CN116859837A - Submerged arc furnace electrode automatic regulating system based on model predictive control - Google Patents
Submerged arc furnace electrode automatic regulating system based on model predictive control Download PDFInfo
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Abstract
The application discloses an automatic submerged arc furnace electrode adjusting system based on model predictive control, which comprises a sensor unit, a data acquisition unit, a central processing unit, a man-machine interaction unit, a model predictive control unit, a numerical control output unit and an execution mechanism unit, wherein the sensor unit is used for acquiring data of a submerged arc furnace electrode; the system solves the problem that the electrode automatic adjustment of the submerged arc furnace cannot be realized in the prior art, realizes the automatic adjustment control of the submerged arc furnace electrode, realizes the effect of stable production and economic benefit improvement, and improves the whole intelligent level of the submerged arc furnace. The system solves the problem that the electrode automatic adjustment of the submerged arc furnace cannot be realized in the prior art, realizes the automatic adjustment control of the submerged arc furnace electrode, realizes the effect of stable production and economic benefit improvement, and improves the whole intelligent level of the submerged arc furnace.
Description
Technical Field
The application relates to the field of automatic electrode regulation control in a smelting submerged arc furnace, in particular to an automatic submerged arc furnace electrode regulation system based on model predictive control.
Background
Currently, the smelting submerged arc furnace is designed and has huge production capacity, the capacity is close to 100MVA or more, three alternating current single-phase transformers are generally adopted for power supply, a primary high-voltage side is connected with a high-voltage power supply system for power taking in a star connection or angle connection mode, a secondary low-voltage side is connected with three electrodes in an angle connection mode, three electrodes are all often operated independently in the actual production process, a process operator selects one electrode to conduct lifting operation according to the furnace condition, when the deviation from a production target is large, the single-phase transformers are subjected to lifting and shifting to complete adjustment, the transformer is used for realizing rough adjustment in a comprehensive way, fine adjustment is realized through electrode lifting, three-phase electric parameters are required to be balanced in the adjustment process, but the three-phase electric parameters are difficult to balance in the actual production process due to strong coupling of the three-phase power supply system, the fluctuation is large, the power consumption is quite different according to the operation methods of the process operator, the furnace body structure can be influenced under the condition of unbalance, the service life of the submerged arc furnace is seriously influenced, and serious economic loss is caused.
In the field of process control, model Predictive Control (MPC) is a typical representation of Advanced Process Control (APC). MPC is the most successful control method and technology after PID, can effectively treat constraint, multivariable, coupling and pure hysteresis, is widely used in industries such as petroleum, chemical industry, cement and the like, but has a very good success in submerged arc furnace smelting. The MPC multivariable control function uses a model to predict future behavior of process output in input change, improves dynamic performance of process control, can furthest inhibit fluctuation of a control system, advances a production process to a control target of quality (or economic) constraint conditions playing a key role in the production process, reduces variance of the control system, and more importantly, MPC can smoothly operate the system on certain boundaries of multiple constraint conditions, so that the control system can operate while clamping, which is key for the MPC to generate economic benefits. Meanwhile, the MPC can quickly inhibit the influence of interference and can also process the strong coupling of a complex multivariable system. The MPC is very suitable for automatic control of electric parameter balance of three-phase electrodes due to strong coupling effect among the three electrodes caused by the special structure of the submerged arc furnace power supply system. After MPC is put into operation, the submerged arc furnace electrode realizes automatic control and adjustment, the operation intensity of process personnel is greatly reduced, the automation rate is obviously improved, the running stability and safety of the device are ensured, the product quality is ensured, the yield of target products is improved, the running cost is reduced, and the economic benefit is obviously improved.
Disclosure of Invention
According to the problems existing in the prior art, the application discloses an automatic submerged arc furnace electrode adjusting system based on model predictive control, which comprises the following components:
the sensor unit is used for collecting the actual position information of three electrodes, the actual gear position of the single-phase transformer, the electrode voltage, current and power information and various physical parameter information in the production process of the submerged arc furnace, and converting the collected parameter information into an electric signal and outputting the electric signal;
the data acquisition unit receives the electric signal information transmitted by the sensor unit in a millisecond scanning period, and performs data processing on the received information in an anti-shake, filtering and passivation mode;
the central processing unit receives the data information transmitted by the data acquisition unit, circularly executes logic processing on the received information according to a second-level period, and prepares a production process control strategy and execution actions of all electric elements on site;
the man-machine interaction unit is used for receiving the processed information transmitted by the central processing unit and displaying real-time data information, receiving a control instruction input by an operator and transmitting the control instruction to the central processing unit to realize bidirectional data exchange;
the model prediction control unit is used for receiving the logic processing information and the production data transmitted by the central processing unit, analyzing the production process data of the submerged arc furnace by adopting a constrained dynamic matrix model strategy, predicting the working state, the electrode position and the single-phase transformer gear output of the submerged arc furnace in a certain time in the future so as to control the electrode voltage, the electrode current and the electrode power to strive for three-phase electric parameter balance, and transmitting the prediction calculation result to the central processing unit according to a minute-level period;
the numerical control output unit receives the control instruction sent by the central processing unit in real time, refreshes the output change control information according to millisecond level, adjusts the output change in real time and converts the information into various physical signals;
and the execution mechanism unit receives the physical signals transmitted by the numerical control output unit and executes various equipment actions in the production process of the submerged arc furnace.
The central processing unit protects the submerged arc furnace equipment according to the upper limit and lower limit protection values of various physical data parameters of three electrodes of the submerged arc furnace, the actual gear of the single-phase transformer, the electrode voltage, the electrode current, the electrode power, the furnace bottom temperature, the flue gas temperature, the oxygen content in the flue gas and the hydrogen content in the flue gas, which are set in the man-machine interaction unit by an operator, and carries out reverse regulation instruction output when overrun, cuts off the main loop instruction of the power supply of the single-phase transformer and transmits the instruction to the numerical control output unit when serious overrun.
The actuating mechanism unit controls the motor to rotate forwards and backwards, drives the on-load voltage regulating switch, controls the switching electromagnetic valve of the hydraulic driving force and controls the opening and closing of the primary high-voltage vacuum circuit breaker device of the single-phase transformer.
When the model prediction control unit adopts a constrained dynamic matrix model strategy to analyze the production process data of the submerged arc furnace, firstly, a unit step response model Y (k) =M of a multiple-input multiple-output MIMO system is established ss Y(k-1)+S u Δu(k-1)+S d Δd(k-1)
y(k)＝CY(k)
y c (k)＝C c y(k)
y m (k)＝C m y(k)
Wherein Δu (k) =u (k) -u (k-1), Δd (k) =d (k) -d (k-1), where Y (k) is the state variable, u (k) is the control input variable, Y (k) is the output variable, Y c (k) Is the controlled output variable, y m (k) Is a measured output variableD (k) is the measured external disturbance variable, if the sampling step number required by the system to enter the steady state is N, the initial condition Y (0) of the response model equation is an N-dimensional column vector, and the system matrix M ss Is an N-dimensional square matrix, S u And S is d The unit step response coefficient matrix is used for controlling the input u and the measurable interference d to output y respectively;
for three electrodes, electrode positions are selected, a single-phase transformer gear is used as an output variable y (k), electrode voltage, electrode current and electrode power are selected as control input variables u (k), furnace bottom temperature, flue gas temperature, oxygen content in flue gas and hydrogen content in flue gas are selected as external disturbance variables d (k) for measurement, coarse adjustment is achieved through gear shifting of the single-phase transformer, fine adjustment is achieved through electrode position lifting, automatic electrode control and adjustment are achieved in the actual stable production process, the electrode position lifting mode is mainly adjusted in a fine adjustment mode, and three-phase electric parameter balance is strived for in the adjustment process.
The model prediction control unit adopts a constrained dynamic matrix model strategy and specifically comprises the following steps:
s0: based on a unit step response model of a multi-input multi-output MIMO system in an MPC control theory, initializing by referring to output, control quantity and control increment constraint conditions: m, S u ,S d ,K F ,H,Γ y ,Γ u … coefficient matrix;
s1, analyzing and refining production experience of electrode operation of an operator of the submerged arc furnace and historical operation data, giving an expected track R (k+1) to obtain a measured value y m (k),d(k)；
S2: performing output state estimation, i.e. calculating according to observer equations
S3: calculating E from each coefficient matrix p (k+1|k)，G(k+1|k)，b(k+1|k)；
S4: QP problem solving is carried out on the objective function by utilizing the constraint conditions of output, control quantity and control increment to obtain delta U * (k)；
S5: calculating DeltaU * (k) Related open loop sequencesThe first step of the column, control increment Δu (k) = [ I ] nu×nu 0…0]ΔU * (k)；
S6: the control quantity u (k) =u (k-1) +deltau (k) acts on the control system, and after the output adjustment of the period is completed, the cycle jumps to the S1 loop for execution.
By adopting the technical scheme, the automatic submerged arc furnace electrode adjusting system based on model predictive control solves the problem that the submerged arc furnace cannot realize automatic electrode adjustment in the prior art, realizes automatic submerged arc furnace electrode adjustment control, realizes stable production and improves economic benefit, and improves the overall intelligent level of the submerged arc furnace.
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In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments described in the present application, and other drawings may be obtained according to the drawings without inventive effort to those skilled in the art.
FIG. 1 is a block diagram of a system according to the present application
FIG. 2 is a schematic diagram of the operation of the system of the present application
Detailed Description
In order to make the technical scheme and advantages of the present application more clear, the technical scheme in the embodiment of the present application is clearly and completely described below with reference to the accompanying drawings in the embodiment of the present application:
the automatic submerged arc furnace electrode adjusting system based on model predictive control shown in fig. 1 specifically comprises a sensor unit 101, a data acquisition unit 102, a central processing unit 103, a man-machine interaction unit 104, a model predictive control unit 105, a numerical control output unit 106 and an execution mechanism unit 107.
Further, the sensor unit 101 functions as: sensing and detecting various physical data parameters such as the actual positions of three electrodes, the actual gear of a single-phase transformer, the electrode voltage, the electrode current, the electrode power, the furnace bottom temperature, the flue gas temperature, the oxygen content in the flue gas, the hydrogen content in the flue gas and the like in the production process of the submerged arc furnace, converting the sensed information into electric signals according to a certain rule, and outputting the electric signals, wherein the output signals can be used by the data acquisition unit 102;
the data acquisition unit 102 functions as: the electrical signals output by the sensor unit 101 are collected according to a millisecond scanning period, the collected signals are subjected to data processing by using anti-shake, filtering, passivation and other methods, the availability of the data is improved, and then the collected data is output to the central processing unit 103;
the central processing unit 103 functions as: the signals collected from the data acquisition unit 102 are circularly processed in a logic control mode according to a second-level period, then the processed real-time information is transmitted to the man-machine interaction unit 104 for process operators to check, and control instructions sent by the man-machine interaction unit 104 are received to enter logic control of the central processing unit 103, so that bidirectional data communication with the man-machine interaction unit 104 is completed, and real man-machine friendly interaction is achieved; the central processing unit 103 sends a large amount of submerged arc furnace production process data to the model predictive control unit 105 for model predictive control data calculation, and then the model predictive control unit 105 returns calculation result information to the central processing unit 103; the central processing unit 103 processes the received calculation result information and adjusts the production process control strategy, a control signal is transmitted to the execution mechanism unit 107 through the numerical control output unit 106, the final actual action of the field device is completed, then the production field process data parameters are changed along with the actual action, and are sensed by the sensor unit 101 again and again, the whole production system is ensured to run reliably, normally and optimally; the central processing unit 103 protects the submerged arc furnace equipment according to the upper limit and lower limit protection values of various physical data parameters such as the actual positions of three electrodes of the submerged arc furnace, the actual gear of the single-phase transformer, the electrode voltage, the electrode current, the electrode power, the furnace bottom temperature, the flue gas temperature, the oxygen content in the flue gas, the hydrogen content in the flue gas and the like which are manually set by the man-machine interaction unit 104, and when the submerged arc furnace equipment is out of limit, reverse regulation instruction output is carried out or when the submerged arc furnace equipment is severely out of limit, the main loop instruction of the single-phase transformer power supply is cut off and output to the numerical control output unit (106) to finally realize protection action through the execution mechanism unit 107.
The man-machine interaction unit 104 has the functions of: friendly communication with process operators is realized, information received from the central processing unit 103 is displayed in real time, and control instructions of the process operators are sent to the central processing unit 103;
the model predictive control unit 105 functions as: the core component for carrying out model predictive control calculation on the submerged arc furnace acquires a large amount of submerged arc furnace generation process data in the central processing unit 103, then executes the model predictive control data calculation function developed in the process, and reversely transmits predictive calculation result information back to the central processing unit 103 in a minute-level period after a single model predictive control calculation task is completed;
the numerical control output unit 106 functions as: receiving control instructions sent by the central processing unit 103 in real time, refreshing output change control information according to millisecond level, adjusting output change in real time, converting the information into various physical signals and transmitting the physical signals to the execution mechanism unit 107;
the function of the actuator unit 107 is: and receiving various physical signals sent by the numerical control output unit 106 to finish various equipment actions in the production process of the submerged arc furnace. The development mainly relates to a single-phase transformer primary high-voltage vacuum circuit breaker opening and closing device, wherein the three single-phase transformer gear lifting and adjusting actuating mechanisms are load voltage regulating switches driven by a motor in forward and reverse directions, the three electrode positions lifting and adjusting actuating mechanisms are switching electromagnetic valves of hydraulic driving force, and the single-phase transformer is severely over-limited in technological parameters.
The model predictive control unit 105 is a core software component for performing model predictive control on the submerged arc furnace, and is generally disposed in Edge server Edge-PC hardware for submerged arc furnace production management, where the server may be deployed as a local server, and the network is disposed in a terminal bus of a last level of the central processing controller hardware, and is independent of the submerged arc furnace production process control factory network. The model prediction control unit 105 is used for model prediction control calculation of automatic regulation of the submerged arc furnace electrode, and the result information data is interacted with the central processing unit 103 and the man-machine interaction unit 104 which are positioned on the terminal bus in real time, so that the purpose of intelligent prediction control is achieved. The Edge server Edge-PC performs data Edge calculation, is an open system composed of hardware and software, and can flexibly execute a packaging application program based on a high-level language; and the visual integrated factory function is used for realizing intelligent use of data on the basis of factories aiming at automatic acquisition, processing and data exchange. The Edge server Edge-PC is based On open industrial Ethernet communication, is compatible with various Ethernet communication protocols, supports OPC, TCP, UDP, ISO-On-TCP, I-Device and S7-Routing communication protocols, supports SNMP, web, FTP, NTP and other IT communication services, and can conveniently directly transplant and dock the functions of the model predictive control system, such as data processing and algorithm units, into other similar industrial intelligent control systems.
The MPC can smoothly operate the system on certain boundaries of multiple constraint conditions, so that the control system can run at the upper limit or the lower limit, which is the key of the MPC to produce economic benefits; the MPC can quickly inhibit the influence of interference and can also process the strong coupling of a complex multivariable system. The MPC uses the model and the measured values of the current process to calculate future actions of the manipulated variables and ensure that all inputs and outputs meet constraints, and then the MPC downloads the calculated plurality of control input values to the central processing unit 103 regulator control loop, where the underlying control is effected, while a feedback mechanism in the MPC can compensate for the prediction error between the model and the process. MPC is a model-based finite time domain (or infinite time domain) open loop optimal control algorithm that essentially uses a process model to predict future states or outputs, and at each sampling instant, the controller takes the system state at the current instant as the initial state, and takes control action by minimizing the difference between the future outputs and the reference trajectory (open loop optimization problem), optimizing to produce a control input sequence, wherein the first component is to be executed and the other components are to be discarded.
Furthermore, a constrained dynamic matrix model (Quadratic Dynamic Matrix Control, QDMC) MPC strategy is selected, and a step response non-parameter model which is easy to obtain in the actual industry is adopted, so that a method for systematically solving input and output constraints is provided, and the variables can be ensured to meet constraint conditions in a certain prediction time domain. The specific calculation method is as follows:
(1) according to MPC theory, considering measurable interference factor, the unit step response model of MIMO system is
Y(k)＝M ss Y(k-1)+S u Δu(k-1)+S d Δd(k-1)
y(k)＝CY(k)
y c (k)＝C c y(k)
y m (k)＝C m y(k)
Wherein Δu (k) =u (k) -u (k-1), Δd (k) =d (k) -d (k-1), where Y (k) is the state variable, u (k) is the control input variable, Y (k) is the output variable, Y c (k) Is the controlled output variable, y m (k) Is a measured output variable and d (k) is an external disturbance variable that can be measured. Setting the sampling step number required by the system to enter a steady state as N, then the initial condition Y (0) of the response model equation is an N-dimensional column vector, and the system matrix M ss Is an N-dimensional square matrix, S u And S is d A matrix of unit step response coefficients controlling input u and measurable disturbance d to output y, respectively. The advanced control system which is developed at this time and can be used for automatic adjustment of the submerged arc furnace electrode based on model prediction control aims at the situation that three electrodes are selected, the single-phase transformer gear is used as an output variable y (k), the electrode voltage, the electrode current and the electrode power are used as control input variables u (k), and the furnace bottom temperature, the flue gas temperature, the oxygen content in the flue gas, the hydrogen content in the flue gas and the like are selected as external disturbance variables d (k) which can be measured. Coarse adjustment is achieved through gear shifting of the single-phase transformer, fine adjustment is achieved through electrode position lifting, electrode automatic control and adjustment are achieved in the actual stable production process in a mode of fine adjustment of electrode position lifting, and three-phase electric parameter balance is strived for in the adjustment process.
(2) Marking the output constraint on the output variable y (k) as y b (k) Simultaneously control and restrict the control quantity and the control increment, y min (k)≤y b (k)≤y max (k)，u min (k)≤u(k)≤u max (k)，Δu min (k)≤Δu(k)≤Δu max (k) A. The application relates to a method for producing a fibre-reinforced plastic composite Setting the position points of 3% and 97% of the stroke of the hydraulic cylinder according to the lifting driving of each electrode as the lower limit and the upper limit of the electrode position; setting the upper limit of unbalance of the three electrodes to 20% by taking the average value of the positions of the three electrodes as a reference, setting the value of unbalance to 0 when the position values of the three electrodes are completely equal, and setting the lower limit; the upper limit of the single adjustment quantity of the positions of the three electrodes is set to be 10mm, and the lower limit is not set; setting the lower limit and the upper limit of the gear of the single-phase transformer according to the gear configuration of the secondary side of the single-phase transformer, and only adjusting the gear within the gear protection limit without adjusting the gear to the boundary when the gear is the lowest gear and the highest gear; setting the maximum gear difference of three single-phase transformers as 2 gears, selecting a strategy that the gears of the three single-phase transformers are lifted and lowered simultaneously in the actual adjustment process, and selecting an adjustment strategy with the gear difference only when the furnace condition is unstable; the upper limit of the single adjustment quantity of the three single-phase transformers is set to be 1 grade, and the lower limit is not set; rated current by secondary side of single-phase transformerThe multiple value is used as the upper limit of the electrode current, 30% of the rated current is set as the lower limit of the electrode current, the electrode breakage is judged, and the program control is carried out, and the automatic adjustment of the MPC electrode is changed to the manual operation of the process; setting the upper limit of the current unbalance of the three electrodes to be 2% by taking the current average value of the three electrodes as a reference, setting the unbalance value to be 0 when the current values of the three electrodes are completely equal, and setting the lower limit; rated voltage of secondary side of single-phase transformer>The multiple value is used as the upper limit of the electrode voltage, 70% of the rated voltage is set as the lower limit of the electrode voltage, abnormal conditions occur in the production process of the submerged arc furnace, and the program control is carried out, so that the automatic adjustment of the MPC electrode is changed to the manual operation of the process; setting the upper limit of the voltage unbalance of the three electrodes to be 5% by taking the average value of the voltages of the three electrodes as a reference, setting the value of the unbalance to be 0 when the voltage values of the three electrodes are completely equal, and setting the lower limit; taking the 120% multiple value of the rated power of the secondary side of the single-phase transformer as the upper limit of the electrode power,setting the lower limit is not performed; setting the upper limit of the power unbalance of the three electrodes to 7% by taking the average power value of the three electrodes as a reference, setting the unbalance value to 0 when the power values of the three electrodes are completely equal, and setting the lower limit; the upper limits of the furnace bottom temperature and the flue gas temperature are respectively set to 500 ℃ and 800 ℃, and the lower limit is not set; the upper limit of the oxygen content in the flue gas and the upper limit of the hydrogen content in the flue gas are respectively set to 0.5% and 8%, and the lower limit is not set.
(3) Aiming at the optimization problem of QDMC at the moment k, given an expected track R (k+1), the objective function is obtained through formula derivation
J(y m (k),ΔU(k))＝||Γ y (Y c (k+1)k)-R(k+1)|| 2 +||Γ u ΔU(k)|| 2 Wherein Γ y And Γ u Is a given weighting matrix.
(4) Designing observer equations
Wherein K is F Calculation by Kalman filtering method to make M ss -K F C m C is nominally asymptotically stable and poles can be arbitrarily configured.
(5) Due to the objective function J (y m (k) Δu (k)) is quadratic and the time-domain constraints are linear, so solving the constraint problem is a quadratic programming (Quadratic programming, QP) problem. Setting z=Δu (k) is an independent variable of optimization and definesThen the objective function becomes through the publicity derivation
J＝||Γ y (S u ΔU(k)-E p (k+1)|k)|| 2 +||Γ u ΔU(k)|| 2 ，
The method is developed to remove the independent variable delta U (k), and the objective function is equivalent to
Wherein,,
(6) the optimization problem of QDMC, which performs control constraint on output variables, control amounts and control increments, is converted into the following QP problem description through formula deduction:
easily known type of middle partThe QP problem is therefore applied to any weighting matrix Γ y ≥0，Γ u All have solution marks of delta U equal to or greater than 0 * (k) Obviously DeltaU * (k) Is the measured value y m (k) The functions in the control and prediction domains are generally nonlinear.
(7) According to the basic principle of predictive control, the first step of the obtained open loop sequence will act on the controlled system, and at the next sampling instant the constraint optimization QP problem will be refreshed with new measurements and the DeltaU will be solved again * (k) Then the closed-loop control law of the constraint QDMC is
Δu(k)＝[I nu×nu 0…0]ΔU * (k)
(8) Finally, the control quantity u (k) =u (k-1) +deltau (k) acts on the system to complete the control of the step.
In the practical application process, the flow of the dynamic matrix control of the QDMC with the time domain constraint, which is implemented in the model prediction control unit (105), is shown in fig. 2, and the execution steps of the flow are as follows:
s0. according to a unit step response model of the multi-input multi-output MIMO system in the MPC control theory, initializing by referring to the output, the control quantity and the control increment constraint conditions: m, S u ,S d ,K F ,H,Γ y ,Γ u …, etc.;
s1, feeding in electrode operation production experience and historical operation data of a submerged arc furnace process staffPerforming line analysis and refinement, giving a desired track R (k+1), and obtaining a measured value y m (k),d(k)；
S2, estimating the output state, namely calculating according to an observer equation
S3, calculating E according to each coefficient matrix p (k+1|k)，G(k+1|k)，b(k+1|k)；
S4, carrying out QP problem solving on the objective function by utilizing constraint conditions of output, control quantity and control increment to obtain delta U * (k)；
S5, calculating delta U * (k) The first step of the correlation open loop sequence, the control increment Δu (k) = [ I ] nu×nu 0…0]ΔU * (k)；
S6, enabling a control quantity u (k) =u (k-1) +delta u (k) to act on a control system, and jumping to S1 for circular execution after the output adjustment of the period is completed;
the QDMC adopts a linear step response coefficient model, which makes the QDMC algorithm only suitable for asymptotically stable objects and first-order integral objects, and for unstable objects, PID control is generally adopted in a central processing unit (103) to calm the unstable objects, then the set value of PID is used as a manipulated variable of the QDMC, and a PID loop is used as a controlled process of the QDMC. Depending on MPC control theory, the model used by MPC only contains accurate low frequency information, and the control problem of high frequency part can be completed by PID control of the bottom central processing unit (103). Therefore, setting the execution period of MPC steady-state target calculation and dynamic optimization to be 1 minute; in the control system of the bottom central processing unit (103), a discrete PID regulating function block is selected for gear shifting of the single-phase transformer, a continuous PID regulating function block is selected for electrode position lifting, and the program execution period of the two function blocks is set to be 1 second.
Although the nonlinearity of the submerged arc furnace process production process is absolute, most large-scale production processes have the characteristics of continuity and stability, so that the steady state and dynamic characteristics of the process in a certain interval near an operating point show a relatively consistent linear relationship, and the corresponding model can relatively accurately represent the input-output relationship of the process, so that the steady state target calculation has a relatively good application effect. As the most effective means of multivariable control, MPC functions to maintain the multivariable control system at the optimal operating point, i.e., to quickly revert the system back to the optimal operating point when disturbances occur. Operating near the optimal operating point, the characteristics reflected by the controlled system are linear, and the purpose of effectively controlling the system can be achieved by using the linear multivariable system model. The optimization in MPC is not a constant global optimization index, but a rolling optimization strategy on a limited time domain is a closed loop optimization based on feedback correction, the rolling implementation of the optimization can cope with uncertainty caused by model mismatch, time variation, interference and the like, the model is corrected in time and compensated, new optimization is always built on an actual basis, so that the control is kept to be actually optimal, namely, the current optimal control strategy is determined by the rolling optimization, and the deviation between a controlled variable and an expected value in a future period of time is minimized.
In summary, the automatic submerged arc furnace electrode adjusting system based on model predictive control has the following characteristics: (1) based on model control, the requirements on the model are not high; (2) adopting a rolling optimization strategy to replace global optimization with local optimization; (3) and the actual measurement information is utilized for feedback correction, so that the robustness of control is enhanced. The specific and complete steps are as follows:
1. the sensor unit 101 is composed of a temperature sensor, an electric parameter detector, a gas analyzer and the like in the production site of the submerged arc furnace, senses and detects various physical data parameters such as the actual positions of three electrodes, the actual gear of a single-phase transformer, electrode voltage, electrode current, electrode power, furnace bottom temperature, flue gas temperature, oxygen content in flue gas, hydrogen content in flue gas and the like in the production process, converts sensed information into electric signals according to a certain rule, and transmits the electric signals to the data acquisition unit 102 through a data cable or a communication cable;
2. the data acquisition unit 102 acquires the output signal of the sensor unit 101 according to a scanning period of millisecond level, and then transmits the acquired data to the central processing unit 103;
3. the central processing unit 103 circularly executes logic control processing on the signals collected from the data collection unit 102 according to the second-level period, and then transmits the data to the man-machine interaction unit 104 and the model prediction control unit 105;
4. the man-machine interaction unit 104 displays important information in the central processing unit 103 in real time, receives a control instruction of a process operator and reversely transmits the control instruction to the central processing unit 103;
5. the model predictive control unit 105 performs model predictive control of the submerged arc furnace production process according to the flowchart implementation method shown in fig. 2 according to a large amount of submerged arc furnace production process data acquired in the central processing unit 103, and reversely transmits predictive calculation result information back to the central processing unit 103 in a minute-level period after a single model predictive control calculation task is completed;
6. when the actual values of various physical data parameters such as the actual positions of three electrodes of the submerged arc furnace, the actual gear of the single-phase transformer, the electrode voltage, the electrode current, the electrode power, the furnace bottom temperature, the flue gas temperature, the oxygen content in the flue gas, the hydrogen content in the flue gas and the like exceed upper and lower limit protection values, the central processing unit 103 automatically switches the output of a production process control strategy reverse regulation instruction of the submerged arc furnace, or receives an adjustment strategy instruction from a process operator of the man-machine interaction unit 104, so that the submerged arc furnace equipment is protected, and the instruction for cutting off the power supply main loop of the single-phase transformer is output immediately under the serious overrun condition;
7. the central processing unit 103 outputs control instructions and data to the numerical control output unit 106, and the numerical control output unit 106 continuously refreshes output change control information from the central processing unit 103 according to millisecond level;
8. the control signal is transmitted to an actuating mechanism unit 107 composed of an electromagnetic valve, a motor and the like through a numerical control output unit 106, lifting adjustment of three single-phase transformer gears is completed through an on-load voltage regulating switch driven by the actuating mechanism in forward and reverse directions of the motor, lifting adjustment of three electrode positions is completed through a switching electromagnetic valve driven by the actuating mechanism in hydraulic driving force, and opening and closing of a high-voltage vacuum circuit breaker of the single-phase transformer are completed when technological parameters are severely overrun;
9. finally, the process data parameters of the production field of the submerged arc furnace are changed along with the process data parameters, and are sensed by the sensor unit 101, so that the process is continuously circulated, and the reliable, stable and optimal operation of the whole production system is always ensured.
The application discloses an automatic submerged arc furnace electrode adjusting system based on model predictive control, wherein the key technology can be partially applied and transplanted to control systems of direct-current submerged arc furnaces or other types of industrial furnaces and kilns, and the partial technology is also in the protection scope of the scheme and is constrained by the technical scheme.
The foregoing is only a preferred embodiment of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art, who is within the scope of the present application, should make equivalent substitutions or modifications according to the technical scheme of the present application and the inventive concept thereof, and should be covered by the scope of the present application.
Claims (5)
1. An automatic submerged arc furnace electrode adjusting system based on model predictive control is characterized by comprising:
the sensor unit (101) is used for collecting the actual position information of three electrodes, the actual gear position of the single-phase transformer, the electrode voltage, current and power information and various physical parameter information in the production process of the submerged arc furnace, and converting the collected parameter information into an electric signal and outputting the electric signal;
the data acquisition unit (102) receives the electric signal information transmitted by the sensor unit in a millisecond scanning period, and performs data processing on the received information in an anti-shake, filtering and passivation mode;
the central processing unit (103) receives the data information transmitted by the data acquisition unit, circularly executes logic processing on the received information according to a second-level period, and prepares a production process control strategy and execution actions of all electric elements on site;
the man-machine interaction unit (104) is used for receiving the processed information transmitted by the central processing unit (103) and displaying real-time data information, receiving a control instruction input by an operator and transmitting the control instruction to the central processing unit (103) to realize bidirectional data exchange;
the model prediction control unit (105) receives logic processing information and production data transmitted by the central processing unit (103), analyzes the production process data of the submerged arc furnace by adopting a constrained dynamic matrix model strategy, predicts the working state and electrode position of the submerged arc furnace in a certain time in the future and outputs a single-phase transformer gear so as to control the electrode voltage, the electrode current and the electrode power to strive for three-phase electric parameter balance, and transmits a prediction calculation result to the central processing unit (103) according to a minute-level period;
the numerical control output unit (106) receives the control instruction sent by the central processing unit (103) in real time, refreshes the output change control information according to millisecond level, adjusts the output change in real time and converts the information into various physical signals;
and the executing mechanism unit (107) receives the physical signals transmitted by the numerical control output unit (106) and executes various equipment actions in the production process of the submerged arc furnace.
2. The model predictive control-based submerged arc furnace electrode automatic regulating system according to claim 1, wherein: the central processing unit (103) protects submerged arc furnace equipment according to the actual positions of three electrodes of the submerged arc furnace, the actual gear of the single-phase transformer, electrode voltage, electrode current, electrode power, furnace bottom temperature, flue gas temperature, oxygen content in the flue gas and upper and lower limit protection values of various physical data parameters of hydrogen content in the flue gas, which are set by an operator in the man-machine interaction unit (104), and outputs reverse regulation instructions when the submerged arc furnace equipment is out of limit, cuts off a main loop instruction of power supply of the single-phase transformer when the submerged arc furnace equipment is severely out of limit, and transmits the instruction to the numerical control output unit (106).
3. The model predictive control-based submerged arc furnace electrode automatic regulating system according to claim 1, wherein: the actuating mechanism unit (107) controls the motor to rotate forwards and backwards, drives the on-load voltage regulating switch, controls the switching electromagnetic valve of the hydraulic driving force and controls the opening and closing of the primary high-voltage vacuum circuit breaker device of the single-phase transformer.
4. The model predictive control-based submerged arc furnace electrode automatic regulating system according to claim 1, wherein: when the model prediction control unit (105) adopts a constrained dynamic matrix model strategy to analyze the production process data of the submerged arc furnace, firstly, a unit step response model Y (k) =M of a multiple-input multiple-output MIMO system is established ss Y(k-1)+S u Δu(k-1)+S d Δd(k-1)
y(k)＝CY(k)
y c (k)＝C c y(k)
y m (k)＝C m y(k)
Wherein Δu (k) =u (k) -u (k-1), Δd (k) =d (k) -d (k-1), where Y (k) is the state variable, u (k) is the control input variable, Y (k) is the output variable, Y c (k) Is the controlled output variable, y m (k) Is the measured output variable, d (k) is the measured external disturbance variable, the initial condition Y (0) of the response model equation is an N-dimensional column vector, and the system matrix M is the number of sampling steps required by the system to enter a steady state is N ss Is an N-dimensional square matrix, S u And S is d The unit step response coefficient matrix is used for controlling the input u and the measurable interference d to output y respectively;
for three electrodes, electrode positions are selected, a single-phase transformer gear is used as an output variable y (k), electrode voltage, electrode current and electrode power are selected as control input variables u (k), furnace bottom temperature, flue gas temperature, oxygen content in flue gas and hydrogen content in flue gas are selected as external disturbance variables d (k) for measurement, coarse adjustment is achieved through gear shifting of the single-phase transformer, fine adjustment is achieved through electrode position lifting, automatic electrode control and adjustment are achieved in the actual stable production process, the electrode position lifting mode is mainly adjusted in a fine adjustment mode, and three-phase electric parameter balance is strived for in the adjustment process.
5. The model predictive control-based submerged arc furnace electrode automatic regulating system according to any one of claims 1 to 4, wherein: the model prediction control unit (105) adopts a constrained dynamic matrix model strategy and specifically comprises the following steps:
s0: based on a unit step response model of a multi-input multi-output MIMO system in an MPC control theory, initializing by referring to output, control quantity and control increment constraint conditions: m, S u ,S d ,K F ,H,Γ y ,Γ u … coefficient matrix;
s1, analyzing and refining production experience of electrode operation of an operator of the submerged arc furnace and historical operation data, giving an expected track R (k+1) to obtain a measured value y m (k),d(k)；
S2: performing output state estimation, i.e. calculating according to observer equations
S3: calculating E from each coefficient matrix p (k+1|k)，G(k+1|k)，b(k+1|k)；
S4: QP problem solving is carried out on the objective function by utilizing the constraint conditions of output, control quantity and control increment to obtain delta U * (k)；
S5: calculating DeltaU * (k) The first step of the correlation open loop sequence, the control increment Δu (k) = [ I ] nu×nu 0…0]ΔU * (k)；
S6: the control quantity u (k) =u (k-1) +deltau (k) acts on the control system, and after the output adjustment of the period is completed, the cycle jumps to the S1 loop for execution.
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| CN118211480B (en) * | 2024-04-02 | 2025-01-07 | 西安交通大学 | Rapid prediction method for performance of submerged arc furnace for hot smelting of nickel iron ore in steel process industry |
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