Electric clamping jaw control method for cutting off cable based on fuzzy PID (Proportion Integration Differentiation) control

Abstract

The invention relates to the technical field of electric clamping jaw control, in particular to a fuzzy PID (Proportion Integration Differentiation) control-based electric clamping jaw control method for cutting off a cable, which comprises the following steps of: controlling a power source permanent magnet synchronous motor of an electric clamping jaw, and obtaining the position and the rotating speed of a rotor of the permanent magnet synchronous motor through an encoder; a three-closed-loop cascade control structure comprising a position PID controller, a speed PID controller and a current fuzzy PID controller is built, a clamping force PID controller is introduced and used for dynamically adjusting the clamping force of an electric clamping jaw in the cable cutting-off process, the control precision and stability of the clamping force are improved, and the clamping force control precision and stability are improved. An SVPWM algorithm is adopted to modulate the built three-phase inverter circuit so as to reduce the pulsation of the output torque of the motor, and then the robustness and stability of the whole vector control system are improved.

Description

Technical Field

[0001] The invention relates to the technical field of electric clamp control, and in particular to a control method of an electric clamp for cable cutting based on fuzzy PID control. Background Art

[0002] With the rapid development of industrial automation, electric grippers, as actuators in control systems, have been used to improve the safety and reliability of operations in places such as cable cutting where remote control is required or construction conditions are complex. Traditional pneumatic grippers and hydraulic grippers have been gradually replaced by electric grippers due to their poor reliability and inability to achieve continuous and stable output of clamping force. In the field of cable cutting, in order to ensure that the device can be fixed on the cable at multiple angles and remain safe and stable during the cutting process, it is necessary to accurately control the clamping force of the electric grippers.

[0003] The electric gripper is composed of a control system and an execution system. The execution system includes the gripper and a transmission structure. An electric motor is selected as the power source of the transmission structure to drive the gripper to clamp the cable. It is generally a DC motor or a stepper motor, but its control accuracy and operation stability are low. At present, most electric grippers use an AC servo motor control system, with an AC servo motor with a simple structure, easy maintenance and high control accuracy as the controlled object. Its control strategy is mainly direct torque control or vector control. At present, most permanent magnet synchronous motors in AC servo motors are used as power elements. Traditional methods for servo control of permanent magnet synchronous motors include robust control, adaptive control, PID control, etc. With the development of artificial intelligence technology, neural network control, fuzzy control and expert system methods have been introduced into the field of permanent magnet synchronous motor control, but some of the above methods are still in the simulation and test stage. Under the complex construction conditions of cable cutting, how to select a permanent magnet synchronous motor control method with good stability and high reliability to ensure the stable and adjustable clamping force and control accuracy of the electric gripper has become a technical problem that needs to be solved urgently.

[0004] In order to ensure that the cable cutting device can be fastened to the cable to be cut at multiple angles, the electric gripper needs to have a wide range of clamping force output and a certain degree of control accuracy. In the execution system, the clamping force of the electric gripper is to convert the rotational motion of the permanent magnet synchronous motor into the linear motion of the gripper's telescopic rod. In order to accurately obtain the information of the clamping force and realize closed-loop control of the clamping force, the traditional method is to install a pressure sensor at the clamping point of the electric gripper to realize the collection of clamping force and rapid feedback of information. However, the installation of the pressure sensor may lead to high equipment maintenance costs, poor reliability and other problems. The vibration generated by the equipment during the cable cutting operation will seriously affect the service life of the sensor. Therefore, how to estimate the clamping force of the gripper without using a pressure sensor also needs to be solved. Summary of the invention

[0005] The purpose of the present invention is to overcome the defects of the prior art and to propose a control method for an electric clamp for cable cutting based on fuzzy PID control, which can improve the control accuracy and stability of the clamping force of the clamp and is suitable for the on-site working environment of cable cutting.

[0006] To achieve the above object, the present invention adopts the following specific technical solutions:

[0007] The present invention provides a method for controlling an electric clamp for cutting a cable based on fuzzy PID control, comprising:

[0008] The permanent magnet synchronous motor, the power source of the electric gripper, is controlled. The position and speed of the permanent magnet synchronous motor rotor are obtained through the encoder. A three-closed-loop cascade control structure including a position PID controller, a speed PID controller, and a current fuzzy PID controller is built. With the three-closed-loop cascade control structure as the main body, a clamping force PID controller is introduced to dynamically adjust the clamping force of the electric gripper during the cable cutting process.

[0009] By controlling the coordination between the permanent magnet synchronous motor and the transmission structure of the electric gripper, the position control and the clamping force control of the electric gripper are realized; the real-time position θ and real-time speed ω of the permanent magnet synchronous motor rotor are obtained through the encoder; the actual current value i of the three-phase winding of the permanent magnet synchronous motor is collected through the resistance sampling method. a 、i b 、i c ;

[0010] The stator current torque component i is obtained based on the field-oriented vector control method of the permanent magnet synchronous motor. q With motor torque T e Based on the pressure sensor-free electric gripper control scheme, the stator current torque component i is obtained. q Linear relationship with the gripper force F;

[0011] The real-time position θ and target position θ of the permanent magnet synchronous motor rotor obtained by the encoder * The input is sent to the position PID controller to realize the position outer loop control. The real-time position θ is obtained through the differential link to obtain the motor speed information ω and is compared with the given speed ω. * The deviation value after difference is input into the speed PID controller to realize speed closed-loop control. The parameters K of position PID controller and speed PID controller are P , K I , K D Adjustment is done through trial and error, simulation and field testing;

[0012] The actual current value i of the three-phase winding of the permanent magnet synchronous motor a 、i b 、i cAfter Clark transformation and Park transformation, the excitation current component i of the motor feedback is obtained. d and the stator current torque component i q , and the target current output by the speed PID controller After comparison operation, it is input into the current fuzzy PID controller;

[0013] Stator current torque component command in current fuzzy PID controller The output of the speed PID controller and the clamping force PID controller output Add them together and add them to the stator current torque component i fed back by the permanent magnet synchronous motor q After comparison operation, it is input into the current fuzzy PID controller;

[0014] Clamping force PID control loop input command F * When the cable is in the state of being cut, it is a fixed value to maintain the stable output of the electric clamping force. During the cable cutting process, the command F * The dynamic change value is determined by the cutting depth. The clamping force F of the clamping jaws is dynamically adjusted according to the cable cutting state through the feedback of the actual clamping force F. The clamping force PID controller parameters are adjusted through trial and error, simulation and a large number of field tests.

[0015] Output u in current fuzzy PID controller d and u q After the Park inverse transform, the voltage vector signals under the stationary coordinates α and β axes are obtained and the target voltage vector u is synthesized. out , which is input into the SVPWM algorithm module to obtain the PWM conduction waveform of each IGBT in the two-level three-phase voltage inverter, and then generate the target current vector to drive the two-level three-phase voltage inverter to form a current closed-loop control.

[0016] Furthermore, the electric gripper control method adopts pressure sensorless control by using the stator current torque component i q Estimate the clamping force F of the gripper and establish the mathematical model of the permanent magnet synchronous motor under the dq rotating coordinate axis, including the stator voltage equation, stator flux equation, and electromagnetic torque equation;

[0017] The stator voltage equation is as follows:

[0018]

[0019] The stator flux equation is as follows:

[0020]

[0021] The electromagnetic torque equation is as follows:

[0022] T e =n p ψ f i q +n p (L d -L q )i d i q ;

[0023] Among them, ψ d , q are the d-axis and q-axis flux of the permanent magnet synchronous motor, L d , L q are the d-axis and q-axis inductances of the motor respectively, and p is the differential operator, that is, n p is the number of pole pairs of the permanent magnet synchronous motor, ψ f is the excitation flux of the permanent magnet of the motor rotor;

[0024] Adopt i d =0 vector control mode, the electromagnetic torque equation is obtained:

[0025]

[0026] Among them, K T is the torque constant of the permanent magnet synchronous motor. Ignoring the friction between the gripper transmission structure, the gripper force is approximately proportional to the electromagnetic torque. F = K F T e , K F is the ratio coefficient of the clamping force to the electromagnetic torque, and the stator current torque component i is obtained q The relationship between the clamping force F and the clamping force F is F = K s i q , where K s K is the ratio coefficient of the clamping force of the clamp and the stator current torque component, s =K T ·K F .

[0027] Furthermore, both the position PID controller and the speed PID controller adopt incremental PID control, and the current fuzzy PID controller adopts fuzzy PID control; the incremental PID control algorithms of the position PID controller and the speed PID controller are as follows:

[0028] Δu(k)=K P [e(k)-e(k-1)]+K I e(k)+K D [e(k)-2e(k-1)+e(k-2)];

[0029] Where, Δe(k)=e(k)-e(k-1), e(k) represents the deviation value of the position and speed input by the kth sampling controller, e(k)=θ * (k)-θ(k), e(k)=ω * (k)-ω(k).

[0030] Furthermore, the control process of the current fuzzy PID controller is as follows:

[0031] Step 1: Obtain the real-time excitation current component i of the permanent magnet synchronous motor under the rotating coordinate axis d , stator current torque component i q and current loop target current And calculate the real-time deviation of each current component;

[0032] Step 2: Perform fuzzy processing on the deviation of each current component and its deviation change rate, and use the membership function to process the fuzzy subsets of the input and output quantities to obtain their distribution on the domain;

[0033] Step 3: Establish fuzzy rules about input and output according to the domain corresponding to the processed input, and obtain fuzzy output according to the fuzzy rules;

[0034] Step 4: Defuzzify the fuzzy output to get ΔK P , ΔK I , ΔK D The exact value of K P , K I , K D The control parameters of the current fuzzy PID controller are obtained by adding them;

[0035] Step 5: The output current torque component i after being processed by the current fuzzy PID controller q Compare it with the expected value, adjust the fuzzy rules according to the error, optimize the current fuzzy PID controller parameters and achieve the expected control target.

[0036] Furthermore, the input and output of the current fuzzy PID controller use the commonly used 7 fuzzy subsets, namely negative large, negative medium, negative small, zero, positive small, positive medium and positive large; then the Gaussian membership function is used for the input current deviation signal and the rate of change, and the triangular membership function is used for each fuzzy subset of the output, and the distribution of the input and output values ​​in the domain (-6, 6) is obtained;

[0037] In the fuzzy processing, when the fuzzy subset corresponding to the current deviation change rate is positive or positive, increase the proportional adjustment coefficient K P; When the fuzzy subset corresponding to the current deviation change rate is positive small, zero or negative small, reduce the differential adjustment coefficient K D When the fuzzy subset corresponding to the current deviation change rate is negative or medium, and the fuzzy subset corresponding to the current deviation is positive or medium, the proportional adjustment coefficient K is increased at the same time. P , integral adjustment coefficient K I , reduce the differential adjustment coefficient K D ;

[0038] In the defuzzification process, the area center method is used to take the abscissa value of the center of gravity of the figure formed by the fuzzy membership function curve and the abscissa axis as the output value, so that the permanent magnet synchronous motor current loop can obtain better dynamic response.

[0039] Furthermore, the steps of using the SVPWM algorithm module to drive a two-level three-phase voltage source inverter are as follows:

[0040] Step 1: The output voltage signal of the current fuzzy PID controller is transformed by Park inverse transformation to obtain the voltage component u of the synthetic voltage vector in the α-β coordinate system α 、u β ;

[0041] Step 2: Obtain the resultant voltage vector u out The sector position is calculated and the time it acts on each sector is calculated. According to the volt-second balance principle, three effective vectors are selected and the action time of the synthesized adjacent non-zero vectors and zero vector is calculated in turn.

[0042] Step 3: Determine the action order of the three vectors, obtain the switching position of PWM, and generate six PWM signals to control the on and off of the three-phase inverter circuit.

[0043] The present invention can achieve the following technical effects:

[0044] 1. The present invention adopts a vector control method of magnetic field oriented control for the permanent magnet synchronous motor. The d-axis component of the stator current is 0, and the rotor flux is decoupled from the q-axis component of the stator current, so that the mathematical model of the permanent magnet synchronous motor is greatly simplified. At this time, the q-axis component of the stator current and the electromagnetic torque are in a simple linear relationship, and the motor can output the maximum torque, and can also respond to the position and torque accurately and quickly.

[0045] 2. A three-closed-loop cascade PID control system of position, speed and current is adopted. The outermost layer is the position control loop, the second layer is the speed control loop, and the inner loop is the current control loop. The three-closed-loop control structure enables the system to position quickly and accurately and ensure the output stability and accuracy of the clamping force of the gripper. The output of the position loop and the speed loop is limited to reduce the impact of excessive speed changes on the system structure. At the same time, it ensures that the permanent magnet synchronous motor can maintain the clamping force of the gripper when it is stalled. When the motor switches between the position control state and the clamping force control state, the limiting processing of the position loop and the speed loop ensures smooth switching between the two states.

[0046] 3. The control scheme without pressure sensor is adopted to overcome the shortcomings of reduced system reliability and high maintenance cost caused by installing pressure sensor at the end of the clamping point of traditional electric grippers. The method of estimating the gripping force of the grippers by sampling the winding current of the permanent magnet synchronous motor instead of the pressure sensor is more suitable for the on-site working environment of cable cutting.

[0047] 4. The current loop adopts fuzzy PID control. Since the permanent magnet synchronous motor control system itself has certain nonlinearity, time-varying and strong coupling, the traditional PID control cannot effectively deal with uncertain information, and the control parameters are fixed. When disturbed, the parameters need to be manually readjusted, the response speed is slow, and the ideal control effect cannot be achieved. Fuzzy PID control has the advantages of good stability and strong robustness. When the controlled object or the external environment changes, the PID control parameters can be adjusted online in real time, the response speed of the current can be accelerated, and the control accuracy and stability of the clamping force of the clamp can be improved, which is very suitable for practical applications on site.

[0048] 5. Based on the three-closed-loop cascade PID control structure of the permanent magnet synchronous motor, the PID control loop of the electric gripper's clamping force is introduced to achieve stable and rapid adjustment of the electric gripper's clamping force during cable cutting.

[0049] 6. The SVPWM algorithm is used to modulate the three-phase inverter circuit. Compared with the traditional SPWM algorithm, the SVPWM algorithm has a higher utilization rate of the inverter DC voltage and a smaller torque ripple coefficient of the permanent magnet synchronous motor, which improves the robustness of the control system, reduces external and internal interference, and improves the control effect and accuracy of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 It is a schematic diagram of a front three-dimensional structure of a portable wireless remote cable cutting electric clamp provided according to an embodiment of the present invention;

[0051] Figure 2 is a schematic diagram of a method for controlling an electric gripper according to an embodiment of the present invention;

[0052] Figure 3is a block diagram of an electric gripper control method provided according to an embodiment of the present invention;

[0053] Figure 4 are parameters of a permanent magnet synchronous motor provided according to an embodiment of the present invention;

[0054] Figure 5 It is a structure diagram of current loop adaptive fuzzy PID control in the electric gripper control method provided according to an embodiment of the present invention.

[0055] Figure 6 is K provided according to an embodiment of the present invention P Fuzzy tuning rules for

[0056] Figure 7 is K provided according to an embodiment of the present invention I Fuzzy tuning rules for

[0057] Figure 8 is K provided according to an embodiment of the present invention D Fuzzy tuning rules. DETAILED DESCRIPTION

[0058] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. In the following description, the same modules are represented by the same reference numerals. In the case of the same reference numerals, their names and functions are also the same. Therefore, the detailed description thereof will not be repeated.

[0059] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and do not constitute a limitation of the present invention.

[0060] The embodiment of the present invention provides a method for controlling an electric clamp for cutting a cable based on fuzzy PID control. Figure 1 The figure is a schematic diagram of the structure of an electric gripper for cable cutting. The electric gripper consists of a remote operation terminal, an electric gripper controller, a permanent magnet synchronous motor, a transmission structure and an aluminum alloy gripper. The remote operation terminal and the electric gripper controller use Bluetooth for wireless communication. According to the outer diameter of cables of different types, the desired opening and closing position of the aluminum alloy gripper is set through the remote operation terminal and transmitted to the controller through the wireless Bluetooth module. At the same time, the wireless signal fed back by the electric gripper monitors and controls the action of the electric gripper in real time.

[0061] Figure 2 This is the schematic diagram of the electric gripper control method. Figure 3 The block diagram of the electric gripper control method is as follows: Figure 2 and Figure 3 As shown, the control method includes:

[0062] The electric gripper control method uses the permanent magnet synchronous motor rotor shaft to drive the gripper mechanical transmission structure to achieve position control and gripping force control of the aluminum alloy gripper;

[0063] The permanent magnet synchronous motor, the power source of the electric gripper, is controlled. The position and speed of the permanent magnet synchronous motor rotor are obtained through the encoder. A three-closed-loop cascade control structure including position PID controller, speed PID controller, and current fuzzy PID controller is built.

[0064] Based on the three-loop cascade control structure, a clamping force PID controller is introduced to dynamically adjust the clamping force of the electric clamp during the cable cutting process;

[0065] By controlling the coordination between the permanent magnet synchronous motor of the electric gripper and the transmission structure of the electric gripper, the position control and the clamping force control of the electric gripper are realized;

[0066] The encoder installed at the tail of the permanent magnet synchronous motor is used to obtain the real-time position θ and real-time speed ω of the permanent magnet synchronous motor rotor; the actual current value i of the three-phase winding of the permanent magnet synchronous motor is collected by the resistance sampling method. a 、i b 、i c ;

[0067] The stator current torque component i is obtained based on the field-oriented vector control method of the permanent magnet synchronous motor. q With motor torque T e Based on the pressure sensor-free electric gripper control scheme, the stator current torque component i is obtained. q Linear relationship with the gripper force F;

[0068] The real-time position θ and target position θ of the permanent magnet synchronous motor rotor obtained by the encoder * The input is sent to the position PID controller to realize the position outer loop control. The real-time position θ is obtained through the differential link to obtain the motor speed information ω and is compared with the given speed ω. * The deviation value after difference is input into the speed PID controller to realize speed closed-loop control. The parameters K of position PID controller and speed PID controller are P , K I , K D Adjustment is done through trial and error, simulation and field testing;

[0069] The actual current value i of the three-phase winding of the permanent magnet synchronous motor a 、i b 、i c After Clark transformation and Park transformation, the excitation current component i of the motor feedback is obtained. d and the stator current torque component i q , and the target current output by the speed PID controller After comparison operation, it is input into the current fuzzy PID controller;

[0070] Stator current torque component command in current fuzzy PID controller The output of the speed PID controller and the clamping force PID controller output Add them together and add them to the stator current torque component i fed back by the permanent magnet synchronous motor q After comparison operation, it is input into the current fuzzy PID controller;

[0071] Output u in current fuzzy PID controller d and u q After the Park inverse transform, the voltage vector signals under the stationary coordinates α and β axes are obtained and the target voltage vector u is synthesized. out , which is input into the SVPWM algorithm module to obtain the PWM conduction waveform of each IGBT in the two-level three-phase voltage inverter, and then generate the target current vector to drive the two-level three-phase voltage inverter to form a current closed-loop control.

[0072] The electric gripper control method adopts pressure sensorless control by using the stator current torque component i q The clamping force F of the gripper is estimated, and the mathematical model of the permanent magnet synchronous motor under the dq rotating coordinate axis is established, including the stator voltage equation, stator flux equation, and electromagnetic torque equation.

[0073] Stator voltage equation:

[0074]

[0075] The stator flux equation is as follows:

[0076]

[0077] The electromagnetic torque equation is as follows:

[0078] T e =n p ψ f i q +n p (L d -L q )i d i q ;

[0079] Among them, ψ d , q are the d-axis and q-axis flux of the permanent magnet synchronous motor, L d , L q are the d-axis and q-axis inductances of the motor respectively, and p is the differential operator, that is, n p is the number of pole pairs of the permanent magnet synchronous motor, ψ f is the excitation flux of the permanent magnet of the motor rotor.

[0080] Adopt i d =0 vector control mode, the electromagnetic torque equation is obtained:

[0081]

[0082] Among them, K T is the torque constant of the permanent magnet synchronous motor; ignoring the friction between the gripper transmission structure, the gripper force is approximately proportional to the electromagnetic torque F = K F T e , K F is the ratio coefficient of the clamping force to the electromagnetic torque, and the stator current torque component i is obtained q The relationship between the clamping force F and the clamping force F is F = K s i q , where K s K is the ratio coefficient of the clamping force of the clamp and the stator current torque component, s =K T ·K F .

[0083] The electric gripper control method adopts a control structure based on a three-closed-loop cascade control structure, and introduces the electric gripper clamping force PID controller into the main control structure. The position loop and speed loop in the three-closed-loop cascade control structure both adopt PID control, and the current loop adopts fuzzy PID control. In order to achieve precise control of the gripper position and speed, the position PID controller and the speed PID controller are controlled by an incremental PID control algorithm combined with the vector control method of the permanent magnet synchronous motor:

[0084] Δu(k)=K P [e(k)-e(k-1)]+K I e(k)+K D [e(k)-2e(k-1)+e(k-2)];

[0085] Where, Δe(k)=e(k)-e(k-1), e(k) represents the deviation value of the position and speed input by the kth sampling controller, e(k)=θ * (k)-θ(k), e(k)=ω * (k)-ω(k).

[0086] The embodiment of the present invention performs modeling and simulation analysis on the position loop and speed loop in the electric gripper control method, wherein the relevant parameters of the permanent magnet synchronous motor are as follows: Figure 4 shown.

[0087] Controller parameter K P , K I , K D After trial and error, simulation and a large number of field tests, the three parameters were adjusted and optimized to complete the parameter setting. For the position loop PID controller, it is mainly used to output the target speed, K D It should be as small as possible, but in order to speed up the response speed, the position loop PID control parameters are set to 200, 0.5, and 1. Since the speed loop PID control parameters are not accurate after theoretical transfer function calculation, simulation is used for manual adjustment. After a large number of field tests and verifications, the speed loop PID control parameters are 0.5, 20, and 0.3.

[0088] PID controller parameters K P is the proportional adjustment coefficient, which is used to speed up the system response and reduce the deviation. P Too small, the response speed is too slow, K P If it is too large, the response speed will be fast and high-frequency oscillation will occur. K D Control, K I is the integral adjustment coefficient, which is used to eliminate the static error generated by the system. I If it is too large, integral saturation will occur and cause large overshoot. I If it is too small, the static error of the system will become larger and difficult to eliminate. D is the differential adjustment coefficient, which is used to reduce the maximum overshoot, but K D Too large a value will cause low-frequency oscillation in the system and slow down the response speed.

[0089] Clamping force PID control loop input command F * When the cable is in the state of being cut, it is a fixed value to maintain the stable output of the electric clamping force. During the cable cutting process, the command F * The cutting depth determines the dynamic change value. Through the feedback of the actual clamping force F, the clamping force of the clamp is adjusted dynamically and quickly according to the cable cutting state. The clamping force PID controller parameter K P , K I , K D Through trial and error, simulation and a large number of field tests, they were obtained to be 0.3, 10 and 0.7 respectively.

[0090] In order to speed up the current response speed and increase the control accuracy and stability of the clamping force of the clamp, fuzzy PID control is adopted for the current inner loop. Figure 5 This is a current loop adaptive fuzzy PID control structure diagram in the electric gripper control system proposed by the present invention. The design of the current loop adaptive fuzzy PID controller includes the following steps:

[0091] Step 1: Obtain the real-time excitation current component i of the permanent magnet synchronous motor under the rotating coordinate axisd , stator current torque component i q and current loop target current And calculate the real-time deviation e and deviation change rate e of each current component c ;

[0092] Step 2: Obtain the real-time deviation e and deviation change rate e c As the input of the two-dimensional fuzzy controller, the deviation e of each current component and its deviation change rate e c Carry out fuzzification processing, use membership function to process the fuzzy subsets of input and output quantities, and obtain their distribution on the domain;

[0093] Step 3: Establish fuzzy rules about input and output according to the domain corresponding to the processed input, and obtain fuzzy output according to the fuzzy rules;

[0094] Step 4: Defuzzify the fuzzy output to obtain the current fuzzy PID controller output ΔK P , ΔK I , ΔK D The exact value of K P , X I , K D The control parameters of the current fuzzy PID controller are obtained by adding them;

[0095] Step 5: The output current torque component i after being processed by the current fuzzy PID controller q With reference value By comparison, the fuzzy rules are adjusted according to the error, and the PID controller parameters are continuously optimized to achieve the expected control target.

[0096] In the above step 2, since the range of input and output variables may not match the corresponding domain, it is necessary to introduce a fuzzy factor to map the input variable range into the domain, and introduce a defuzzification factor to map the output variable domain into the output variable range. Adjust these two factors to set the input and output action strength of the current fuzzy PID controller. The fuzzy factor is The domain of the fuzzy subset of the input quantity is [-n,n], and the continuous domain is [X a ,X b ], the defuzzification factor is Among them, the output continuous domain is [Y a ,Y b ], the domain of fuzzy subset is [-m,m].

[0097] The input and output of the current fuzzy PID controller both use the commonly used 7 fuzzy subsets, namely negative large (NB), negative middle (NM), negative small (NS), zero (ZO), positive small (PS), positive middle (PM) and positive large (PB). In order to improve the anti-interference and self-adaptive ability of the current loop to the outside world, the Gaussian membership function is used for the input current deviation signal and the rate of change. In order to improve the response speed of the system to the feedback signal, the triangular membership function is used for each fuzzy subset of the output, and it is carried out within the range of the domain (-6, 6) to obtain the distribution of the input and output values ​​​​in the domain.

[0098] According to the fuzzy control algorithm, different PID control parameters can be output in real time by formulating fuzzy rules. The fuzzy rules can be adjusted in real time according to the feedback effect of the control system, and the input current component deviation e and its deviation change rate e c Applying fuzzy control rules to logically infer the controller fuzzy output ΔK P , ΔK I , ΔK D , the formulated fuzzy control rules are input into the fuzzy PID during simulation. P The fuzzy tuning rules are set as Figure 6 As shown, K I The fuzzy tuning rules are as follows Figure 7 As shown, K D The fuzzy tuning rules are set as Figure 8 shown.

[0099] In the fuzzy processing, when the fuzzy subset corresponding to the current deviation change rate is positive or positive, increase the proportional adjustment coefficient K P ; When the fuzzy subset corresponding to the current deviation change rate is positive small, zero or negative small, reduce the differential adjustment coefficient K D When the fuzzy subset corresponding to the current deviation change rate is negative or medium, and the fuzzy subset corresponding to the current deviation is positive or medium, the proportional adjustment coefficient K is increased at the same time. P , integral adjustment coefficient K I , reduce the differential adjustment coefficient K D .

[0100] According to the above fuzzy rules, fuzzy reasoning can be performed to obtain ΔK P , ΔK I , ΔK D The fuzzy output of the controller is obtained by using the Mamdani fuzzy inference algorithm. After the fuzzy output is obtained, the output quantity is defuzzified to obtain the accurate output value of the controller.

[0101] In the defuzzification process, the area center method is used to take the abscissa value of the center of gravity of the figure surrounded by the fuzzy membership function curve and the abscissa axis as the output value, and then multiply it by the defuzzification factor to obtain the fuzzy PID controller output ΔK P , ΔK I , ΔK D The exact value of the original PID controller and the initial value K P , K I , K D Add as the control parameter of the current PID controller, which is expressed as follows:

[0102]

[0103] where {e,e c}Obtained by querying the fuzzy rule table.

[0104] After simulation and a large number of field tests, the fuzzy tuning rules were adjusted and the fuzzy PID controller parameters were obtained to be 3.4, 0.2, and 0.63, respectively. The fuzzy factor K input is 0.8, and the adjusted defuzzification factor K output is 0.15, at this time the electronic current torque component i q Can quickly track the target current value The curve has a small oscillation component and no overshoot, and has good dynamic characteristics. After SVPWM modulation, the three-phase current output by the permanent magnet synchronous motor presents a symmetrical sine wave with small harmonic components and stable output torque. It can still maintain a stable and continuous clamping force when the electric gripper is in the clamping force control state, and can respond quickly to changes in the system.

[0105] In the established three-closed-loop PID control system simulation model, the outputs of the position loop and speed loop are limited, thereby reducing the impact of excessive speed changes on the system structure. At the same time, it ensures that the permanent magnet synchronous motor can maintain the clamping force of the gripper when it is stalled. When the motor switches between the position control state and the clamping force control state, the limiting processing of the position loop and the speed loop ensures smooth switching between the two states.

[0106] The SVPWM technology is used to drive the two-level three-phase voltage inverter, and the output signal drives the permanent magnet synchronous motor to obtain a stable output torque. To build the SVPWM module in the control system, the following steps should be included:

[0107] Step 1: The output voltage signal of the current inner loop fuzzy PID controller is transformed by inverse Park to obtain the voltage component u of the synthetic voltage vector in the α-β coordinate system α 、u β ;

[0108] Step 2: Obtain the resultant voltage vector u outThe sector position is calculated and the time it acts on each sector is calculated. According to the volt-second balance principle, three effective vectors are selected and the action time of the synthesized adjacent non-zero vectors and zero vector is calculated in turn.

[0109] Step 3: Determine the action order of the three vectors, obtain the switching position of PWM, and generate six PWM signals to control the on and off of the three-phase inverter circuit.

[0110] After parameter tuning, for the given position reference signal, the permanent magnet synchronous motor can respond quickly and reach the specified position, while meeting the stability requirements of the system. For the device vibration caused by the on-site cable cutting test and the real-time force changes of the mechanical structure of some positions inside the device caused by the cable cutting saw during the follow-up cutting and retracting process, the permanent magnet synchronous motor can adaptively tune the control parameters and adjust the output torque in a relatively short time to stabilize the working state of the device, indicating that the permanent magnet synchronous motor control system has strong anti-interference ability and good adaptive ability.

[0111] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0112] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

[0113] The above specific implementations of the present invention do not constitute a limitation on the protection scope of the present invention. Any other corresponding changes and modifications made based on the technical concept of the present invention should be included in the protection scope of the claims of the present invention.

Claims

1. A method for controlling an electric clamp for cable cutting based on fuzzy PID control, characterized in that: include: The permanent magnet synchronous motor, the power source of the electric gripper, is controlled. The position and speed of the permanent magnet synchronous motor rotor are obtained through the encoder. A three-closed-loop cascade control structure including a position PID controller, a speed PID controller, and a current fuzzy PID controller is built. With the three-closed-loop cascade control structure as the main body, a clamping force PID controller is introduced to dynamically adjust the clamping force of the electric gripper during the cable cutting process. By controlling the coordination between the permanent magnet synchronous motor and the transmission structure of the electric gripper, the position control and the clamping force control of the electric gripper are realized; the real-time position θ and real-time speed ω of the permanent magnet synchronous motor rotor are obtained through the encoder; the actual current value i of the three-phase winding of the permanent magnet synchronous motor is collected through the resistance sampling method. a 、i b 、i c ; The stator current torque component i is obtained based on the field-oriented vector control method of the permanent magnet synchronous motor. q With motor torque T e Based on the pressure sensor-free electric gripper control scheme, the stator current torque component i is obtained. q Linear relationship with the gripper force F; The real-time position θ and target position θ of the permanent magnet synchronous motor rotor obtained by the encoder * The input is sent to the position PID controller to realize the position outer loop control. The real-time position θ is obtained through the differential link to obtain the motor speed information ω and is compared with the given speed ω. * The deviation value after difference is input into the speed PID controller to realize speed closed-loop control. The parameters K of position PID controller and speed PID controller are P , K I , K D Adjustment is done through trial and error, simulation and field testing; The actual current value i of the three-phase winding of the permanent magnet synchronous motor a 、i b 、i c After Clark transformation and Park transformation, the excitation current component i of the motor feedback is obtained. d and the stator current torque component i q , and the target current output by the speed PID controller After comparison operation, it is input into the current fuzzy PID controller; Stator current torque component command in current fuzzy PID controller The output of the speed PID controller and the clamping force PID controller output Add them together and add them to the stator current torque component i fed back by the permanent magnet synchronous motor q After comparison operation, it is input into the current fuzzy PID controller; Clamping force PID control loop input command F * When the cable is in the state of being cut, it is a fixed value to maintain the stable output of the electric clamping force. During the cable cutting process, the command F * The dynamic change value is determined by the cutting depth. The clamping force F of the clamping jaws is dynamically adjusted according to the cable cutting state through the feedback of the actual clamping force F. The clamping force PID controller parameters are adjusted through trial and error, simulation and a large number of field tests. Output u in current fuzzy PID controller d and u q After the Park inverse transform, the voltage vector signals under the stationary coordinates α and β axes are obtained and the target voltage vector u is synthesized. out , which is input into the SVPWM algorithm module to obtain the PWM conduction waveform of each IGBT in the two-level three-phase voltage inverter, and then generate the target current vector to drive the two-level three-phase voltage inverter to form a current closed-loop control.

2. The method for controlling the electric clamp for cable cutting based on fuzzy PID control according to claim 1, characterized in that: The electric gripper control method adopts pressure sensorless control by using the stator current torque component i q Estimate the clamping force F of the gripper and establish the mathematical model of the permanent magnet synchronous motor under the dq rotating coordinate axis, including the stator voltage equation, stator flux equation, and electromagnetic torque equation; The stator voltage equation is as follows: The stator flux equation is as follows: The electromagnetic torque equation is as follows: T e =n p ψ f i q +n p (L d -L q )i d i q ; Among them, ψ d , q are the d-axis and q-axis flux of the permanent magnet synchronous motor, L d , L q are the d-axis and q-axis inductances of the motor respectively, and p is the differential operator, that is, n p is the number of pole pairs of the permanent magnet synchronous motor, ψ f is the excitation flux of the permanent magnet of the motor rotor; Adopt i d =0 vector control mode, the electromagnetic torque equation is obtained: Among them, K T is the torque constant of the permanent magnet synchronous motor. Ignoring the friction between the gripper transmission structure, the gripper force is approximately proportional to the electromagnetic torque. F = K F T e , K F is the ratio coefficient of the clamping force to the electromagnetic torque, and the stator current torque component i is obtained q The relationship between the clamping force F and the clamping force F is F = K s i q , where K s K is the ratio coefficient of the clamping force of the clamp and the stator current torque component, s =K T ·K T .

3. The method for controlling the electric clamp for cable cutting based on fuzzy PID control according to claim 1, characterized in that: Both the position PID controller and the speed PID controller adopt incremental PID control, and the current fuzzy PID controller adopts fuzzy PID control; the incremental PID control algorithms of the position PID controller and the speed PID controller are as follows: Δu(k)=K P [E(k)-E(k-1)]+K I e(k)+K D [e(k)-2e(k-1)+e(k-2)]; Where, Δe(k)=E(k)-e(k-1), e(k) represents the deviation value of the position and speed input by the kth sampling controller, e(k)=θ * (k)-θ(k), e(K)=ω * (K)-ω(K).

4. The method for controlling the electric clamp for cable cutting based on fuzzy PID control according to claim 1, characterized in that: The control process of the current fuzzy PID controller is as follows: Step 1: Obtain the real-time excitation current component i of the permanent magnet synchronous motor under the rotating coordinate axis d , stator current torque component i q and current loop target current And calculate the real-time deviation of each current component; Step 2: Fuzzify the deviation of each current component and its deviation change rate, and use the membership function to process the fuzzy subsets of the input and output quantities to obtain their distribution in the domain; Step 3: Establish fuzzy rules about input and output according to the domain corresponding to the processed input, and obtain fuzzy output according to the fuzzy rules; Step 4: Defuzzify the fuzzy output to get ΔK P , ΔK I , ΔK D The exact value of K P , K I , K D The control parameters of the current fuzzy PID controller are obtained by adding them; Step 5: The output current torque component i after being processed by the current fuzzy PID controller q Compare it with the expected value, adjust the fuzzy rules according to the error, optimize the current fuzzy PID controller parameters and achieve the expected control target.

5. The method for controlling the electric clamp for cable cutting based on fuzzy PID control according to claim 4, characterized in that: The input and output of the current fuzzy PID controller use the commonly used 7 fuzzy subsets, namely negative large, negative medium, negative small, zero, positive small, positive medium and positive large; then the Gaussian membership function is used for the input current deviation signal and the rate of change, and the triangular membership function is used for each fuzzy subset of the output, and the distribution of the input and output values ​​in the domain (-6, 6) is obtained; In the fuzzy processing, when the fuzzy subset corresponding to the current deviation change rate is positive or positive, increase the proportional adjustment coefficient K P ; When the fuzzy subset corresponding to the current deviation change rate is positive small, zero or negative small, reduce the differential adjustment coefficient K D When the fuzzy subset corresponding to the current deviation change rate is negative or medium, and the fuzzy subset corresponding to the current deviation is positive or medium, the proportional adjustment coefficient K is increased at the same time. P , integral adjustment coefficient K I , reduce the differential adjustment coefficient K D ; In the defuzzification process, the area center method is used to take the abscissa value of the center of gravity of the figure formed by the fuzzy membership function curve and the abscissa axis as the output value, so that the permanent magnet synchronous motor current loop can obtain better dynamic response.

6. The method for controlling the electric clamp for cable cutting based on fuzzy PID control according to claim 1, characterized in that: The steps of using the SVPWM algorithm module to drive a two-level three-phase voltage inverter are as follows: Step 1: The output voltage signal of the current fuzzy PID controller is transformed by Park inverse transformation to obtain the voltage component u of the synthetic voltage vector in the α-β coordinate system α 、u β ; Step 2: Obtain the resultant voltage vector u out The sector position is calculated and the time it acts on each sector is calculated. According to the volt-second balance principle, three effective vectors are selected and the action time of the synthesized adjacent non-zero vectors and zero vector is calculated in turn. Step 3: Determine the action order of the three vectors, obtain the switching position of PWM, and generate six PWM signals to control the on and off of the three-phase inverter circuit.

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