Hydraulic synchronous control method based on model prediction

Abstract

The invention relates to the technical field of building construction control, and particularly discloses a hydraulic synchronous control method based on model prediction, which comprises the following steps: constructing a state space model for a silo group hydraulic lifting system; state changes at future moments are predicted through the system model; solving a control problem on a finite time domain through an optimizer; the actual lifting height of the hydraulic jack is fed back to the control system, the system state at the next moment is predicted again, and control input is adjusted; a rolling optimization strategy is adopted, only the optimal control input of the current moment is executed at each control moment, and the future control input is recalculated according to the feedback value of the next moment. By establishing an accurate system model and optimizing control input, the problem that the sliding speed and height of each jack are inconsistent due to traditional manual operation can be effectively avoided, the geometric accuracy of silo group sliding formwork construction is ensured, and the construction quality is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of construction control, and particularly relates to a hydraulic synchronous control method based on model prediction. Background Art

[0002] In the slip form construction of silo groups, the synchronous lifting of the slip form is crucial. The traditional control of the jack formwork lifting relies on manual operation, which has many drawbacks. On the one hand, manual operation is prone to errors. The surveyors manually measure the horizontal elevation of the support rods and compare the scale. During the construction of large-scale silo groups, when multiple jacks work simultaneously, it is difficult to ensure that the lifting speeds and heights of each jack are the same, which affects the construction accuracy. On the other hand, multi-point operation increases the complexity. Each jack needs to be precisely controlled, otherwise it is easy to cause the formwork to tilt, affecting the geometric accuracy of the silo structure. In addition, manual operation lacks a real-time feedback mechanism. When there are deviations in the slip form lifting, it is difficult to adjust and correct them in a timely manner, affecting the construction progress and quality.

[0003] At present, although the slip form construction technology has been widely used, there are still deficiencies in the aspects of horizontal degree, vertical degree and stress monitoring. The existing monitoring means have low automation and intelligence levels, and it is difficult to achieve full-range and high-precision real-time monitoring in complex construction environments. Therefore, there is an urgent need for an advanced method that can improve the construction accuracy and efficiency of the slip form and achieve hydraulic synchronous control. Summary of the Invention

[0004] The present invention aims to provide a hydraulic synchronous control method based on model prediction to solve the problems of asynchronous hydraulic lifting, low construction accuracy and lack of real-time feedback adjustment in the slip form construction of silo groups, ensure that the slip form accurately lifts according to the set height, and improve the construction quality and efficiency.

[0005] The object of the present invention can be achieved by the following technical solutions: A hydraulic synchronous control method based on model prediction includes the following steps: S1: Construct a state space model for the hydraulic lifting system of the silo group; S2: Based on the current system state and control input, predict the state change at the future moment through the system model and compare it with the expected lifting height; S3: Solve the control problem in the finite time domain through an optimizer, with the goal of minimizing the deviation between the predicted height and the expected height, while considering the speed limit and pressure constraint of the hydraulic system; S4: Feed back the actual lifting height of the hydraulic jack to the control system, re-predict the system state at the next moment and adjust the control input; S5: Adopt a rolling optimization strategy. Only the optimal control input at the current moment is executed at each control moment, and the future control input is recalculated according to the feedback value at the next moment.

[0006] As a further solution of the present invention: in the above S1, the state space model is as follows: ; wherein, x(t) represents the height of each silo at present, u(t) represents the speed of the hydraulic jack, and A, B, and C are the state space matrices of the system.

[0007] As a further solution of the present invention: in the above S3, when considering the speed limit and pressure constraint of the hydraulic system, the control formula is: ; wherein, x(t) represents the current system state, u(t) represents the control input, x ref represents the desired lifting height, Q is the weight matrix of the state deviation, indicating the sensitivity of the control system to the height deviation; R is the weight matrix of the control input, indicating the sensitivity of the system to the change of the control quantity; N is the length of the prediction time domain, that is, the system predicts the state of the next N moments. Determine the control input sequence u(t), u(t + 1),..., u(t + N) within a future period of time.

[0008] As a further solution of the present invention: in the above S4, the displacement of the lifting frame of the hydraulic press is monitored in real time by a wire-pulling encoder, and the data is transmitted to the control system for feedback and adjustment.

[0009] As a further solution of the present invention: in the above S5, the control input is used to control the control cabinet of the hydraulic station to adjust the lifting speed of the hydraulic jack, so as to realize the synchronous lifting of the sliding mode.

[0010] As a further solution of the present invention: it also includes real-time monitoring of the operating state of the hydraulic system. When an abnormality occurs, the lifting is immediately stopped and an alarm is issued, and the control input is recalculated according to the new feedback data at the next control moment.

[0011] As a further solution of the present invention: in the above S4, it includes: Using high-precision sensors, in combination with the 5G network or industrial Ethernet, the displacement of the lifting frame of the hydraulic press, the pressure of the hydraulic system, and the actual position of the silo are collected in real time and transmitted to the control system. The system compares the feedback data with the predicted desired state. If there is a deviation, the control input is recalculated according to the model predictive control algorithm, and the possible deviation is compensated and adjusted in combination with the dynamic characteristics of the system and the prediction information.

[0012] As a further solution of the present invention: the high-precision sensors include wire-pulling encoders, pressure sensors, and displacement sensors.

[0013] Advantages of the present invention: By establishing an accurate system model and optimizing the control input, it can effectively avoid the problem of inconsistent jack lifting speeds and heights caused by traditional manual operations, ensure the geometric accuracy of the slip form construction of the silo group, and improve the construction quality; The real-time feedback and adjustment mechanism enables the system to promptly respond to deviations during the slip form lifting process, quickly adjust the lifting speed of the hydraulic jacks, avoid error accumulation, and ensure the construction progress; The present invention takes into account the constraint conditions of the hydraulic system, has strong robustness, can operate stably in a complex construction environment, and provides a reliable control guarantee for the slip form construction of the silo group. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The present invention will be further described below in conjunction with the accompanying drawings.

[0015] Figure 1 is a schematic flow chart of a hydraulic synchronous control method based on model prediction of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0016] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without making creative efforts shall fall within the protection scope of the present invention.

[0017] Please refer to Figure 1 as shown, the present invention is a hydraulic synchronous control method based on model prediction, including the following steps: In the slip form construction of the silo group, select suitable hardware devices such as hydraulic jacks and wire rope encoders. For example, use GYD-35 type hydraulic jacks, whose theoretical stroke is 35mm, actual working stroke is greater than 20mm, maximum working pressure is 8MPa, maximum lifting weight is 3.5t, and working lifting weight is 1.5t, meeting the construction load requirements; Select the OID-R381024-L3M-IP68 absolute value wire rope encoder of OiDee Company, with a range of 0-3000mm, a measurement accuracy of 0.195mm, a linear accuracy of ±0.1%, and transmit the displacement information to the control system through RS485 communication to accurately monitor the lifting height of the hydraulic jack lifting frame in real time.

[0018] System modeling: According to the actual physical characteristics of the silo group hydraulic lifting system, collect a large amount of experimental data to determine the values of the state space matrices A, B, and C. For example, through testing the relationship between the pressure and flow rate of the hydraulic system and the jack lifting speed and silo height change, combined with physical principles, establish a mathematical model that accurately reflects the dynamic characteristics of the system; A mathematical model is established based on the hydraulic lifting system of the silo group and is represented by the state - space model as follows: ; Among them, \(x(t)\) represents the state of the system, that is, the height of each silo at present; \(u(t)\) represents the control input, that is, the speed of the hydraulic jack; \(A\), \(B\), and \(C\) are the state - space matrices of the system, and their determination depends on in - depth theoretical analysis of the hydraulic lifting system, a large amount of on - site experimental data, and accurate numerical simulation. For example, by obtaining the lifting speed of the jack and the change data of the silo height under different oil pressures and flow rates through experiments, and using system identification algorithms to fit the specific values of the state - space matrices, ensuring that the model can accurately reflect the dynamic characteristics of the system. This model is established based on the physical characteristics of the system and experimental data, and accurately describes the relationship between the lifting speed and height of each silo.

[0019] State prediction: Based on the current system state \(x(t)\) and control input \(u(t)\), predict the state change at future times through the above - mentioned system model. Specifically, use the model to calculate the lifting height of each silo in the future and compare it with the expected lifting height \(x\) ref to determine whether the lifting process meets the expectations. During the prediction process, considering the uncertainties in the construction environment, such as fluctuations in the concrete pouring speed, wind and other external interference factors, advanced estimation methods such as Kalman filtering are used to optimally estimate the system state to improve the accuracy of the prediction. Compare the predicted future lifting heights of each silo with the pre - set expected lifting height \(x\) ref to calculate the height deviation. Not only pay attention to the overall height deviation, but also analyze the deviation of each silo separately to provide a basis for subsequent precise control.

[0020] Optimization problem solving: Solve a control problem over a finite time - horizon through an optimizer. The goal is to minimize the deviation between the predicted height and the expected height, while considering the constraints of the hydraulic system, such as speed limits and pressure constraints. The control formula used is: ; Among them, \(x(t + k)\) is the predicted state of the system at future time \(t + k\); \(x\) ref is the expected reference height; \(u(t + k)\) is the control input (the lifting speed of the hydraulic jack); \(Q\) is the weight matrix of the state deviation, indicating the sensitivity of the control system to the height deviation; \(R\) is the weight matrix of the control input, indicating the sensitivity of the system to changes in the control quantity; \(N\) is the length of the prediction time - horizon, that is, the system predicts the state of the future \(N\) time - instants. By solving this optimization problem, determine the control input sequence \(u(t), u(t + 1),\cdots, u(t + N)\) for a period of time in the future.

[0021] Real - time feedback and adjustment: The wire-pulling encoder monitors the displacement of the lifting frame of the hydraulic press in real time and transmits the data to the adaptive control box through the RS485 communication circuit. After receiving the data, the adaptive control box compares it with the expected lifting height. If there is a deviation, it calculates the adjusted control input according to the model predictive control algorithm and controls the hydraulic station control cabinet to adjust the lifting speed of the hydraulic jack through a non-intrusive control method. Only the optimal control input at the current moment is executed at each control moment, and the control input for the next moment is recalculated based on the new feedback value to achieve rolling optimization control. For example, when it is detected that the lifting height of a certain silo lags behind, the system automatically increases the lifting speed of the hydraulic jack of that silo to ensure the synchronous lifting of each silo.

[0022] Due to the dynamic nature of the system, state feedback is performed at each moment in the present invention. The actual lifting height of the hydraulic jack is fed back to the control system, and the system state at the next moment is re-predicted and the control input is adjusted based on these feedback values. For example, when it is found that there is a deviation between the actual lifting height and the predicted height of a certain silo, the lifting speed of the hydraulic jack of that silo is adjusted in a timely manner to keep the lifting heights of each silo synchronized.

[0023] Real-time feedback and adjustment are important mechanisms to ensure the effectiveness of the hydraulic synchronous control method. During the slip form construction of a silo group, with the help of high-precision sensors such as wire-pulling encoders, pressure sensors, displacement sensors, etc., key information such as the displacement of the lifting frame of the hydraulic press, the pressure of the hydraulic system, and the actual position of the silo is monitored in real time. These sensors transmit the collected data to the control system through a high-speed and reliable communication network such as a 5G network or an industrial Ethernet. After receiving the feedback data, the control system compares and analyzes it with the predicted state and the desired state. If it is found that there is a deviation between the actual state and the desired state, the control input is recalculated according to the model predictive control algorithm. Adjustment is not only made based on the current deviation, but also combined with the dynamic characteristics and predictive information of the system to compensate for possible deviations in advance. For example, when it is detected that the lifting speed of a certain silo is slow, the control system not only increases the lifting speed of the hydraulic jack of that silo, but also judges the possible deviation trend in the future according to the prediction model and appropriately increases the adjustment amplitude to ensure that each silo can quickly and accurately reach the goal of synchronous lifting.

[0024] Execute the control input: Adopt a rolling optimization strategy. Only the optimal control input u(t) at the current moment is executed at each control moment, and the control input for the future will be recalculated based on the feedback value at the next moment. In this way, during the construction process, the control input can be continuously optimized according to the actual situation to ensure the accuracy and stability of the slip form lifting.

[0025] The execution control input is to apply the optimized control strategy to the actual operation of the silo group slip form construction. Adopting the strategy of rolling optimization, only the optimal control input u(t) calculated at the current moment is executed at each control moment. The control system sends the control instruction to the hydraulic station control cabinet, and the hydraulic station control cabinet precisely adjusts parameters such as the lifting speed and flow rate of the hydraulic jacks according to the instruction. During the execution process, considering the response delay and non-linear characteristics of the hydraulic system, appropriate compensation and correction are made to the control instruction. For example, by establishing a response model of the hydraulic system, predicting the actual effect after the execution of the control instruction, and adjusting the instruction in advance to ensure that the hydraulic jacks can operate accurately according to the control requirements. At the same time, the operating state of the hydraulic system, such as parameters like oil pressure and oil temperature, is monitored in real time. When abnormal situations are found in the system, corresponding protection measures are immediately taken, such as stopping the lifting operation and sending out an alarm, to ensure the construction safety. As the construction progresses, the control input is recalculated according to the newly collected feedback data at the next control moment, and the control strategy is continuously updated and optimized to achieve precise and stable synchronous lifting of the slip form.

[0026] The above has described in detail an embodiment of the present invention, but the content described is only a preferred embodiment of the present invention and cannot be considered as limiting the scope of implementation of the present invention. All equivalent changes and improvements made according to the scope of the application of the present invention shall still fall within the scope covered by the patent of the present invention.

Claims

1. A hydraulic synchronous control method based on model prediction, characterized in that Including the following steps: S1: Construct a state - space model for the hydraulic lifting system of the silo group; S2: Based on the current system state and control input, predict the state change at future moments through the system model and compare it with the desired lifting height; S3: Solve the control problem over a finite time domain through an optimizer, with the goal of minimizing the deviation between the predicted height and the desired height, while considering the speed limit and pressure constraints of the hydraulic system; S4: Feed back the actual lifting height of the hydraulic jack to the control system, re - predict the system state at the next moment and adjust the control input; S5: Adopt a rolling optimization strategy, where only the optimal control input at the current moment is executed at each control moment, and future control inputs are recalculated based on the feedback values at the next moment.

2. The hydraulic synchronous control method based on model prediction according to claim 1, wherein In the above S1, the state - space model is: ； where \(x(t)\) represents the height of each silo at present, \(u(t)\) represents the speed of the hydraulic jack, and \(A\), \(B\), \(C\) are the state - space matrices of the system.

3. A hydraulic synchronization control method based on model prediction according to claim 1, characterized in that In the above S3, when considering the speed limit and pressure constraints of the hydraulic system, the control formula is: ； where x ref represents the desired lift height, Q is the weight matrix of the state deviation, representing the sensitivity of the control system to the height deviation; R is the weight matrix of the control input, representing the sensitivity of the system to the change of the control quantity; N is the length of the prediction horizon, that is, the system predicts the states of the next N time instants; Determine the control input sequence \(u(t), u(t + 1),\cdots, u(t+N)\) for a period of time in the future.

4. A hydraulic synchronous control method based on model prediction according to claim 1, characterized in that In the above S4, the displacement of the hydraulic press lifting frame is monitored in real time through a wire - drawing encoder, and the data is transmitted to the control system for feedback and adjustment.

5. A hydraulic synchronous control method based on model prediction according to claim 1, characterized in that, In the above S5, the control input is used to control the hydraulic station control cabinet to adjust the lifting speed of the hydraulic jack, so as to achieve synchronous lifting of the sliding mode.

6. The hydraulic synchronization control method based on model prediction according to claim 1, wherein It also includes real - time monitoring of the operating state of the hydraulic system. When an abnormality occurs, the lifting is immediately stopped and an alarm is issued, and the control input is recalculated according to the new feedback data at the next control moment.

7. A hydraulic synchronous control method based on model prediction according to claim 1, characterized in that In the above S4, it includes: Using high - precision sensors, combined with 5G network or industrial Ethernet, real - time collect the displacement of the hydraulic press lifting frame, the pressure of the hydraulic system and the actual position of the silo and transmit them to the control system. The system compares the feedback data with the predicted desired state. If there is a deviation, recalculate the control input according to the model predictive control algorithm, and compensate and adjust the possible deviation by combining the dynamic characteristics of the system and the prediction information.

8. A model prediction-based hydraulic synchronization control method according to claim 7, characterized in that The high - precision sensors include wire - drawing encoders, pressure sensors and displacement sensors.

Images