molding process is expanded,It is that k batches t+1 the i-th stage, injection molding processes moment are opened up
The system mode of exhibition.To meet the matrix of injection molding process condition, dimension is (n+l) × (n+l),To meet the matrix of injection molding process condition, dimension is m × (n+l).
The shape of the gain matrix control law of injection molding process can be obtained under repeatability and non-repeatability disturbance in 2-2.
Formula is as follows：
Iteration more new law r is can be obtained in conjunction with step 1-6i(t, k+1) can be obtained injection molding in conjunction with step 1-3
The optimal valve opening u of processi(t,k)。
2-3. repeats step 1.6 to 2.2 and continues to solve the optimal valve opening of new injection molding process in subsequent time
ui(t, k) acts on proportioning valve, and recycles successively.
Claims (1)
1. a kind of chemical industry batch time-lag process Robust Iterative Learning Control method, it is characterised in that this method is specifically：
Step 1, the state-space model for establishing controlled device in batch process, comprise the concrete steps that：
1-1. acquires the real-time running data of batch process first, establishes a batch process system model, will be in indefinite interference
Under batch process system model be described as follows：
Wherein k and t indicates batch and the batch time of running respectively, and x (t+1, k+1), x (t, k+1), x (t-d (t), k+1) are respectively
It is k+1 batch t+1 moment, t moment, the system mode at t-d (t) moment, d (t) is the state delay of system t moment, y (t, k+
1)∈RlIt is the system output of k+1 batch t moments, dimension Rl, u (t, k+1) ∈ RmIt is the system input of k+1 batch t moments,
Dimension is Rm, l, m are system output and input order respectively；ρ (t, k) indicates the technique rank at t moment k batch systems
Section；Cρ(t,k)It is appropriate dimensional systems matrix respectively；It is the appropriate dimensional systems with state delay d
Matrix； It is system disturbance matrix, ω respectivelyρ(t,k)(t, k) is unknown disturbance outside t moment k batches, x (0, k+
1) be k+1 batch systems original state, initial value is set as x0,k+1；
1-2. is as follows in the batch process system model in the i-th stage：
Wherein i=1,2 ..., q are natural numbers, and i indicates the operation stage of batch process, xi(t+1,k+1)、xi(t,k+1)、xi
(t, k+1) is t+1 moment the i-th stage of k+1 batches, t moment, the system mode at t-d (t) moment, u respectivelyi(t, k+1) is k+1
The system of i-th stage of batch t moment inputs, yi(t, k+1) is the system output of the i-th stage of k+1 batches t moment,Ci
It is the sytem matrix of the i-th stage appropriate dimension respectively；It is the sytem matrix of the i-th stage appropriate dimension with state delay d； It is that the i-th stage is unknown not respectively
Determining system disturbance matrix, ωi(t, k) is unknown disturbance outside t moment k the i-th stages of batch；
1-3. determines the input of batch process system model：
Wherein ui(t, 0) is to start the i-th stage of batch t moment system initial input, ui(t, k) is the i-th stage of k batches t moment
System inputs, ri(t,k+1)∈RmIt is the i-th stage of k+1 batches t moment iteration more new law, T is indicated sometime；
1-4. combination steps 1-2, the i-th stage batch process system output errors ei(t, k+1) is defined as follows:
WhereinIndicate that the i-th stage with delay d gives desired trajectory, ei(t, k+1) is the i-th stage of k+1 batches t moment
System output errors；
1-5. combination step 1-2 to 1-4, obtain following primitive formula：
Wherein δ is the backward difference operator of batch, ei(t+1, k) is the system output errors at t+1 moment the i-th stage of k batches, ei(t+1,k+1)
It is the system output errors at t+1 moment the i-th stage of k+1 batches；ui
(t, k) is the system input of the i-th stage of k batches t moment, xi(t-d (t), k) is the system at k batches the i-th stage t-d (t) moment
State；
Two-dimensional transformations model final 1-6. is indicated in the form of following：
WhereinWhen being k+1 batch t+1 moment, t moment, t-d (t) respectively
The system mode expanded is carved,It is the system mode expanded at the k batch t+1 moment, Z (t, k+1) is that k+1 batch t moments are opened up
The system output of exhibition,Expression is defined as；RespectivelyMiddle d takes matrix when 1,2；When being k+1 batch t
Carve the external unknown disturbance expanded；For the matrix of the i-th stage appropriate dimension；
Step 2, the batch process controller for designing controlled device, comprise the concrete steps that：
2-1. is based on step 1, and robust performance ensures that the optimal iteration more new law form under control is as follows：
WhereinFor the gain matrix that the i-th stage is different；It is the system that the i-th stage of k+1 batches t moment is expanded
State,It is the system mode expanded the t+1 moment the i-th stage of k batches time；To meet system condition
Matrix, dimension be (n+l) × (n+l), Y1 i,To meet the matrix of system condition, dimension is m × (n+l)；
For 2-2. under repeatability and non-repeatability disturbance, the form that gain matrix control law can be obtained is as follows：
Iteration more new law r is can be obtained in conjunction with step 1-6i(t, k+1) can be obtained optimal system in conjunction with step 1-3 and input ui
(t,k)；
2-3. repeats step 1.6 to 2.2 and continues to solve new optimal system input u in subsequent timei(t, k) acts on control
Object, and recycle successively.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110083139A (en) * | 2019-05-22 | 2019-08-02 | 杭州电子科技大学 | A kind of industrial process performance based on two-dimentional LQG benchmark determines method |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105334739A (en) * | 2015-12-04 | 2016-02-17 | 东北大学 | FAST whole network control method based on P type learning law of iterative learning |
| CN107168293A (en) * | 2017-06-23 | 2017-09-15 | 杭州电子科技大学 | A kind of model prediction tracking and controlling method of batch chemical process |
| CN107544255A (en) * | 2017-10-12 | 2018-01-05 | 杭州电子科技大学 | A kind of state compensation model control method of batch process |
| CN107765549A (en) * | 2017-10-12 | 2018-03-06 | 杭州电子科技大学 | A kind of New Iterative learning control method of batch industrial process |
-
2018
- 2018-06-28 CN CN201810685863.5A patent/CN108628173A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105334739A (en) * | 2015-12-04 | 2016-02-17 | 东北大学 | FAST whole network control method based on P type learning law of iterative learning |
| CN107168293A (en) * | 2017-06-23 | 2017-09-15 | 杭州电子科技大学 | A kind of model prediction tracking and controlling method of batch chemical process |
| CN107544255A (en) * | 2017-10-12 | 2018-01-05 | 杭州电子科技大学 | A kind of state compensation model control method of batch process |
| CN107765549A (en) * | 2017-10-12 | 2018-03-06 | 杭州电子科技大学 | A kind of New Iterative learning control method of batch industrial process |
Non-Patent Citations (7)
| Title |
|---|
| LIMIN WANG ET AL.: "Average dwell time-based optimal iterative learning control for multi-phase batch processes", 《JOURNAL OF PROCESS CONTROL》 * |
| LIMIN WANG ET AL.: "Delay-range-dependent robust 2D iterative learning control for batch processes with state delay and uncertainties", 《CHINESE JOURNAL OF CHEMICAL ENGINEERING》 * |
| LIMIN WANG ET AL.: "Delay-Range-Dependent-Based Hybrid Iterative Learning FaultTolerant Guaranteed Cost Control for Multiphase Batch Processes", 《INDUSTRIAL AND ENGINEERING CHEMISTRY RESEARCH》 * |
| LIMIN WANG ET AL.: "Iterative learning fault-tolerant control for injection molding processes against actuator faults", 《JOURNAL OF PROCESS CONTROL》 * |
| LIMIN WANG ET AL.: "Robust design of feedback integrated with iterative learning control for batch processes with uncertainties and interval time-varying delays", 《JOURNAL OF PROCESS CONTROL》 * |
| 王立敏等: "基于T-S模糊模型的间歇过程的迭代学习容错控制", 《化工学报》 * |
| 王立敏等: "间歇过程复合迭代学习容错保性能控制器设计", 《上海交通大学学报》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110083139A (en) * | 2019-05-22 | 2019-08-02 | 杭州电子科技大学 | A kind of industrial process performance based on two-dimentional LQG benchmark determines method |
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