A roof concrete vibration control system based on PID and a use method thereof

Abstract

The application provides a roof concrete vibration control system based on PID and a use method, and belongs to the technical field of roof construction. The system comprises a PID controller, a database, a rule base, a high-frequency vibrator, a moving mechanism and a simulation module. The PID controller obtains a control amount according to a linear combination of proportion, integration and differentiation based on the deviation between a given input value and an actual output value, and outputs a control signal to a controlled object according to the control amount. The rule base is obtained based on the fuzzification of the control amount, and is the basis for realizing fuzzy reasoning. The simulation module is simulated and analyzed by using Simulink. The problems that the traditional plug-in vibration rod is used for vibration, the vibration is not comprehensive and missed, the concrete of the slope roof plate is easily honeycombed and pitted, the flat vibrator is used, the surface is not controlled during the vibration process, the vibration forming effect is poor, and the slope roof surface is easily formed in a wavy uneven shape are solved.

Description

Technical Field

[0001] This invention belongs to the technical field of roof construction, and specifically relates to a PID-based roof concrete vibration control system and its usage method. Background Technology

[0002] In recent years, in engineering construction, the aesthetically pleasing and flexible sloping roof form has become increasingly popular, and people's requirements for roofs are also getting higher and higher.

[0003] However, poor concrete forming and density during the construction of concrete roof structures, resulting in poor self-waterproofing, has always been an unavoidable common problem in building construction quality.

[0004] The main causes of defects in concrete roof structure quality are as follows: Concrete vibration. Traditional immersion vibrators are used for vibration, but the vibration is incomplete and incomplete, which can easily cause honeycomb and pitting on the concrete of the pitched roof panel. When using a plate vibrator, the vibration process cannot control the surface leveling and the vibration molding effect is poor, which can easily lead to uneven and wavy shapes on the surface of the pitched roof. Summary of the Invention

[0005] This invention provides a PID-based roof concrete vibration control system and its usage method, which solves the problems of incomplete vibration and missed vibration when using traditional immersion vibrators, which easily cause honeycomb and pitting on the concrete of pitched roof panels, and the inability to control surface leveling and poor vibration molding effect when using plate vibrators, which easily leads to uneven and wavy shapes on the surface of pitched roofs.

[0006] In view of the above problems, the technical solution proposed by the present invention is as follows:

[0007] This invention provides a PID-based roof concrete vibration control system, including a PID controller, a database, a rule base, a high-frequency vibrator, a moving mechanism, and a simulation module. The PID controller obtains the control quantity by using a linear combination of proportional, integral, and derivative functions based on the deviation between the given input value and the actual output value, and outputs a control signal to the controlled object based on the control quantity.

[0008] The database is used to provide data information to the vibration control system;

[0009] The rule base is derived from the fuzzification of control variables and forms the basis for fuzzy reasoning.

[0010] The high-frequency vibrator is used for vibrating the roof concrete.

[0011] The moving mechanism is used to control the displacement of the high-frequency vibrator, and includes a chassis, a left swivel wheel, and a right swivel wheel;

[0012] The simulation module uses Simulink for simulation and analysis to evaluate the controller's performance and optimize it according to actual conditions. It includes a fuzzy PID control unit, a motion control unit, a vibrating robot arm control unit, and a data acquisition unit.

[0013] As a preferred embodiment of the present invention, the rule data of the rule base includes a proportion P, an integral I, and a derivative D, and a proportionality coefficient K. P Integral coefficient KI and differential coefficient K D Wherein, the proportionality coefficient K P The integral coefficient K determines the response speed. I The differential coefficient K is used to overcome static error. D Used to overcome vibration.

[0014] As a preferred embodiment of the present invention, the PID controller further includes a controlled object, which is the high-frequency vibrator and the moving mechanism, and controls the desired value. and actual output error value By performing proportional, integral, and derivative operations respectively, and then summing them, the control law is obtained. This law is then passed to the transfer function to control the controlled object. The error can be expressed as:

[0015] ;

[0016] The formula for controlling the input is as follows:

[0017] ;

[0018] in, It is the derivative.

[0019] As a preferred embodiment of the present invention, the fuzzy PID control unit controls the high-frequency vibrator and the moving mechanism based on the fuzzy PID algorithm;

[0020] The motion control unit is used to receive instructions from the fuzzy PID control unit and control the motion mechanism to perform displacement.

[0021] The vibration robot arm control unit is used to control the movement of the high-frequency vibrator and its robot arm to perform vibration work;

[0022] The data acquisition unit is used to collect the displacement of the high-frequency vibrator's robotic arm and the rotation speed and rotation angle of the universal wheels of the moving mechanism.

[0023] As a preferred embodiment of the present invention, the control steps of the fuzzy PID control unit for the high-frequency vibrator robotic arm are as follows:

[0024] a1. Obtain the usage status information of the robotic arm, obtain the tracking error, and establish a mathematical model based on the usage status and error of the robotic arm;

[0025] a2 controls the movement of each joint and collects the movement trajectory of the robotic arm through the data acquisition unit;

[0026] a3 inputs the tracking error into a pre-built fuzzy PID control unit, outputs the corresponding control signal, builds a fuzzy PID controller model, and performs real-time control of the robotic arm based on the control signal.

[0027] As a preferred technical solution of the present invention, in step a3, the specific method of constructing the fuzzy PID control unit is as follows: determine the tracking error variable of the robotic arm, determine the composite error term based on the tracking error variable, determine the inherent unknown dynamic function of the robotic arm based on the composite error term, simulate the inherent unknown dynamic function of the robotic arm using Simulink, and construct the simulated PID control unit based on the weight information obtained from the simulation model.

[0028] The tracking error variables include the control electrical signals of the motors at each joint of the robotic arm, the angle of rotation of the robotic arm, displacement, and speed.

[0029] As a preferred embodiment of the present invention, the data acquisition unit collects the rotational speed of the motors of the casters on the moving mechanism. The motor speeds of the left caster and the right caster are W1 and W2, respectively, with a radius of R and a distance of L between the left and right casters. Then, the following motion equations are obtained:

[0030] ;

[0031] ;

[0032] Where V is the speed of the omnidirectional wheel, which is a uniform speed or average speed, and Q is the speed in a generalized sense.

[0033] The turning radius at any given time is:

[0034] ;

[0035] When W1=W2, ρ is infinite, meaning the robot moves in a straight line. When W1>W2, the robot turns right. When W1<W2, the robot turns left. Based on the movement rules of the moving mechanism, the fuzzy PID control unit performs fuzzy calculations on the movement of the moving mechanism and applies motion constraints.

[0036] On the other hand, a method for using a PID-based roof concrete vibration control system includes the following steps:

[0037] S1. Establish the system model by using modules in Simulink to build a model of the controlled object.

[0038] S2, Design a fuzzy PID control unit and a neural network. Use the fuzzy logic controller module and neural network module in Simulink to implement the design of the fuzzy PID control unit and the neural network.

[0039] S3 combines a fuzzy PID control unit and a neural network. Simulink is used to combine the fuzzy PID control unit and the neural network, and the fuzzy output variables are transmitted to the neural network controller to adaptively adjust the weights through training data.

[0040] S4. Adjust the control system parameters. Depending on the actual situation, it is necessary to adjust the parameters of the control system. This step can be achieved through the parameter setting module in Simulink.

[0041] S5, Simulation and Analysis: Uses Simulink for simulation and analysis to evaluate the performance of the control system and optimize it based on actual conditions;

[0042] S6, based on optimized control data, controls the vibrator's robotic arm and moving mechanism to perform stable vibration and position movement of the roof concrete through the control system.

[0043] As a preferred technical solution of the present invention, in step S2, the design of the fuzzy PID control unit requires converting the input variables and output variables into fuzzy sets, then setting rules to describe the relationship between the input variables and output variables, and finally optimizing according to the actual situation.

[0044] The design of a neural network module requires determining the input and output variables of the neural network, and then adaptively adjusting the weights based on the training data.

[0045] Compared with the prior art, the beneficial effects of the present invention are:

[0046] This invention utilizes PID and Simulink to establish models of the vibrator and moving mechanism. By simulating the motion data of the vibrator and moving mechanism and evaluating the performance of the simulation, the operation of the vibrator and moving mechanism is optimized according to different roof concrete conditions. Then, the vibrator and moving mechanism are controlled to perform stable vibration of the roof concrete, saving computing resources and further improving the overall control performance and motion accuracy of the system, resulting in better vibration effect for roof concrete.

[0047] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, and in order to make the above and other objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0048] Figure 1 This is a schematic diagram of a PID-based roof concrete vibration control system disclosed in this invention.

[0049] Figure 2 This is a schematic diagram of the structure of a simulation module of a PID-based roof concrete vibration control system disclosed in this invention;

[0050] Figure 3 This is a flowchart illustrating the usage method of a PID-based roof concrete vibration control system disclosed in this invention. Detailed Implementation

[0051] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0052] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0053] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0054] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," and "counterclockwise," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0055] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0056] Example 1

[0057] See attached document Figure 1-2 As shown, the present invention provides a technical solution: a PID-based roof concrete vibration control system, including a PID controller, a database, a rule base, a high-frequency vibrator, a moving mechanism, and a simulation module. The PID controller obtains the control quantity by using a linear combination of proportional, integral, and derivative functions based on the deviation between the given input value and the actual output value, and outputs a control signal to the controlled object based on the control quantity.

[0058] The database is used to provide data information to the vibration control system and to store various types of data, facilitating subsequent data retrieval.

[0059] The rule base is derived from the fuzzification of control variables and is the foundation for realizing fuzzy reasoning;

[0060] High-frequency vibrators are used to vibrate roof concrete. A mechanical arm drives the plate on the high-frequency vibrator to vibrate the roof concrete.

[0061] The moving mechanism is used to control the displacement of the high-frequency vibrator. It includes a chassis, a left swivel wheel, and a right swivel wheel. The chassis supports the high-frequency vibrator, and the swivel wheels enable the high-frequency vibrator to move.

[0062] The simulation module uses Simulink for simulation and analysis to evaluate the controller's performance and optimize it according to actual conditions. It includes a fuzzy PID control unit, a motion control unit, a vibrating robot arm control unit, and a data acquisition unit.

[0063] Furthermore, using Simulink's fuzzy PID controller combines neural networks and fuzzy controllers, leveraging the adaptability of neural networks and the empirical nature of fuzzy controllers to achieve better control performance. In the fuzzification stage, input and output variables are transformed into fuzzy sets, that is, they are mapped to fuzzy sets. In the neural network control stage, the fuzzy output variables are transmitted to the neural network controller, and the weights are adaptively adjusted through training data to achieve better control performance. In the defuzzification stage, the output of the neural network controller is mapped to the actual control quantity to obtain a specific control quantity.

[0064] The embodiments of the present invention are also implemented through the following technical solutions.

[0065] In embodiments of the present invention, the rule data of the rule base includes a proportion P, an integral I, and a derivative D, and a proportion coefficient K. P Integral coefficient K I and differential coefficient K D Wherein, the proportionality coefficient K P The integral coefficient K determines the response speed. I The differential coefficient K is used to overcome static error. D Used to overcome vibration.

[0066] In addition, the ratio K P It significantly affects the response speed and is proportional to the adjustment force. If K P If K is too small, the adjustment effect will be slower and take longer. P If the value is too large, the response will be very fast, but the resulting overshoot will also be larger.

[0067] Integral K I It effectively overcomes static errors and can eliminate static errors caused by heat dissipation, resistance, and other factors.

[0068] Differential K D Used to overcome vibration, in only K P and K I Under the influence of the control, the control quantity of the controlled object will oscillate around the expected value. The differential term is controlled according to the rate of change of the error value, which is similar to the damping effect and can make the controlled physical quantity approach zero.

[0069] In embodiments of the present invention, the PID controller further includes a controlled object, which is the high-frequency vibrator and the moving mechanism, and controls the desired value. and actual output error value By performing proportional, integral, and derivative operations respectively, and then summing them, the control law is obtained. This law is then passed to the transfer function to control the controlled object. The error can be expressed as:

[0070] ;

[0071] The formula for controlling the input is as follows:

[0072] ;

[0073] in, It is the derivative.

[0074] In an embodiment of the present invention, the fuzzy PID control unit controls the high-frequency vibrator and the moving mechanism based on the fuzzy PID algorithm;

[0075] The motion control unit is used to receive instructions from the fuzzy PID control unit and control the left and right omnidirectional wheels of the motion mechanism to steer and move.

[0076] The vibration robot arm control unit is used to control the movement of the high-frequency vibrator and its robot arm to carry out vibration work;

[0077] The data acquisition unit is used to collect the displacement of the high-frequency vibrator's robotic arm and the rotation speed and angle of the universal wheels of the moving mechanism.

[0078] In an embodiment of the present invention, the control steps of the fuzzy PID control unit for the high-frequency vibrator robotic arm are as follows:

[0079] a1. Obtain the usage status information of the robotic arm, obtain the tracking error, and establish a mathematical model based on the usage status and error of the robotic arm;

[0080] a2 controls the movement of each joint and collects the movement trajectory of the robotic arm through the data acquisition unit;

[0081] a3 inputs the tracking error into a pre-built fuzzy PID control unit, outputs the corresponding control signal, builds a fuzzy PID controller model, and performs real-time control of the robotic arm based on the control signal.

[0082] In an embodiment of the present invention, step a3, the specific method for constructing the fuzzy PID control unit is as follows: determine the tracking error variable of the robotic arm, determine the composite error term based on the tracking error variable, determine the inherent unknown dynamic function of the robotic arm based on the composite error term, simulate the inherent unknown dynamic function of the robotic arm using Simulink, and construct the simulated PID control unit based on the weight information obtained from the simulation model.

[0083] The tracking error variables include the control electrical signals of the motors at each joint of the robotic arm, the angle of rotation of the robotic arm, displacement, and speed.

[0084] In an embodiment of the present invention, the data acquisition unit collects the rotational speed of the motors of the casters on the moving mechanism. The motor speeds of the left and right casters are W1 and W2, respectively, with a radius of R and a distance of L between the left and right casters. Then, the following motion equations are obtained:

[0085] ;

[0086] ;

[0087] Where V is the speed of the omnidirectional wheel, which is a uniform speed or average speed, and Q is the speed in a generalized sense.

[0088] The turning radius at any given time is:

[0089] ;

[0090] When W1=W2, ρ is infinite, meaning the robot moves in a straight line. When W1>W2, the robot turns right. When W1<W2, the robot turns left. Based on the movement rules of the mobile mechanism, the movement of the mobile mechanism is fuzzily calculated by the fuzzy PID control unit, and motion constraints are applied.

[0091] Example 2

[0092] See attached document Figure 3 As shown in the figure, another embodiment of the present invention provides a method for using a PID-based roof concrete vibration control system, which includes the following steps:

[0093] S1. Establish the system model by using modules in Simulink to build a model of the controlled object.

[0094] S2, Design a fuzzy PID control unit and a neural network. Use the fuzzy logic controller module and neural network module in Simulink to implement the design of the fuzzy PID control unit and the neural network.

[0095] S3 combines a fuzzy PID control unit and a neural network. Simulink is used to combine the fuzzy PID control unit and the neural network, and the fuzzy output variables are transmitted to the neural network controller to adaptively adjust the weights through training data.

[0096] S4. Adjust the control system parameters. Depending on the actual situation, it is necessary to adjust the parameters of the control system. This step can be achieved through the parameter setting module in Simulink.

[0097] S5, Simulation and Analysis: Uses Simulink for simulation and analysis to evaluate the performance of the control system and optimize it based on actual conditions;

[0098] S6, based on optimized control data, controls the vibrator's robotic arm and moving mechanism to perform stable vibration and position movement of the roof concrete through the control system.

[0099] In an embodiment of the present invention, in step S2, the design of the fuzzy PID control unit requires converting the input variables and output variables into fuzzy sets, then setting rules to describe the relationship between the input variables and output variables, and finally optimizing according to the actual situation.

[0100] The design of a neural network module requires determining the input and output variables of the neural network, and then adaptively adjusting the weights based on the training data.

[0101] In addition, to ensure system safety, initial parameters should be set at the beginning of debugging. If the overshoot of the step response generated by the selected parameters exceeds 10%, the proportional coefficient should be reduced and the integral time increased. If there is no overshoot in the step response, but the controlled variable rises too slowly and the transition time is too long, the parameters should be adjusted in the opposite direction.

[0102] When the deviation value is less than the set threshold, the PID controller detects the deviation signal and selects fuzzy PID adaptive control to control the system. When the deviation value is greater than or equal to the set threshold, the system is controlled by adaptive control of the classical PID composite control model.

[0103] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention can have various modifications and variations. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

[0104] It should be understood that the specific order or hierarchy of steps in the disclosed process is an example of an exemplary method. Based on design preferences, it should be understood that the specific order or hierarchy of steps in the process may be rearranged without departing from the scope of this disclosure. The appended method claims provide elements of various steps in an exemplary order and are not intended to limit the scope to the specific order or hierarchy described.

[0105] Those skilled in the art will also understand that the various illustrative logic blocks, modules, circuits, and algorithm steps described in conjunction with the embodiments herein can be implemented as electronic hardware, computer software, or a combination thereof. To clearly illustrate the interchangeability between hardware and software, the various illustrative components, blocks, modules, circuits, and steps described above are generally described in terms of their functionality. Whether such functionality is implemented as hardware or software depends on the specific application and the design constraints imposed on the overall system. Those skilled in the art can implement the described functionality in alternative ways for each specific application; however, such implementation decisions should not be construed as departing from the scope of this disclosure.

[0106] For software implementation, the techniques described in this application can be implemented using modules (e.g., procedures, functions, etc.) that perform the functions described in this application. This software code can be stored in memory units and executed by a processor. The memory units can be implemented within the processor or outside the processor; in the latter case, they are communicatively coupled to the processor via various means, as is well known in the art.

[0107] The foregoing description includes examples of one or more embodiments. It is certainly impossible to describe all possible combinations of components or methods in order to describe the above embodiments, but those skilled in the art will recognize that further combinations and arrangements of the various embodiments are possible. Therefore, the embodiments described herein are intended to cover all such changes, modifications, and variations that fall within the scope of the appended claims. Furthermore, the term "comprising" as used in the specification or claims is interpreted in a manner similar to the term "including," as interpreted when used as a conjunction in the claims. Additionally, the use of any term "or" in the specification of the claims is intended to mean "non-exclusive or."

Claims

1. A PID-based roof concrete vibration control system, characterized in that, It includes a PID controller, a database, a rule base, a high-frequency vibrator, a moving mechanism, and a simulation module. The PID controller obtains the control quantity by using a linear combination of proportional, integral, and derivative functions based on the deviation between the given input value and the actual output value, and outputs a control signal to the controlled object based on the control quantity. The database is used to provide data information to the vibration control system; The rule base is derived from the fuzzification of control variables and forms the basis for fuzzy reasoning. The high-frequency vibrator is used for vibrating the roof concrete. The moving mechanism is used to control the displacement of the high-frequency vibrator, and includes a chassis, a left swivel wheel, and a right swivel wheel; The simulation module uses Simulink for simulation and analysis to evaluate the performance of the controller and optimize it according to the actual situation. It includes a fuzzy PID control unit, a motion control unit, a vibrating robot arm control unit, and a data acquisition unit. The fuzzy PID control unit controls the high-frequency vibrator and the moving mechanism based on the fuzzy PID algorithm; The motion control unit is used to receive instructions from the fuzzy PID control unit and control the motion mechanism to perform displacement. The vibration robot arm control unit is used to control the movement of the high-frequency vibrator and its robot arm to perform vibration work; The data acquisition unit is used to collect the displacement of the high-frequency vibrator's robotic arm and the rotation speed and rotation angle of the universal wheels of the moving mechanism.

2. The PID-based roof concrete vibration control system according to claim 1, characterized in that, The rule data in the rule base includes proportion P, integral I, and derivative D, and the proportional coefficient K. P Integral coefficient K I and differential coefficient K D Wherein, the proportionality coefficient K P The integral coefficient K determines the response speed. I The differential coefficient K is used to overcome static error. D Used to overcome vibration.

3. The PID-based roof concrete vibration control system according to claim 2, characterized in that, The PID controller also includes controlled objects, which are the high-frequency vibrator and the moving mechanism. It controls the desired value... Error value between the actual output and the actual output By performing proportional, integral, and derivative operations respectively, and then summing them, the control law is obtained. This law is then passed to the transfer function to control the controlled object. The error can be expressed as: The formula for controlling the input is as follows: in, It is the derivative.

4. The PID-based roof concrete vibration control system according to claim 1, characterized in that, The control steps of the fuzzy PID control unit for the high-frequency vibrator robotic arm are as follows: a1. Obtain the usage status information of the robotic arm, obtain the tracking error, and establish a mathematical model based on the usage status and error of the robotic arm; a2 controls the movement of each joint and collects the movement trajectory of the robotic arm through the data acquisition unit; a3 inputs the tracking error into a pre-built fuzzy PID control unit, outputs the corresponding control signal, builds a fuzzy PID controller model, and performs real-time control of the robotic arm based on the control signal.

5. A PID-based roof concrete vibration control system according to claim 4, characterized in that, In step a3, the specific method for constructing the fuzzy PID control unit is as follows: determine the tracking error variable of the robotic arm, determine the composite error term based on the tracking error variable, determine the inherent unknown dynamic function of the robotic arm based on the composite error term, simulate the inherent unknown dynamic function of the robotic arm using Simulink, and construct the simulated PID control unit based on the weight information obtained from the simulation model. The tracking error variables include the control electrical signals of the motors at each joint of the robotic arm, the angle of rotation of the robotic arm, displacement, and speed.

6. The PID-based roof concrete vibration control system according to claim 1, characterized in that, The data acquisition unit collects the rotational speeds of the motors of the casters on the moving mechanism. The motor speeds of the left caster and the right caster are W1 and W2, respectively, and the radius is R. The distance between the left and right casters is L. Then, the following motion equations exist: Where V is the speed of the omnidirectional wheel, which is a uniform speed or average speed, and Q is the speed in a generalized sense. The turning radius at any given time is: When W1=W2, ρ is infinite, meaning the robot moves in a straight line. When W1>W2, the robot turns right. When W1<W2, the robot turns left. Based on the movement rules of the moving mechanism, the fuzzy PID control unit performs fuzzy calculations on the movement of the moving mechanism and applies motion constraints.

7. A method for using a PID-based roof concrete vibration control system, applied to the PID-based roof concrete vibration control system according to any one of claims 1 to 6, characterized in that, Includes the following steps: S1. Establish the system model by using modules in Simulink to build a model of the controlled object. S2, Design a fuzzy PID control unit and a neural network. Use the fuzzy logic controller module and neural network module in Simulink to implement the design of the fuzzy PID control unit and the neural network. S3 combines a fuzzy PID control unit and a neural network. Simulink is used to combine the fuzzy PID control unit and the neural network, and the fuzzy output variables are transmitted to the neural network controller to adaptively adjust the weights through training data. S4. Adjust the control system parameters. Depending on the actual situation, it is necessary to adjust the parameters of the control system. This step can be achieved through the parameter setting module in Simulink. S5, Simulation and Analysis: Uses Simulink for simulation and analysis to evaluate the performance of the control system and optimize it based on actual conditions; S6, based on optimized control data, controls the vibrator's robotic arm and moving mechanism to perform stable vibration and position movement of the roof concrete through the control system.

8. The method of using the PID-based roof concrete vibration control system according to claim 7, characterized in that, In step S2, the design of the fuzzy PID control unit requires converting the input and output variables into fuzzy sets, then setting rules to describe the relationship between the input and output variables, and finally optimizing them according to the actual situation. The design of a neural network module requires determining the input and output variables of the neural network, and then adaptively adjusting the weights based on the training data.

Images