A hydraulic joint control method based on AMESim-Simulink joint simulation

Abstract

The present invention discloses a hydraulic joint control method based on AMESim-Simulink co-simulation, which relates to the field of robot hydraulic joint control. The method includes S1: building a robot hydraulic joint simulation model in AMESim; S2: establishing a robot hydraulic joint angle calculation model in Simulink; S3: establishing a robot hydraulic joint fuzzy PID model in Simulink; S4: using Simulink as an intermediate simulation platform, transmitting the hydraulic cylinder piston displacement signal in the robot hydraulic joint simulation model obtained in S1 to Simulink, using the robot hydraulic joint angle calculation model obtained in S2 to convert the hydraulic cylinder piston displacement signal into an angle signal, and outputting the electro-hydraulic servo valve current signal to the electro-hydraulic servo valve in AMESim through the fuzzy PID controller in the robot hydraulic joint fuzzy PID model obtained in S3, thereby realizing precise control of the robot hydraulic joint. The present invention verifies that the use of AMESim-Simulink co-simulation can more accurately control the robot hydraulic joint.

Description

Technical Field

[0001] The present invention belongs to the field of robot hydraulic joint control, and in particular relates to a hydraulic joint control method based on AMESim-Simulink joint simulation. Background Art

[0002] At present, electro-hydraulic servo valves are rarely used for control of robot hydraulic joints. Compared with the more commonly used electromagnetic proportional reversing valves, electro-hydraulic servo valves, as a multi-stage amplified closed-loop hydraulic servo system, have faster response speed and higher control accuracy.

[0003] However, the theoretical derivation of the transfer function and mathematical model of the electro-hydraulic servo valve is very complicated and not convenient for analysis and calculation. In order to further improve the control accuracy of the robot hydraulic joint under the action of the electro-hydraulic servo valve, the present invention proposes a hydraulic joint control method based on AMESim-Simulink joint simulation. Summary of the Invention

[0004] The present invention provides a hydraulic joint control method based on AMESim-Simulink joint simulation to solve the problem of difficulty in building a mathematical model of the current electro-hydraulic servo valve proposed in the above background technology and to improve the control accuracy of the robot hydraulic joint.

[0005] The specific technical solutions adopted in the present invention are as follows:

[0006] The present invention provides a hydraulic joint control method based on AMESim-Simulink joint simulation, which is as follows:

[0007] S1: Build a robot hydraulic joint simulation model in AMESim;

[0008] S2: Establish a robot hydraulic joint angle calculation model in Simulink;

[0009] S3: Establish a fuzzy PID model of the robot hydraulic joint in Simulink;

[0010] S4: Using Simulink as the intermediate simulation platform, the hydraulic cylinder piston displacement signal in the robot hydraulic joint simulation model obtained in S1 is transmitted to Simulink. The robot hydraulic joint angle calculation model obtained in S2 is used to convert the hydraulic cylinder piston displacement signal into an angle signal. The fuzzy PID controller in the robot hydraulic joint fuzzy PID model obtained in S3 outputs the electro-hydraulic servo valve current signal to the electro-hydraulic servo valve in AMESim to achieve precise control of the robot hydraulic joint.

[0011] Preferably, the S1 is as follows:

[0012] S1.1: Build an electro-hydraulic servo valve model in AMESim based on the electro-hydraulic servo valve structural schematic. The electro-hydraulic servo valve model includes a torque motor sub-model, a nozzle sub-model, and a spool valve sub-model, arranged in descending order.

[0013] S1.2: Based on the electro-hydraulic servo valve model described in S1.1, a constant-pressure oil source, a hydraulic cylinder, and a displacement sensor are constructed. The constant-pressure oil source is used to provide constant-pressure oil. The hydraulic cylinder is connected to the spool valve assembly in the spool valve sub-model. Changes in the opening of the spool valve sub-model can cause the hydraulic cylinder to move. The displacement sensor is rigidly connected to the piston of the hydraulic cylinder and can compare the detected displacement with the input value to generate a new current signal to control torque feedback, forming a secondary closed-loop control, thereby achieving precise control of the spool valve.

[0014] S1.3: Use the Visual Studio compiler as the transmission medium between AMEsim and Simulink. Generate a simulation interface module through the Interface module in AMEsim software to build an interface for data transmission with Simulink. The input end of the simulation interface module is connected to the displacement sensor, and the output end is connected to the variable current source.

[0015] Preferably, the S2 is as follows:

[0016] According to the robot hydraulic joint structure, the conversion calculation formula between hydraulic cylinder displacement and robot hydraulic joint angle is established in Simulink:

[0017]

[0018] Where θ represents the robot hydraulic joint angle, AB and BC represent the fixed distances of the robot hydraulic joints, AC' represents the minimum hydraulic cylinder stroke, and L represents the hydraulic cylinder motion stroke.

[0019] Preferably, the S3 is as follows:

[0020] S3.1: In Simulink, the robot hydraulic joint angle is used as the research adjustment signal, and the angle data fed back from S2 is used as the difference between the angle data and the input signal as the angle deviation e;

[0021] S3.2: The fuzzy module adopts a two-input and three-output form. The angular deviation e and the angular difference change rate ec are input values, and the three PID coefficient changes ΔKP, ΔKI, and ΔKD are output values ​​of the analog control. The membership function uses a triangular membership function to establish the corresponding relationship between the input and output. The domain of the fuzzy subsets of the input and output are expressed as:

[0022] {NB,NM,NS,ZO,PS,PM,PB}

[0023] Among them, NB represents large negative, NM represents medium negative, NS represents small negative, ZO represents zero, PS represents small positive, PM represents medium positive, and PB represents large positive. The precise value inputs of e and ec are converted into fuzzy membership through the input membership function to obtain E and EC.

[0024] S3.3: Establish fuzzy control rules to convert input signal error and error change rate into ΔKP, ΔKI, and ΔKD;

[0025] S3.4: Add the ΔKP, ΔKI, and ΔKD outputted from S3.3 to KP, KI, and KD respectively to realize the control parameters in the PID controller.

[0026] Furthermore, the fuzzy control rules are as follows:

[0027] S3.31: When both E and EC after fuzzification are in the N series of fuzzy subsets, it means that the actual value is higher than the stable value and is far away from the stable value. In this case, the overshoot value should be lowered, the differential link value should be increased, and the proportional coefficient and integral coefficient should be reduced.

[0028] S3.32: When E is in the N series of fuzzy subsets and EC is in the P series of fuzzy subsets, it means that the actual value is higher than the stable value but is approaching it. At this time, the larger the rate of change, the better until it reaches the stable value. In this case, the proportional coefficient should be increased. When approaching the stable value, the integral value should be reduced and the differential value should be increased to avoid large overshoot.

[0029] S3.33: When E is in the P series subset of the fuzzy subset and EC is in the N series subset of the fuzzy subset, it means that the actual value is lower than the stable value but is approaching it. Increasing ΔKP will speed up the response, while decreasing ΔKI and ΔKD. When approaching the stable value, the overshoot should be reduced, so increase the differential coefficient and slowly decrease the integral coefficient.

[0030] S3.34: When both E and EC are in the fuzzy subset P series subset, it means that the actual value is lower than the stable value and is far away from the stable value; at this time, the differential coefficient should be increased to approach the stable value as soon as possible.

[0031] Compared with the prior art, the present invention has the following beneficial effects:

[0032] By building a simulation model of the robot hydraulic joint controlled by an electro-hydraulic servo valve on the AMESim simulation platform and building a fuzzy PID controller based on Simulink for control, the simulation results are made more intuitive and easier to analyze. At the same time, it is verified that the AMESim-Simulink joint simulation can more accurately control the robot hydraulic joint. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 is a flow chart of the hydraulic joint control method of AMESim-Simulink co-simulation in the embodiment;

[0034] Figure 2 1 is a structural principle diagram of the electro-hydraulic servo valve in the embodiment;

[0035] Figure 3 is the sub-model of the electro-hydraulic servo valve torque motor in the embodiment;

[0036] Figure 4 It is the nozzle sub-model of the electro-hydraulic servo valve in the embodiment;

[0037] Figure 5 is the electro-hydraulic servo valve spool sub-model in the embodiment;

[0038] Figure 6 This is a diagram of a hydraulic joint model of a robot in an embodiment;

[0039] Figure 7 This is a simplified diagram of the motion structure of the hydraulic cylinder in the hydraulic joint of the robot in the embodiment;

[0040] Figure 8 1 is a schematic diagram of a robot hydraulic joint simulation model in the AMEsim simulation platform in an embodiment;

[0041] The figures in the figure are marked as follows: 1-torque motor; 2-nozzle; 3-sliding valve; 4-magnetic gap; 5-permanent magnet; 6-coil; 7-magnetic element; 8-nozzle baffle; 9-force feedback assembly; 10-elastic unit; 11-piston; 12-sliding valve assembly; 13-mass block; 14-upper end cover; 15-hydraulic cylinder; 16-connecting rod; 17-lower end cover; 18-encapsulated torque motor sub-model; 19-variable current source; 20-hydraulic cylinder; 21-interface module; 22-displacement sensor; 23-constant pressure oil source. DETAILED DESCRIPTION

[0042] The present invention will be further described and illustrated below with reference to the accompanying drawings and specific embodiments. The technical features of each embodiment of the present invention may be combined accordingly, provided that there is no conflict between them.

[0043] like Figure 1 As shown, the present invention provides a hydraulic joint control method based on AMESim-Simulink joint simulation, which is specifically as follows:

[0044] S1: Build a robot hydraulic joint simulation model in AMESim.

[0045] In actual use, the steps are as follows:

[0046] S1.1: Build an electro-hydraulic servo valve model in AMESim based on the electro-hydraulic servo valve structural schematic diagram;

[0047] The electro-hydraulic servo valve model mainly includes a torque motor 1 sub-model, a nozzle 2 sub-model, and a slide valve 3 sub-model, which are arranged in sequence from top to bottom.

[0048] In this embodiment, the structural principle diagram of the electro-hydraulic servo valve is as follows: Figure 2 As shown in the figure, it can be seen that the electromagnetic servo valve can be divided into three parts: torque motor 1, nozzle 2, and slide valve 3.

[0049] like Figure 3 As shown, the torque motor 1 sub-model in this embodiment mainly includes a magnetic gap 4, a permanent magnet 5, a coil 6, and a magnetic element 7. The permanent magnet 5 generates a fixed magnetic flux, and the current flowing into the coil 6 generates a magnetic flux. The magnetic element 7 transmits the two magnetic fluxes to the two magnetic ports of the magnetic gap 4 respectively. The interaction generates electromagnetic torque, which is then output through the mechanical port of the magnetic gap 4.

[0050] like Figure 4 As shown, the nozzle 2 sub-model in this embodiment primarily comprises a nozzle baffle 8, a force feedback assembly 9, and an elastic unit 10. The nozzle baffles 8 are symmetrically positioned on either side of the force feedback assembly 9, and the outer side of the nozzle baffle 8 is connected to an elastic unit 10, fixed at one end. The nozzle baffle 8 generates feedback hydraulic torque based on the valve core flow-displacement relationship. The force feedback assembly 9 is used to input a current signal to generate electromagnetic torque and feedback hydraulic torque on the nozzle baffle, thereby affecting the movement of the nozzle baffle 8 and the spool valve. The elastic unit 10 is a spring damping element used to absorb impact between the nozzle baffle and prevent excessive rotation of the force feedback assembly.

[0051] like Figure 5 As shown, the spool valve 3 sub-model in this embodiment primarily comprises a piston 11, a spool valve assembly 12, and a mass 13. The spool valve assemblies 12 are symmetrically positioned on either side of the mass 13, and the spool valve assemblies 12 are connected to the piston 11. The piston 11 connects to the force feedback assembly, driving the spool valve. The spool valve assembly 12 adjusts the valve opening size and controls the hydraulic flow rate through movement. The mass 13 represents the spool valve's mass.

[0052] In this embodiment, the two input ports of the torque motor 1 sub-model are connected to the two output ports of a variable current source 19, which in turn connects to a force feedback assembly 9. The output port of the force feedback assembly 9 connects to the right piston 11 of the spool valve 3 sub-model. The hydraulic ports of the two end pistons 11 are each connected to the nozzle baffle 8. The variable current source 19 receives the input control current signal and transmits it to the torque motor 1 sub-model, converting the current signal into electromagnetic torque, which in turn drives the nozzle baffle 2 sub-model to deflect. This deflection causes the spool valve assembly 12 in the spool valve 3 sub-model to move. The flow rate change in the spool valve 3 sub-model is fed back to the nozzle baffle 2. When the forces are balanced, the spool valve 3 stops moving, thereby controlling the valve opening.

[0053] S1.2: Based on the electro-hydraulic servo valve model constructed in S1.1, build a constant pressure oil source 23, a hydraulic cylinder 20 and a displacement sensor 22.

[0054] Among them, the constant pressure oil source 23 is used to provide constant pressure oil for the entire system to ensure sufficient flow supply, and mainly includes components such as a motor and a hydraulic pump; the hydraulic cylinder 20 is connected to the slide valve assembly 12 in the slide valve 3 sub-model. The opening change of the slide valve 3 sub-model can cause the hydraulic cylinder 20 to move; the displacement sensor 22 is rigidly connected to the piston of the hydraulic cylinder 20, and can compare the detected displacement with the input value to form a closed-loop control, thereby realizing precise control of the opening of the electro-hydraulic servo valve.

[0055] S1.3: Build an interface for data transmission with Simulink: Use the Visual Studio compiler as the transmission medium between AMEsim and Simulink. Generate a simulation interface module 21 through the Interface module in AMEsim software to build an interface for data transmission with Simulink.

[0056] The input end of the simulation interface module 21 is connected to the displacement sensor 22 , and the output end is connected to the variable current source 19 .

[0057] The robot hydraulic joint simulation model built in the AMEsim simulation platform in this embodiment is as follows Figure 8 As shown, it mainly includes an encapsulated torque motor sub-model 18 (that is, in order to facilitate the subsequent construction of the model, the constructed torque motor 1 sub-model is encapsulated to obtain an encapsulated torque motor sub-model 18), a variable current source 19, a hydraulic cylinder 20, an interface module 21 and a constant pressure oil source 23.

[0058] S2: Establish a robot hydraulic joint angle calculation model in Simulink.

[0059] In actual use, the steps are as follows:

[0060] According to the robot hydraulic joint structure, the conversion calculation formula between hydraulic cylinder displacement and robot hydraulic joint angle is established in Simulink:

[0061]

[0062] Where θ represents the robot hydraulic joint angle, AB and BC represent the fixed distances of the robot hydraulic joints, AC' represents the minimum hydraulic cylinder stroke, and L represents the hydraulic cylinder motion stroke.

[0063] In this embodiment, the robot hydraulic joint structure is as follows Figure 6 and 7 As shown in the figure, the upper end cover and the lower end cover are connected with point A as the center of the circle, the upper end cover and the piston rod of the hydraulic cylinder are connected with point B as the center of the circle, and the hydraulic cylinder body is connected to the support fixed to the connecting rod. Points A and B are fixed on the upper end cover, and point C is fixed on the connecting rod. The length of AB is fixed, and the joint rotates around B. The piston movement causes the length of AC to change, which in turn affects the angle θ of the robot's hydraulic joint.

[0064] S3: Build a fuzzy PID model of the robot hydraulic joint in Simulink.

[0065] In actual use, the steps are as follows:

[0066] S3.1: In Simulink, the robot hydraulic joint angle is used as the research adjustment signal, and the angle data fed back from S2 is used as the difference between the angle data and the input signal as the angle deviation e;

[0067] S3.2: The fuzzy module adopts a two-input and three-output form. The angular deviation e and the angular difference change rate ec are input values, and the three PID coefficient changes ΔKP, ΔKI, and ΔKD are output values ​​of the analog control. The membership function uses a triangular membership function to establish the corresponding relationship between the input and output. The domain of the fuzzy subsets of the input and output are expressed as:

[0068] {NB,NM,NS,ZO,PS,PM,PB}

[0069] Among them, NB represents large negative, NM represents medium negative, NS represents small negative, ZO represents zero, PS represents small positive, PM represents medium positive, and PB represents large positive. The precise value inputs of e and ec are converted into fuzzy membership through the input membership function to obtain E and EC.

[0070] S3.3: Establish fuzzy control rules to convert input signal error and error change rate into ΔKP, ΔKI, and ΔKD;

[0071] In this embodiment, the fuzzy control rules are as follows:

[0072] S3.31: When both E and EC after fuzzification are in the N series of fuzzy subsets, it means that the actual value is higher than the stable value and is far away from the stable value. In this case, the overshoot value should be lowered, the differential link value should be increased, and the proportional coefficient and integral coefficient should be reduced.

[0073] S3.32: When E is in the N series of fuzzy subsets and EC is in the P series of fuzzy subsets, it means that the actual value is higher than the stable value but is approaching it. At this time, the larger the rate of change, the better until it reaches the stable value. In this case, the proportional coefficient should be increased. When approaching the stable value, the integral value should be reduced and the differential value should be increased to avoid large overshoot.

[0074] S3.33: When E is in the P series subset of the fuzzy subset and EC is in the N series subset of the fuzzy subset, it means that the actual value is lower than the stable value but is approaching it. Increasing ΔKP will speed up the response, while decreasing ΔKI and ΔKD. When approaching the stable value, the overshoot should be reduced, so increase the differential coefficient and slowly decrease the integral coefficient.

[0075] S3.34: When both E and EC are in the fuzzy subset P series subset, it means that the actual value is lower than the stable value and is far away from the stable value; at this time, the differential coefficient should be increased to approach the stable value as soon as possible.

[0076] S3.4: Add the ΔKP, ΔKI, and ΔKD outputted from S3.3 to KP, KI, and KD respectively to realize the control parameters in the PID controller.

[0077] S4: Using Simulink as the intermediate simulation platform, the hydraulic cylinder piston displacement signal in the robot hydraulic joint simulation model obtained in S1 is transmitted to Simulink. The robot hydraulic joint angle calculation model obtained in S2 is used to convert the hydraulic cylinder piston displacement signal into an angle signal. The fuzzy PID controller in the robot hydraulic joint fuzzy PID model obtained in S3 outputs the electro-hydraulic servo valve current signal to the electro-hydraulic servo valve in AMESim to achieve precise control of the robot hydraulic joint.

[0078] The present invention uses the AMESim / Simulink joint simulation platform to build a robot hydraulic joint system and control model to carry out simulation research. After simulation, it is found that the use of structural control based on the fuzzy PID model can achieve precise control of the robot hydraulic joint.

[0079] The embodiment described above is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Persons skilled in the art may make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, any technical solution obtained by equivalent substitution or equivalent transformation falls within the scope of protection of the present invention.

Claims

1. A hydraulic joint control method based on AMESim-Simulink joint simulation, characterized in that: The details are as follows: S1: Build a robot hydraulic joint simulation model in AMESim; S2: Establish a robot hydraulic joint angle calculation model in Simulink; S3: Establish a fuzzy PID model of the robot hydraulic joint in Simulink; S4: Using Simulink as the intermediate simulation platform, the hydraulic cylinder piston displacement signal in the robot hydraulic joint simulation model obtained in S1 is transmitted to Simulink. The hydraulic cylinder piston displacement signal is converted into an angle signal using the robot hydraulic joint angle calculation model obtained in S2. The fuzzy PID controller in the robot hydraulic joint fuzzy PID model obtained in S3 outputs the electro-hydraulic servo valve current signal to the electro-hydraulic servo valve in AMESim, thus achieving precise control of the robot hydraulic joint. The S2 is specifically as follows: According to the robot hydraulic joint structure, the conversion calculation formula between hydraulic cylinder displacement and robot hydraulic joint angle is established in Simulink: Where θ represents the robot hydraulic joint angle, AB and BC represent the fixed distances of the robot hydraulic joints, AC' represents the minimum hydraulic cylinder stroke, and L represents the hydraulic cylinder motion stroke.

2. A hydraulic joint control method based on AMESim-Simulink joint simulation according to claim 1, characterized in that: The S1 is specifically as follows: S1.1: Based on the structural principle diagram of the electro-hydraulic servo valve, an electro-hydraulic servo valve model is constructed in AMESim; the electro-hydraulic servo valve model includes a torque motor (1) sub-model, a nozzle (2) sub-model, and a slide valve (3) sub-model, which are arranged in order from top to bottom; S1.2: On the basis of the electro-hydraulic servo valve model described in S1.1, a constant pressure oil source (23), a hydraulic cylinder (20) and a displacement sensor (22) are constructed; the constant pressure oil source (23) is used to provide constant pressure oil; the hydraulic cylinder (20) is connected to the slide valve assembly (12) in the slide valve (3) sub-model, and the opening change of the slide valve (3) sub-model can cause the piston of the hydraulic cylinder (20) to be displaced; the displacement sensor (22) is rigidly connected to the piston of the hydraulic cylinder (20), and can compare the detected displacement with the input quantity to form a new current signal control torque feedback, thereby forming a secondary closed-loop control, thereby achieving precise control of the slide valve (3); S1.3: Using the Visual Studio compiler as a transmission medium between AMEsim and Simulink, a simulation interface module (21) is generated in the AMEsim software through the Interface module to build an interface for data transmission with Simulink; the input end of the simulation interface module (21) is connected to the displacement sensor (22), and the output end is connected to the variable current source (19).

3. A hydraulic joint control method based on AMESim-Simulink joint simulation according to claim 1, characterized in that: The S3 is as follows: S3.1: In Simulink, the robot hydraulic joint angle is used as the research adjustment signal, and the angle data fed back from S2 is used as the difference between the angle data and the input signal as the angle deviation e; S3.2: The fuzzy module adopts a two-input and three-output form. The angular deviation e and the angular difference change rate ec are input values, and the three PID coefficient changes ΔKP, ΔKI, and ΔKD are output values ​​of the analog control. The membership function uses a triangular membership function to establish the corresponding relationship between the input and output. The domain of the fuzzy subsets of the input and output are expressed as: {NB,NM,NS,ZO,PS,PM,PB} Among them, NB represents large negative, NM represents medium negative, NS represents small negative, ZO represents zero, PS represents small positive, PM represents medium positive, and PB represents large positive. The precise value inputs of e and ec are converted into fuzzy membership through the input membership function to obtain E and EC. S3.3: Establish fuzzy control rules to convert input signal error and error change rate into ΔKP, ΔKI, and ΔKD; S3.4: Add the ΔKP, ΔKI, and ΔKD outputted from S3.3 to KP, KI, and KD respectively to realize the control parameters in the PID controller.

4. A hydraulic joint control method based on AMESim-Simulink joint simulation according to claim 3, characterized in that: The fuzzy control rules are as follows: S3.31: When both E and EC after fuzzification are in the N series of fuzzy subsets, it means that the actual value is higher than the stable value and is far away from the stable value. In this case, the overshoot value should be lowered, the differential link value should be increased, and the proportional coefficient and integral coefficient should be reduced. S3.32: When E is in the N series of fuzzy subsets and EC is in the P series of fuzzy subsets, it means that the actual value is higher than the stable value but is approaching it. At this time, the larger the rate of change, the better until it reaches the stable value. In this case, the proportional coefficient should be increased. When approaching the stable value, the integral value should be reduced and the differential value should be increased to avoid large overshoot. S3.33: When E is in the P series subset of the fuzzy subset and EC is in the N series subset of the fuzzy subset, it means that the actual value is lower than the stable value but is approaching it. Increasing ΔKP will speed up the response, while decreasing ΔKI and ΔKD. When approaching the stable value, the overshoot should be reduced, so increase the differential coefficient and slowly decrease the integral coefficient. S3.34: When both E and EC are in the fuzzy subset P series subset, it means that the actual value is lower than the stable value and is far away from the stable value; at this time, the differential coefficient should be increased to approach the stable value as soon as possible.

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