Hydraulic joint control method based on AMESimm-Simulink joint simulation

Abstract

The invention discloses a hydraulic joint control method based on AMESim-Simulink joint simulation, and relates to the field of robot hydraulic joint control. The method comprises the steps that S1, a robot hydraulic joint simulation model is built in AMESim; s2, a robot hydraulic joint angle calculation model is established in Simulink; s3, a robot hydraulic joint fuzzy PID model is established in Simulink; s4, using Simulink as an intermediate simulation platform, transmitting a hydraulic cylinder piston displacement signal in the robot hydraulic joint simulation model obtained in the step S1 to Simulink, converting the hydraulic cylinder piston displacement signal into an angle signal by using the robot hydraulic joint angle calculation model obtained in the step S2, and calculating the angle signal according to the angle signal. And S3, outputting an electro-hydraulic servo valve current signal to an electro-hydraulic servo valve in AMESim through a fuzzy PID controller in the fuzzy PID model of the hydraulic joint of the robot obtained in the step S3 to realize accurate control of the hydraulic joint of the robot. According to the method, the fact that the hydraulic joints of the robot can be more accurately controlled by adopting AMESim-Simulink joint simulation is verified.

Description

Technical Field

[0001] The 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 to control robot hydraulic joints. Compared with the more commonly used electromagnetic proportional reversing valves, electro-hydraulic servo valves, as multi-stage amplified closed-loop hydraulic servo systems, have faster response speeds 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 that it is difficult to build a mathematical model of the current electro-hydraulic servo valve mentioned in the above background technology, and to improve the control accuracy of the robot hydraulic joint.

[0005] The specific technical solutions adopted by 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 the fuzzy PID model of robot hydraulic joints 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, and 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 to achieve precise control of the robot hydraulic joint.

[0011] Preferably, the S1 is as follows:

[0012] S1.1: According to 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 sub-model, a nozzle sub-model and a slide valve sub-model arranged in sequence from top to bottom;

[0013] S1.2: On the basis of 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 slide valve assembly in the slide valve sub-model, and the opening change of the slide valve sub-model can cause the hydraulic cylinder to displace; the displacement sensor is rigidly connected to the piston of the hydraulic cylinder, and can compare the detected displacement with the input amount to form a new current signal control torque feedback, forming a secondary closed-loop control, and thus realizing precise control of the slide 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 the 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 calculation formula for the conversion between the hydraulic cylinder displacement and the robot hydraulic joint angle is established in Simulink:

[0017]

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

[0019] Preferably, 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 by S2 is taken as the difference with the input signal as the angle deviation e;

[0021] S3.2: The fuzzy module adopts the form of two inputs and three outputs; among them, the angle deviation e and the angle difference change rate ec are input values, and the three coefficient changes of PID ΔKP, ΔKI, ΔKD are used as the output values ​​of analog control. The membership function uses the 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 means negative big, NM means negative medium, NS means negative small, ZO means zero, PS means positive small, PM means positive medium, and PB means positive big; the precise value input of e and ec is 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 output by 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 fuzzy subset N series subset, it means that the actual value is higher than the stable value and is far away from the stable value; at this time, 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 fuzzy subset N series subset and EC is in the fuzzy subset P series subset, it means that the actual value is higher than the stable value, but is in a state of constantly approaching. 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 at the beginning; and 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 fuzzy subset P series subset and EC is in the fuzzy subset N series subset, it means that the actual value is lower than the stable value, but is in a state of approaching. Increasing ΔKP speeds up the response and reducing ΔKI and ΔKD. When approaching the stable value, the overshoot should be reduced, so the differential coefficient is increased and the integral coefficient is slowly reduced.

[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 more intuitive and easy 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 joint simulation in the embodiment;

[0034] Figure 2 is a structural schematic diagram of an electro-hydraulic servo valve in an embodiment;

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

[0036] Figure 4 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 is a diagram of a hydraulic joint model of a robot in an embodiment;

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

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

[0041] The reference numerals in the figure are: 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 is further described and illustrated below in conjunction with the accompanying drawings and specific embodiments. The technical features of each embodiment of the present invention can be combined accordingly without conflicting with each other.

[0043] like Figure 1 As shown, the present invention provides a hydraulic joint control method based on AMESim-Simulink joint simulation, and the method 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 according to the structural schematic diagram of the electro-hydraulic servo valve;

[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, the coil 6 flows with current to generate a magnetic flux, and the magnetic element 7 transmits the two magnetic fluxes to the two magnetic ports of the magnetic gap 4 respectively, and the electromagnetic torque is generated by the interaction and 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 mainly includes a nozzle baffle 8, a force feedback component 9 and an elastic unit 10. Among them, the nozzle baffles 8 are symmetrically arranged on both sides of the force feedback component 9, and the outer side of the nozzle baffle 8 is connected to the elastic unit 10 with one end fixed. The nozzle baffle 8 generates a feedback hydraulic torque through the valve core flow-displacement relationship. The force feedback component 9 is used to input a current signal to generate an electromagnetic torque and a feedback hydraulic torque of the nozzle baffle, thereby affecting the movement of the nozzle baffle 8 and the slide valve. The elastic unit 10 is a spring damping element, which is used to absorb the impact between the nozzle baffles and prevent the force feedback component from rotating excessively.

[0051] like Figure 5 As shown, the slide valve 3 sub-model in this embodiment mainly includes a piston 11, a slide valve assembly 12 and a mass block 13. Among them, the slide valve assembly 12 is symmetrically provided on both sides of the mass block 13, and the slide valve assembly 12 is connected to the piston 11. The piston 11 is used to connect the force feedback assembly to drive the slide valve to move. The slide valve assembly 12 changes the valve port size by moving to control the hydraulic flow, and the mass block 13 is the slide valve mass.

[0052] In this embodiment, the two input ports of the torque motor 1 sub-model are respectively connected to the two output ports of the variable current source 19, the two output ports are connected to the force feedback component 9, the output port of the force feedback component 9 is connected to the right end piston 11 of the slide valve 3 sub-model, and the hydraulic ports of the two end pistons 11 are respectively 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, converts the current signal into electromagnetic torque, and then pushes the nozzle baffle 2 sub-model to deflect, and this deflection causes the slide valve component 12 in the slide valve 3 sub-model to move, and the flow change in the slide valve 3 sub-model is fed back to the nozzle baffle 2. When the force is balanced, the slide valve 3 stops moving, thereby controlling the valve opening.

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

[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 sliding valve assembly 12 in the sliding valve 3 sub-model, and the opening change of the sliding 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 amount 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, and generate a simulation interface module 21 through the Interface module in the 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 a packaged 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 packaged to obtain a packaged 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 calculation formula for the conversion between the hydraulic cylinder displacement and the robot hydraulic joint angle is established in Simulink:

[0061]

[0062] Among them, θ represents the robot hydraulic joint angle, AB and BC represent the robot hydraulic joint fixed distances, 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, the upper end cover is connected to the lower end cover with point A as the center, the upper end cover is connected to the piston rod of the hydraulic cylinder with point B as the center, 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, point C is fixed on the connecting rod, the length of AB is fixed, the joint rotates around B, the piston movement causes the length of AC to change, and then affects the hydraulic joint angle θ of the robot.

[0064] S3: Establish 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 by S2 is taken as the difference with the input signal as the angle deviation e;

[0067] S3.2: The fuzzy module adopts the form of two inputs and three outputs; among them, the angle deviation e and the angle difference change rate ec are input values, and the three coefficient changes of PID ΔKP, ΔKI, ΔKD are used as the output values ​​of analog control. The membership function uses the 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 means negative big, NM means negative medium, NS means negative small, ZO means zero, PS means positive small, PM means positive medium, and PB means positive big; the precise value input of e and ec is 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 fuzzy subset N series subset, it means that the actual value is higher than the stable value and is far away from the stable value; at this time, 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 fuzzy subset N series subset and EC is in the fuzzy subset P series subset, it means that the actual value is higher than the stable value, but is in a state of constantly approaching. 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 at the beginning; and 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 fuzzy subset P series subset and EC is in the fuzzy subset N series subset, it means that the actual value is lower than the stable value, but is in a state of approaching. Increasing ΔKP speeds up the response and reducing ΔKI and ΔKD. When approaching the stable value, the overshoot should be reduced, so the differential coefficient is increased and the integral coefficient is slowly reduced.

[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 output by 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, and 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 to achieve precise control of the robot hydraulic joint.

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

[0079] The above-described embodiment is only a preferred solution of the present invention, but it is not intended to limit the present invention. A person skilled in the relevant technical field may make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, any technical solution obtained by equivalent replacement or equivalent transformation falls within the protection scope 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 the fuzzy PID model of robot hydraulic joints 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, and 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 to achieve precise control of the robot hydraulic joint.

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: According to 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 comprises a torque motor (1) sub-model, a nozzle (2) sub-model and a slide valve (3) sub-model arranged in sequence 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 amount to form a new current signal control torque feedback, thereby forming a secondary closed-loop control, thereby realizing 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 S2 is specifically as follows: According to the robot hydraulic joint structure, the calculation formula for the conversion between the hydraulic cylinder displacement and the robot hydraulic joint angle is established in Simulink: Among them, θ represents the robot hydraulic joint angle, AB and BC represent the robot hydraulic joint fixed distances, AC' represents the minimum hydraulic cylinder stroke, and L represents the hydraulic cylinder motion stroke.

4. 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 by S2 is taken as the difference with the input signal as the angle deviation e; S3.2: The fuzzy module adopts the form of two inputs and three outputs; among them, the angle deviation e and the angle difference change rate ec are input values, and the three coefficient changes of PID ΔKP, ΔKI, ΔKD are used as the output values ​​of analog control. The membership function uses the 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 means negative big, NM means negative medium, NS means negative small, ZO means zero, PS means positive small, PM means positive medium, and PB means positive big; the precise value input of e and ec is 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 output by S3.3 to KP, KI, and KD respectively to realize the control parameters in the PID controller.

5. A hydraulic joint control method based on AMESim-Simulink joint simulation according to claim 4, characterized in that: The fuzzy control rules are as follows: S3.31: When both E and EC after fuzzification are in the fuzzy subset N series subset, it means that the actual value is higher than the stable value and is far away from the stable value; at this time, 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 fuzzy subset N series subset and EC is in the fuzzy subset P series subset, it means that the actual value is higher than the stable value, but is in a state of constantly approaching. 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 at the beginning; and 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 fuzzy subset P series subset and EC is in the fuzzy subset N series subset, it means that the actual value is lower than the stable value, but is in a state of approaching. Increasing ΔKP speeds up the response and reducing ΔKI and ΔKD. When approaching the stable value, the overshoot should be reduced, so the differential coefficient is increased and the integral coefficient is slowly reduced. 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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