Robust hydraulic control and simulation system and method for mechanical arm

Abstract

The invention provides a robust hydraulic control and simulation system and method for a mechanical arm, and the method comprises the steps: determining the position and type of a kinematic pair based on a three-dimensional model, and building a multi-body dynamics simulation system of the mechanical arm; determining a transmission mode according to the hydraulic original drawing, and establishing a hydraulic transmission simulation system of the mechanical arm; and an action execution control algorithm is designed, and a feedback control simulation system of the mechanical arm is established. According to the simulation system, a joint simulation technology is adopted, intercommunication among a multi-body dynamics system, a hydraulic transmission system and a feedback control system is achieved, and a mechanical-hydraulic-control joint simulation platform is formed. On the basis, a robust hydraulic transmission system and a robust feedback control system are designed, and finally the performance of the mechanical arm in the complex environment is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of hydraulic transmission simulation and automation for heavy equipment, and particularly to a robust hydraulic control strategy, simulation system and method for a robotic arm. Background Art

[0002] In the applications of modern industry, as a key actuator of heavy equipment, robotic arms are widely used in fields such as tunnel boring, mining, production assembly, etc. These robotic arms usually need to perform precise tasks in extreme environments, facing complex scenarios such as uneven distribution of environmental media and drastic changes in working loads. Especially in high-load environments such as tunnel construction and bulk material excavation, robotic arms are prone to problems such as decreased motion accuracy, enhanced abnormal vibration, and weakened execution ability, directly affecting the overall performance and working efficiency of heavy equipment.

[0003] As an important drive system of the robotic arm, the hydraulic control system is responsible for providing precise power and efficient energy conversion. The performance of the robotic arm, especially the execution accuracy of its movements, directly depends on the robustness and response speed of this system. Optimizing the hydraulic control strategy to ensure that the system can transmit precise motion trajectories as required is the core of improving the overall performance of the robotic arm. However, when facing load fluctuations, fluid dynamics changes, and environmental disturbances, the hydraulic control system often exhibits problems such as response lag and inaccurate control.

[0004] The research on how to improve the hydraulic control strategy mainly focuses on two aspects: on the one hand, it is to optimize the system composition of hydraulic transmission. The traditional transmission system consists of a fixed-displacement pump, fixed-displacement valves, and a fixed-pressure system, and its performance is extremely unstable when facing load fluctuations and cannot be automatically adjusted. Current research focuses on how to adjust the displacement of the hydraulic pump and the opening of the valves according to load changes and design more robust hydraulic components; on the other hand, it is to construct a more robust control loop. Traditional hydraulic control methods include PID control, sliding mode control, etc., which are difficult to cope with the non-linearity, time-variation, and high dynamicity exhibited by the system in complex environments and cannot quickly adjust control parameters to adapt to new working conditions. Current research focuses on improving the load adaptability and disturbance stability of the control method and designing new controllers.

[0005] The analysis and optimization of the current hydraulic control system mainly rely on the experimental method, that is, through a large number of physical experiments and tests to verify the effect of the hydraulic control strategy. However, experimental verification not only takes a long time but also has high costs. Especially in complex environments and extreme working conditions, it is difficult for the experimental method to comprehensively simulate real working conditions and cannot effectively evaluate the stability and robustness of the hydraulic system during long-term operation. Therefore, more and more research has begun to adopt simulation-based methods to replace traditional experimental verification.

[0006] The simulation technology of hydraulic control systems has been widely applied. However, existing simulation platforms usually focus on the optimization of a single field. The dynamic simulation of mechanisms, hydraulic transmission simulation, and control system simulation are relatively separated from each other, lacking comprehensive simulation of multiple disciplines and fields, and it is difficult to simulate the tight coupling of the three in real working conditions. Through the comprehensive application of co-simulation technology, building a unified "mechanism-hydraulic-control" simulation platform has become the key to solving this problem.

[0007] Patent document CN112199827A (application number: 202011015716.0) discloses a dynamic simulation method for a robotic arm, including: obtaining a set of kinematic parameters, a set of joint trajectory parameters, and a set of dynamic parameters of the robotic arm; the set of dynamic parameters includes reduction ratio parameters and installation position parameters of each motor for driving the connecting rods; according to the set of kinematic parameters, the set of joint trajectory parameters, and the set of dynamic parameters, the joint torques and motor torques corresponding to each drivable connecting rod are obtained. By introducing the reduction ratio parameters of the motors of each driving connecting rod and the installation position parameters of the motors in the simulation calculation of obtaining the joint torques and motor torques corresponding to each driven connecting rod, this patent is more adaptable to the needs of the design of motors arranged across joints and can obtain more accurate simulation results.

[0008] In view of the above situation, the present invention designs a robust hydraulic transmission system and a corresponding robust control system, builds a unified "mechanism-hydraulic-control" multi-field simulation platform, analyzes, optimizes, and verifies hydraulic control strategies, and finally proposes a robust hydraulic control strategy and simulation system for a robotic arm. The purpose of the present invention is to improve the robustness of the hydraulic control system of the robotic arm in a complex environment through multi-disciplinary collaboration, and thus improve the overall working performance of major equipment. Summary of the Invention

[0009] Aiming at the defects in the prior art, the purpose of the present invention is to provide a robust hydraulic control and simulation method and system for a robotic arm.

[0010] According to a robust hydraulic control and simulation method for a robotic arm provided by the present invention, it includes:

[0011] Step S1: Respectively construct a multi-body dynamics simulation model, a hydraulic transmission simulation model, and a feedback control simulation model based on the three-dimensional model of the robotic arm and the hydraulic schematic diagram;

[0012] Step S2: Based on the multi-body dynamics simulation model, the hydraulic transmission simulation model, and the feedback control simulation model, build a mechanism-hydraulic-control co-simulation platform through co-simulation technology;

[0013] Step S3: Simulate the real working conditions based on the machine-hydraulic-control co-simulation platform. Control the hydraulic transmission system through the feedback control simulation model. The hydraulic transmission system generates hydraulic pressure to drive the motion of the joint mechanism. The multi-body dynamics simulation model obtains the joint displacement information and transmits it to the feedback control simulation model through the hydraulic transmission simulation model. The feedback control simulation model calculates the error of the joint motion trajectory based on the feedback displacement to form a closed-loop control.

[0014] Preferably, the multi-body dynamics simulation model includes: constructing a three-dimensional model of the robotic arm using the CAD design software CREO, determining the positions and types of kinematic pairs, measuring the kinematic parameters, and establishing a kinematic theoretical model that describes the mapping relationship between the joint trajectories and the end path of the robotic arm; importing the three-dimensional model into the multi-body dynamics software ADAMS, defining the material types, centroid positions, and kinematic pair types of each component to form the dynamic model of the robotic arm, and verifying the accuracy of the motion form of the dynamic model with the kinematic theoretical model.

[0015] Preferably, the hydraulic transmission simulation model includes: combining and setting the parameters of the functional components in the modular simulation software AMESIM by referring to the actual hydraulic schematic diagram of the robotic arm to construct a simulation model of the real hydraulic transmission system.

[0016] Preferably, the feedback control simulation model includes: calling the functional components of the modular control software SIMULINK to build a feedback control system for the hydraulic transmission of the robotic arm.

[0017] Preferably, step S2 includes:

[0018] The multi-body dynamics simulation model receives the hydraulic pressure transmitted by the hydraulic transmission simulation model and outputs the joint displacement to the hydraulic transmission simulation model;

[0019] The hydraulic transmission simulation model receives the control signal transmitted by the feedback control simulation model, outputs the hydraulic pressure to the multi-body dynamics simulation model, and outputs the received joint displacement to the feedback control simulation model;

[0020] The feedback control simulation model receives the joint displacement, forms a feedback control loop, and outputs the control signal to the hydraulic transmission simulation model;

[0021] Using model interchange technology, the multi-body dynamics simulation model is encapsulated as a whole into an FMU module, and the interfaces for receiving liquid pressure and outputting joint displacement are retained. After encapsulation, the FMU module is imported into the hydraulic transmission simulation model as a whole. Using co-simulation technology, based on the C++ low-level language, a data path for transmitting joint displacement and control signals is established in the hydraulic transmission simulation model and the feedback control simulation model. Finally, model verification is carried out. An ideal joint displacement curve is preset in the feedback control simulation model, and a control signal is generated to control the hydraulic valve in the hydraulic transmission simulation model. The liquid pressure drives the joint displacement of the mechanism, and the joint displacement is also received by the feedback control simulation model in real time. If the joint displacement conforms to the preset ideal curve, the performance is verified.

[0022] In this process, the encapsulated multi-body dynamics simulation model performs off-line or on-line co-simulation, and the hydraulic transmission simulation model and the feedback control simulation model perform on-line co-simulation.

[0023] Preferably, the method further includes: replacing the constant current source or constant pressure source with a load-sensitive pump in the hydraulic transmission system, and the load-sensitive pump is used to adjust the displacement of the pump according to the load pressure feedback.

[0024] An electro-hydraulic proportional direction valve controlled by electromagnetic force is added to the hydraulic transmission system, and the electro-hydraulic proportional direction valve is used to convert the control signal into a spool acting force through a proportional electromagnet to achieve stepless regulation of the flow rate.

[0025] Preferably, the method further includes: optimizing the feedback control simulation model.

[0026] The optimization of the feedback control simulation model includes: based on historical data or initial tests, using a genetic algorithm combined with H∞ robust control constraints to perform robust optimization on the PID controller parameters in the feedback control simulation model; subsequently, using fuzzy rules to dynamically adjust the PID parameters of the PID controller during the control process.

[0027] According to a robust hydraulic control and simulation system for a robotic arm provided by the present invention, it includes:

[0028] Module M1: Respectively construct a multi-body dynamics simulation model, a hydraulic transmission simulation model, and a feedback control simulation model based on the three-dimensional model of the robotic arm and the hydraulic schematic diagram.

[0029] Module M2: Based on the multi-body dynamics simulation model, the hydraulic transmission simulation model, and the feedback control simulation model, build a machine-hydraulic-control co-simulation platform through co-simulation technology.

[0030] Module M3: The joint simulation platform based on machine - liquid - control simulates the real working conditions. The hydraulic transmission system is controlled by the feedback control simulation model. The hydraulic transmission system generates hydraulic pressure to drive the joint mechanism to move. The multi - body dynamics simulation model obtains the joint displacement information and transmits it to the feedback control simulation model through the hydraulic transmission simulation model. The feedback control simulation model calculates the error of the joint motion trajectory based on the feedback displacement to form a closed - loop control.

[0031] Preferably, the multi - body dynamics simulation model includes: constructing a three - dimensional model of the robotic arm using the CAD design software CREO, determining the position and type of kinematic pairs, measuring kinematic parameters, and establishing a kinematic theoretical model describing the mapping relationship between the joint trajectory and the end - effector path of the robotic arm; importing the three - dimensional model into the multi - body dynamics software ADAMS, defining the material type, centroid position, and kinematic pair type of each component to form the dynamic model of the robotic arm, and verifying the accuracy of the motion form of the dynamic model with the kinematic theoretical model;

[0032] The hydraulic transmission simulation model includes: by referring to the actual hydraulic schematic diagram of the robotic arm, combining and setting parameters of functional components in the modular simulation software AMESIM to construct a simulation model of the real hydraulic transmission system;

[0033] The feedback control simulation model includes: calling the functional components of the modular control software SIMULINK to build a feedback control system for the hydraulic transmission of the robotic arm.

[0034] Preferably, the module M2 includes:

[0035] The multi - body dynamics simulation model receives the hydraulic pressure transmitted by the hydraulic transmission simulation model and outputs the joint displacement to the hydraulic transmission simulation model;

[0036] The hydraulic transmission simulation model receives the control signal transmitted by the feedback control simulation model, outputs the hydraulic pressure to the multi - body dynamics simulation model, and outputs the received joint displacement to the feedback control simulation model;

[0037] The feedback control simulation model receives the joint displacement, forms a feedback control loop, and outputs the control signal to the hydraulic transmission simulation model;

[0038] Using the model interchange technology, the multi-body dynamics simulation model is encapsulated as a whole into an FMU module, and the interfaces for receiving the liquid pressure and outputting the joint displacement are reserved. After the encapsulation is completed, the FMU module is imported into the hydraulic transmission simulation model as a whole; using the co-simulation technology, based on the C++ low-level language, data paths for transmitting the joint displacement and control signals are established in the hydraulic transmission simulation model and the feedback control simulation model; finally, model verification is carried out. An ideal joint displacement curve is preset in the feedback control simulation model, and a control signal is generated to control the hydraulic valve in the hydraulic transmission simulation model. The liquid pressure drives the joint displacement of the mechanism, and the joint displacement is also received by the feedback control simulation model in real time. If the joint displacement conforms to the preset ideal curve, the performance is verified;

[0039] In this process, the encapsulated multi-body dynamics simulation model performs off-line or on-line co-simulation, and the hydraulic transmission simulation model and the feedback control simulation model perform on-line co-simulation.

[0040] Compared with the prior art, the present invention has the following beneficial effects:

[0041] 1. The robust hydraulic control and simulation method and system for the robotic arm provided by the present invention can be used at low cost for simulating complex environmental conditions and building a hydraulic control system. Based on the hydraulic control strategy designed on this platform, the execution accuracy and performance robustness of the robotic arm in complex environments can be improved;

[0042] 2. The present invention provides a robust hydraulic transmission system and a robust feedback control system, ultimately improving the performance of the robotic arm in complex environments;

[0043] 3. The present invention can be used for the execution robotic arms of major equipment such as tunnel boring machines, excavators, rock drilling jumbo, and assembly robots, and improve the performance of their hydraulic control based on co-simulation analysis; it can solve the problems of long time consumption and high cost of the existing experimental analysis methods, and the problems of severe performance fluctuations and unstable control methods of the existing hydraulic control strategies. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] By reading the detailed description of the non-restrictive embodiments with reference to the following drawings, other features, objects, and advantages of the present invention will become more apparent:

[0045] Figure 1 It is the overall framework diagram of the hydraulic control strategy and simulation system of the present invention.

[0046] Figure 2 It is the schematic block diagram of the preparation work for model building of the present invention.

[0047] Figure 3 It is the schematic block diagram of the multi-body dynamics model building of the present invention.

[0048] Figure 4 It is a schematic block diagram for building the hydraulic transmission model of the present invention.

[0049] Figure 5 It is a schematic block diagram for building the feedback control model of the present invention.

[0050] Figure 6 It is a schematic block diagram for the co-simulation technology of the present invention.

[0051] Figure 7 It is a detailed explanatory diagram of the robust hydraulic transmission components of the present invention.

[0052] Figure 8 It is a detailed explanatory diagram of the robust feedback control algorithm of the present invention.

[0053] Figure 9 It is an example of a typical complex environment involved in the present invention. The physical properties of different regions are different. This complex environment is shown as an example of a cantilever roadheader arm cutting a complex gangue coal seam. Specific embodiments

[0054] The present invention will be described in detail below with reference to specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several changes and improvements can still be made. These all belong to the protection scope of the present invention.

[0055] Embodiment 1

[0056] According to the robust hydraulic control and simulation system and method for a robotic arm provided by the present invention, by building a multi-domain simulation platform of "mechanism - hydraulics - control", it can be used at low cost for simulating complex environmental conditions and building a hydraulic control system. The hydraulic control strategy designed based on this platform can improve the performance robustness of the robotic arm in complex environments.

[0057] The robust hydraulic control and simulation method for the robotic arm includes: a multi-body dynamics simulation model, constructing a three-dimensional geometric model of the robotic arm to clarify the transmission types and methods of each kinematic pair; a hydraulic transmission simulation model, constructing a hydraulic system required to drive the kinematic pairs of the robotic arm and designing hydraulic valves and hydraulic lifting actuators; a feedback control simulation model, constructing a robust controller for controlling the hydraulic flow rate to form a feedback loop for hydraulic transmission control. The simulation models in the three fields rely on co-simulation technology to transfer simulation data to each other, forming a "mechanism-hydraulics-control" co-simulation platform. The robust hydraulic control and simulation method for the robotic arm is analyzed and verified relying on the "mechanism-hydraulics-control" co-simulation platform. On this basis, a robust hydraulic transmission system and the corresponding robust control system are designed in the simulation platform, mainly including designing a load-sensitive variable pump, an electro-hydraulic proportional direction valve, and a fuzzy PID controller optimized by robustness, so as to further improve the execution accuracy and performance robustness.

[0058] Further, the multi-body dynamics simulation model of the robotic arm includes: using the CAD design software CREO to establish a complete three-dimensional model of the robotic arm, determining the positions and types of kinematic pairs, measuring the necessary kinematic parameters, and finally establishing a kinematic theory model describing the mapping relationship between the joint trajectories and the end path of the robotic arm in the DH coordinate system. Importing the three-dimensional model into the multi-body dynamics software ADAMS, defining the material types, centroid positions, kinematic pair types, etc. of each component to form the dynamics model of the robotic arm, and verifying the accuracy of the motion form of the dynamics model with the kinematic theory model.

[0059] Further, the hydraulic transmission simulation model of the robotic arm includes: by referring to the actual hydraulic schematic diagram of the robotic arm, combining and setting the parameters of the functional components in the modular simulation software AMESIM to construct a simulation model of the actual hydraulic transmission system. The function of the hydraulic transmission system is to drive the actuator of the lifting mechanism with oil pressure, and the lifting mechanism corresponds to the translational kinematic pair of the robotic arm.

[0060] Further, the feedback control simulation model of the robotic arm includes: calling the functional components of the modular control software SIMULINK to build a feedback control system for the hydraulic transmission of the robotic arm. The controller is the main component of this system, and a robust control algorithm can be designed. The function of the feedback control system is to read the displacement of the translational kinematic pair of the robotic arm in real time, generate a feedback control quantity, and act on the electromagnetic force of the direction valve of the hydraulic transmission system.

[0061] Furthermore, the "mechanical - hydraulic - control" co - simulation platform of the robotic arm includes: It is composed of an ADAMS multi - body dynamics system, an AMESIM hydraulic transmission system, and a SIMULINK feedback control system. Through co - simulation technology, the circulation of models and data is carried out to build a unified multi - domain collaborative simulation platform, which can simulate the process of an embedded controller controlling the hydraulic transmission system under real - working conditions, the hydraulic transmission system generating hydraulic pressure to drive the joint mechanism to move, and the joint displacement sensor feeding back the displacement to the controller in real time.

[0062] Furthermore, the co - simulation technology of the robotic arm simulation platform covers the "model interchange" technology. Through the model interchange technology, the ADAMS model is encapsulated into an FMU module, and the interface for data transfer is retained, enabling it to receive the hydraulic pressure of the AMESIM model and transfer the kinematic pair displacement to the AMESIM model. After encapsulation, the ADAMS model can be simulated offline and call the solver of AMESIM.

[0063] Furthermore, the co - simulation technology of the robotic arm simulation platform covers the "co - simulation" technology. Through the co - simulation technology, real - time data transfer interfaces are set in both the AMESIM model and the SIMULINK model, enabling the SIMULINK model to provide the hydraulic valve electromagnetic force control signal to the AMESIM model and receive the kinematic pair displacement transferred by the AMESIM model. After setting, both need to call their respective solvers for co - simulation.

[0064] Furthermore, the robust hydraulic transmission system of the robotic arm is implemented in the AMESIM model, constructing a load - sensitive pump and an electro - hydraulic proportional direction valve that are sensitive to external load changes, improving the adaptability to external disturbances while enhancing the efficiency of hydraulic transmission and achieving stepless regulation of the hydraulic valve.

[0065] Furthermore, the robust feedback control system of the robotic arm is implemented in the SIMULINK model, designing a new robust controller. This controller first uses a genetic algorithm combined with H∞ robust control constraints based on historical data or initial tests to robustly optimize the PID controller parameters, and then dynamically adjusts the PID parameters during the control process using fuzzy rules. Through the combination of robust optimization and fuzzy control, giving full play to the advantages of both, on the basis of ensuring robustness, the controller has flexible real - time adjustment capabilities.

[0066] Embodiment 2

[0067] Embodiment 2 is a preferred example of Embodiment 1

[0068] As Figure 1 shown, a robust hydraulic control and simulation method for a robotic arm provided by the present invention includes:

[0069] Step 1: Define the working conditions and object, consider the system composition of the robotic arm according to the complex environment faced, and form a 3D model and a hydraulic schematic diagram.

[0070] Step 2: Single-domain simulation. Considering the actual working conditions, successively construct a multi-body dynamics model describing the motion, a hydraulic transmission model providing drive, and a feedback control model responsible for coordination.

[0071] Step 3: Multi-domain co-simulation. Adopt the co-simulation technology of "model exchange" and "co-simulation", build a data and model transmission path between platforms, and simulate the entire process of real hydraulic control.

[0072] Step 4: Design a robust transmission system. Through the optimization of pumps and valves, improve the environmental adaptability of the system in the hydraulic transmission model.

[0073] Step 5: Design a robust control system. Combine robust optimization and fuzzy rules to improve the performance of the controller in the feedback control model.

[0074] Specifically, as Figure 2 、 Figure 9 shown, Step 1 includes: As the end effector of the equipment, the complex environment and application scenarios faced by the equipment are different, and the motion mode and system composition of the robotic arm are also different. It is necessary to carry out the preliminary preparation work for model construction according to the actual working conditions. On the basis of clarifying the operating principle of the robotic arm, first form a 3D geometric model, determine its component composition, and perform precise 3D modeling of each component through the computer-aided design software CREO to ensure that the dimensions of each component correspond to the physical object one by one. Based on the component design drawings, form the assembly of the entire robotic arm and record the types and central coordinates of all joint kinematic pairs; secondly, form a kinematic model, abstract the joint kinematic pairs of the robotic arm into points at their central coordinates, establish a DH coordinate system according to the relative positions and angles of each joint, and establish the forward / inverse kinematic model of the robotic arm under the DH coordinate system. By inputting the displacement curves of each joint, the end path can be calculated for the verification of the subsequent multi-body dynamics model; finally, form a hydraulic schematic diagram and a control circuit diagram. Considering the actual hydraulic system of the robotic arm, determine the selection and parameters of components such as pumps, valves, fuel tanks, hydraulic cylinders, and pipeline connectors in the hydraulic system, form an accurate hydraulic schematic diagram, and mark necessary information such as the transmission form and the flow direction of hydraulic oil. Combining the hydraulic schematic diagram, design a controller, construct a feedback control circuit for controlling the opening and closing of control valves and the flow direction of hydraulic valves, and form a complete control circuit diagram.

[0075] As Figure 3 、 Figure 4 、 Figure 5As shown in the figure, step 2 includes: based on the overall understanding of the robotic arm from the 3D geometric model, hydraulic schematic diagram, control circuit diagram, etc. formed in step 1, the multi-body dynamics simulation model, hydraulic transmission simulation model, and feedback control simulation model are built separately in three fields: mechanism motion, hydraulic transmission, and coordinated control. The models can reflect various performance indicators and working mechanisms of the robotic arm during operation in the form of simulation, laying a foundation for the establishment of the co-simulation model.

[0076] The multi-body dynamics simulation model of the robotic arm is established in the multi-body dynamics simulation software ADAMS. First, according to the 3D geometric model formed in step 1, all its components are unified into the global coordinate system and imported into ADAMS in the.x_t format to ensure the relative positions of the components of the robotic arm remain unchanged; next, define the materials used for each component, and the software will automatically calculate the centroid of each component and the whole according to the material definition; next, define the kinematic pairs of the whole robotic arm. According to its overall motion form, define the type and central coordinates of the kinematic pairs at the joints of the robotic arm. Common kinematic pair types include translational pair, spherical pair, cylindrical pair, fixed pair, etc., and the central coordinates have been determined using the measurement function of CREO in step 1; finally, conduct model verification. Similarly, according to the overall motion form of the robotic arm, add a drive at the kinematic pair, that is, customize the joint displacement curve, and conduct multi-body dynamics simulation. At the same time, input the drive curve into the previously established forward kinematics model of the robotic arm to obtain the end path solution value, and compare the solution value with the simulation result to verify the accuracy of the model. In addition, adding a drive or kinematic pair will increase constraints and reduce degrees of freedom. After adding, it is necessary to verify whether there are redundant degrees of freedom or overconstraints in the overall model.

[0077] The hydraulic transmission simulation model of the robotic arm is established in the modular simulation software AMESIM. First, according to the hydraulic schematic diagram formed in step 1, clarify the composition and working principle of each component of the hydraulic system, and drag the corresponding modular components in the component library of AMESIM, such as hydraulic pumps, hydraulic valves, hydraulic cylinders, oil storage tanks, etc., and connect the various hydraulic components through pipelines to form a certain loop relationship; next, set appropriate working parameters for the hydraulic components, such as the flow rate and pressure range of the hydraulic pump, the switching mode and control logic of the hydraulic valve, the working stroke, piston area, and cylinder diameter of the hydraulic cylinder, the viscosity and density of the hydraulic oil, etc. Appropriate working parameters of the hydraulic components determine the performance of the hydraulic transmission system and need to be set carefully with reference to the physical object; finally, conduct model verification. After completing the system modeling and parameter setting, observe the dynamic response of the hydraulic system under different load conditions to ensure that its response speed, output force, and other indicators meet the requirements.

[0078] The feedback control simulation model of the robotic arm is established in the modular control software SIMULINK. First, define the key output signals of the hydraulic system, such as the displacement of the hydraulic rod, the pressure of the hydraulic oil, the flow rate, etc. SIMULINK needs to receive these output signals for feedback control and set the corresponding signal receiving ports. Next, clarify the controlled quantities of the hydraulic system, usually the switching mode or control logic of the hydraulic valve, and set the corresponding signal output ports. Finally, design a complete feedback control loop. This loop includes an error calculation module, a controller module, and a control signal output module, which can receive the feedback of the hydraulic system, generate control signals through the controller, and the control method uses a classic PID controller.

[0079] As Figure 6 shown, step 3 includes: First, clarify the overall mechanism of the hydraulic drive of the robotic arm. In this mechanism, the movement of the mechanism is driven by the hydraulic pressure at the joints, forming a certain joint movement trajectory. The pressure and flow rate of the hydraulic oil in the hydraulic system are adjusted by the hydraulic valve, and the hydraulic valve is affected by the signal provided by the feedback control system. At the same time, displacement sensors are installed at the joints of the mechanism, which can transmit the displacement amount to the feedback control system in real time for error calculation of the joint movement trajectory, forming a closed-loop control. Next, determine the model and data transmission path between the three domain simulation platforms, design the transmission interface. The ADAMS platform receives the hydraulic pressure transmitted by the AMESIM platform and outputs the joint displacement to the AMESIM platform. The AMESIM platform receives the control signal transmitted by the SIMULINK platform, outputs the hydraulic pressure to the ADAMS platform, and outputs the received joint displacement to the SIMULINK. The SIMULINK platform receives the joint displacement, forms a feedback control loop, and outputs the control signal to the AMESIM platform. Next, use the model interchange technology to encapsulate the entire ADAMS model into an FMU module and retain the interfaces for receiving hydraulic pressure and outputting joint displacement. After encapsulation, import the entire FMU module into the AMESIM platform. Next, use the co-simulation technology to establish a data path for transmitting joint displacement and control signals in the AMESIM platform and the SIMULINK platform based on the C++ underlying language. Finally, conduct model verification. Preset an ideal joint displacement curve in the SIMULINK platform, generate a control signal to control the hydraulic valve in the AMESIM platform. The hydraulic pressure drives the joint displacement of the mechanism, and the joint displacement will also be received by the SIMULINK platform in real time. If the joint displacement roughly conforms to the preset ideal curve, the performance of the system is verified. During this process, the encapsulated AMAMS platform can be offline, and the AMESIM platform and the SIMULINK platform must be online for co-simulation.

[0080] As Figure 7As shown, step 4 includes: further enhancing the robustness of the verified AMESIM hydraulic transmission system, and the specific approach is divided into two aspects. On the one hand, according to the actual working conditions, replace the original constant current source or constant pressure source in the system with a load-sensing pump, and design the necessary components such as the pump body, variable piston cylinder, flow control valve, pressure control valve, etc. After completion, this hydraulic pump can automatically adjust the output flow according to the load change, reduce the power consumption of the pump under low load conditions, and provide the required flow under high load conditions, realizing the reasonable allocation of hydraulic resources; on the other hand, the original hydraulic valve in the system has poor environmental adaptability, so an electro-hydraulic proportional direction valve controlled by electromagnetic force is designed. Based on the three-position four-way valve in AMESIM, set the voltage as the input of the control signal to adjust the spool position to simulate the influence of the change of electromagnetic force on the spool position. After the spool position changes, the hydraulic oil flow changes, causing the hydraulic driving force received by the hydraulic rod, which is an actuator, to also change; finally, conduct model verification and comparison, and also observe the dynamic response of the hydraulic system under different load conditions, and compare the performance index differences between the system after enhancing the robustness and the original system, such as response time, efficiency, energy consumption, etc. Through simulation verification, ensure that the robustness design enables the hydraulic transmission system to work stably under different loads and improves the overall efficiency of the system.

[0081] As Figure 8 shown, step 5 includes: conducting a robustness design in the verified SIMULINK feedback control system to improve the performance of the original PID controller and enhance the overall adaptive ability of the system. First, carry out mining based on historical data. In the historical data, analyze the performance indicators such as position error, speed error, response time, overshoot, etc. shown by the system with different PID parameters facing different working conditions, which can identify the sensitivity of the system to PID parameters and the dynamic response characteristics of the system itself, and at the same time obtain the regression relationship between the PID parameters and the system performance performance, as well as a suitable range of initial PID parameters. If the historical data is not sufficient to support the above analysis, it can be supplemented with the result data of the joint simulation platform based on the experimental design.

[0082] Next, based on the obtained "parameter - performance" regression relationship and the initial PID parameter range, the initial values of PID parameters are obtained through the optimization method of the genetic algorithm GA. To further enhance the robustness of the controller, the GA algorithm is combined with the H∞ robust control constraint. In this process, the genetic algorithm optimizes the combination of PID parameters in multiple iterations. The fitness function of GA not only considers the conventional performance indicators of the system, such as position error, velocity error, and response time, but also combines the H∞ robust control constraint conditions to ensure that the optimization process can still maintain the stability and efficiency of the system when the load changes, disturbances, or system uncertainties increase, and avoid system instability or excessive response. Through the parameter optimization with robustness constraints, the system can adaptively find the optimal initial values of PID parameters globally while ensuring stable operation.

[0083] Finally, to improve the real - time adjustment ability of the system, fuzzy control is introduced based on the initial values of the adaptive PID parameters in the actual control process. Fuzzy control dynamically adjusts the parameters of the PID controller according to the system error and the error change rate monitored in real - time. By setting a set of fuzzy rules, it can ensure that the control system adjusts the gain of the PID controller according to the real - time feedback. For example, when the error is large and the change rate is fast, the fuzzy controller may increase the proportional gain (Kp) to accelerate the response speed; when the error is small and the change is stable, the integral gain (Ki) is reduced to prevent over - regulation of the system, which enables the controller to quickly respond to load mutations, external disturbances, or system dynamic changes.

[0084] This robust feedback control system ensures the stability and flexibility of the PID controller in the hydraulic system by combining H∞ robust optimization and fuzzy control. On the premise of ensuring robustness, the system can adapt to load changes and disturbances by adjusting the PID parameters in real - time, thus providing more accurate and reliable control performance.

[0085] Through the design of a robust hydraulic transmission system and a robust feedback control system, the present invention proposes a robust hydraulic control strategy for the robotic arm, and this strategy will ultimately be verified in the co - simulation platform. Disturbances are artificially added in the ADAMS platform to simulate the uncertain variable - load environment faced by the robotic arm in the real working condition, and the robotic arm with the robust hydraulic control strategy is made to work. By comparing with the system before improvement, the stability and accuracy of the control system are evaluated. If the performance of the system does not meet the expectations, the component design of the hydraulic transmission system can be further adjusted and the response rules of the controller can be further improved.

[0086] In summary, the present invention is directed to a robotic arm for operation and construction in a complex environment, aiming to improve its action execution accuracy and performance robustness in an uncertain variable load environment. In view of the difficulty of conducting experiments in extreme environments, a multi-domain simulation platform is constructed using co-simulation technology to simulate the entire working process of the robotic arm, reducing the R & D cost and shortening the verification time. Based on the simulation, a research on a robust hydraulic control strategy is carried out, and a robust hydraulic transmission system and a robust feedback control system are designed, improving the overall comprehensive performance of the system. The present invention is applicable to various robotic arms working in complex environments and has certain practical value.

[0087] The present invention also provides a robust hydraulic control and simulation system for a robotic arm. The robust hydraulic control and simulation system for the robotic arm can be implemented by executing the process steps of the robust hydraulic control and simulation method for the robotic arm. That is, those skilled in the art can understand the robust hydraulic control and simulation method for the robotic arm as a preferred implementation manner of the robust hydraulic control and simulation system for the robotic arm.

[0088] Those skilled in the art know that in addition to implementing the systems, devices and their respective modules provided by the present invention in the form of pure computer-readable program codes, the method steps can be logically programmed to enable the systems, devices and their respective modules provided by the present invention to be implemented in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, embedded microcontrollers, etc. to achieve the same program. Therefore, the systems, devices and their respective modules provided by the present invention can be regarded as a kind of hardware component, and the modules included therein for implementing various programs can also be regarded as the structures within the hardware component; the modules for implementing various functions can also be regarded as both software programs for implementing the method and the structures within the hardware component.

[0089] The specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essence of the present invention. Without conflict, the embodiments of the present application and the features in the embodiments can be arbitrarily combined with each other.

Claims

1. A robust hydraulic control and simulation method for a robotic arm, characterized in that: include: Step S1: constructing a multi-body dynamics simulation model, a hydraulic transmission simulation model and a feedback control simulation model based on the three-dimensional model of the robotic arm and the hydraulic principle diagram; Step S2: Based on the multi-body dynamics simulation model, the hydraulic transmission simulation model and the feedback control simulation model, a joint simulation platform of machine-hydraulic-control is built through joint simulation technology; Step S3: Simulate the real working condition based on the joint simulation platform of machine, hydraulic and control, control the hydraulic transmission system through the feedback control simulation model, the hydraulic transmission system generates hydraulic pressure to drive the joint mechanism to move, the multi-body dynamics simulation model obtains the joint displacement information, and transmits it to the feedback control simulation model through the hydraulic transmission simulation model. The feedback control simulation model calculates the error of the joint motion trajectory based on the feedback displacement to form a closed-loop control.

2. The robust hydraulic control and simulation method of a robotic arm according to claim 1, characterized in that: The multi-body dynamics simulation model includes: using CAD design software CREO to build a three-dimensional model of the robot arm, determining the position and type of the kinematic pair, measuring kinematic parameters, and establishing a kinematic theory model that describes the mapping relationship between the robot arm joint trajectory and the end path; importing the three-dimensional model into the multi-body dynamics software ADAMS, defining the material type, center of mass position and kinematic pair type of each component, forming a dynamic model of the robot arm, and verifying the accuracy of the motion form of the dynamic model with the kinematic theory model.

3. The robust hydraulic control and simulation method of a robotic arm according to claim 1, characterized in that: The hydraulic transmission simulation model includes: by referring to the actual hydraulic principle diagram of the mechanical arm, combining and parameterizing the functional components in the modular simulation software AMESIM, and constructing a simulation model of a real hydraulic transmission system.

4. The robust hydraulic control and simulation method of a robotic arm according to claim 1, characterized in that: The feedback control simulation model includes: calling the functional components of the modular control software SIMULINK to build a feedback control system for the hydraulic transmission of the robotic arm.

5. The robust hydraulic control and simulation method of a robotic arm according to claim 1, characterized in that: The step S2 comprises: The multi-body dynamics simulation model receives the hydraulic pressure transmitted by the hydraulic transmission simulation model, and outputs the joint displacement to the hydraulic transmission simulation model; The hydraulic transmission simulation model receives the control signal transmitted by the feedback control simulation model, outputs the hydraulic pressure to the multi-body dynamics simulation model, and outputs the received joint displacement to the feedback control simulation model; The feedback control simulation model receives the joint displacement, forms a feedback control loop, and outputs a control signal to the hydraulic transmission simulation model; The multi-body dynamics simulation model is encapsulated as a whole into an FMU module by using the model interchange technology, and the interface for receiving hydraulic pressure and outputting joint displacement is retained. After the encapsulation is completed, the FMU module is imported into the hydraulic transmission simulation model as a whole; the collaborative simulation technology is used, based on the C++ underlying language, to establish a data path for transmitting joint displacement and control signals in the hydraulic transmission simulation model and the feedback control simulation model; finally, the model is verified, an ideal joint displacement curve is preset in the feedback control simulation model, and a control signal is generated to control the hydraulic valve in the hydraulic transmission simulation model and the joint displacement of the hydraulic pressure drive mechanism, and the joint displacement will also be received in real time by the feedback control simulation model. If the joint displacement meets the preset ideal curve, the performance is verified; In this process, the encapsulated multi-body dynamics simulation model is collaboratively simulated offline or online, and the hydraulic transmission simulation model and the feedback control simulation model are collaboratively simulated online.

6. The robust hydraulic control and simulation method of a robotic arm according to claim 1, characterized in that: The method further comprises: replacing the constant current source or the constant pressure source with a load sensitive pump in the hydraulic transmission system, wherein the load sensitive pump is used to adjust the displacement of the pump according to load pressure feedback; An electro-hydraulic proportional directional valve controlled by electromagnetic force is added to the hydraulic transmission system. The electro-hydraulic proportional directional valve is used to convert a control signal into a valve core force through a proportional solenoid to achieve stepless flow control.

7. The robust hydraulic control and simulation method of a robotic arm according to claim 1, characterized in that: The method further comprises: optimizing the feedback control simulation model; The optimization of the feedback control simulation model includes: based on historical data or initial tests, using a genetic algorithm combined with H∞ robust control constraints to robustly optimize the PID controller parameters in the feedback control simulation model; and then using fuzzy rules to dynamically adjust the PID parameters of the PID controller during the control process.

8. A robust hydraulic control and simulation system for a robotic arm, characterized in that: include: Module M1: Based on the three-dimensional model of the robotic arm and the hydraulic schematic diagram, a multi-body dynamics simulation model, a hydraulic transmission simulation model and a feedback control simulation model are constructed respectively; Module M2: Based on the multi-body dynamics simulation model, hydraulic transmission simulation model and feedback control simulation model, a joint simulation platform of machine-hydraulic-control is built through joint simulation technology; Module M3: Based on the joint simulation platform of machine, hydraulic and control, the real working conditions are simulated, and the hydraulic transmission system is controlled by the feedback control simulation model. The hydraulic transmission system generates hydraulic pressure to drive the joint mechanism to move. The multi-body dynamics simulation model obtains the joint displacement information and transmits it to the feedback control simulation model through the hydraulic transmission simulation model. The feedback control simulation model calculates the error of the joint motion trajectory based on the feedback displacement to form a closed-loop control.

9. The robust hydraulic control and simulation system for a robotic arm according to claim 8, characterized in that: The multi-body dynamics simulation model includes: using CAD design software CREO to build a three-dimensional model of the robot arm, determine the position and type of the kinematic pair, measure kinematic parameters, and establish a kinematic theory model that describes the mapping relationship between the robot arm joint trajectory and the end path; importing the three-dimensional model into the multi-body dynamics software ADAMS, defining the material type, center of mass position and kinematic pair type of each component, forming a dynamic model of the robot arm, and verifying the accuracy of the kinematic model motion form with the kinematic theory model; The hydraulic transmission simulation model comprises: by referring to the actual hydraulic principle diagram of the mechanical arm, combining and parameterizing the functional components in the modular simulation software AMESIM, and constructing a simulation model of the real hydraulic transmission system; The feedback control simulation model includes: calling the functional components of the modular control software SIMULINK to build a feedback control system for the hydraulic transmission of the robotic arm.

10. The robust hydraulic control and simulation system for a robotic arm according to claim 8, characterized in that: The module M2 comprises: The multi-body dynamics simulation model receives the hydraulic pressure transmitted by the hydraulic transmission simulation model, and outputs the joint displacement to the hydraulic transmission simulation model; The hydraulic transmission simulation model receives the control signal transmitted by the feedback control simulation model, outputs the hydraulic pressure to the multi-body dynamics simulation model, and outputs the received joint displacement to the feedback control simulation model; The feedback control simulation model receives the joint displacement, forms a feedback control loop, and outputs a control signal to the hydraulic transmission simulation model; The multi-body dynamics simulation model is encapsulated as a whole into an FMU module by using the model interchange technology, and the interface for receiving hydraulic pressure and outputting joint displacement is retained. After the encapsulation is completed, the FMU module is imported into the hydraulic transmission simulation model as a whole; the collaborative simulation technology is used, based on the C++ underlying language, to establish a data path for transmitting joint displacement and control signals in the hydraulic transmission simulation model and the feedback control simulation model; finally, the model is verified, an ideal joint displacement curve is preset in the feedback control simulation model, and a control signal is generated to control the hydraulic valve in the hydraulic transmission simulation model and the joint displacement of the hydraulic pressure drive mechanism, and the joint displacement will also be received in real time by the feedback control simulation model. If the joint displacement meets the preset ideal curve, the performance is verified; In this process, the encapsulated multi-body dynamics simulation model is collaboratively simulated offline or online, and the hydraulic transmission simulation model and the feedback control simulation model are collaboratively simulated online.

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