Self-sensing sliding friction characteristics modeling and control optimization method and device for unstructured terrain

Abstract

The present invention discloses a self-sensing sliding friction characteristic modeling and control optimization method and device for unstructured terrain, including: S1. establishing a normal stress distribution model and a tangential stress distribution model when the wheel contacts the lunar soil; S2. adjusting the normal stress distribution model and the tangential stress distribution model based on the friction characteristics of the lunar soil, and establishing a sliding friction characteristic model based on the physical characteristics of the lunar soil; S3. correcting the traction force and driving torque of the wheel based on the sliding friction characteristic model, and feeding back into the PID control model, dynamically adjusting the control input through the error signal of the wheel speed, so as to accurately control the movement process of the lunar rover in real time; the present invention dynamically introduces the physical characteristics of the lunar soil into the modeling of the friction coefficient, and realizes accurate control of the lunar rover's driving process through the coupling of the dynamic state of the wheel and the dynamic feedback mechanism of the PID control, providing theoretical and technical support for the stable driving of the lunar rover in the complex lunar environment.

Description

Technical Field

[0001] The present invention relates to the field of aerospace technology, and more particularly to a method and device for self-sensing sliding friction characteristic modeling and control optimization for unstructured terrain. Background Art

[0002] For unstructured terrain, similar to the ground, sliding friction characteristics are one of the key factors affecting the driving performance of the lunar rover. In the lunar environment, the friction between the wheels and the lunar soil not only depends on the physical properties of the lunar soil, but is also affected by multiple factors such as wheel design, driving speed, and load. Accurate modeling and optimal control of sliding friction characteristics are of great significance to improving the driving performance of the lunar rover and ensuring the smooth progress of the exploration mission.

[0003] Modeling sliding friction characteristics is fundamental to lunar rover control technology. Early research focused on classical friction models, such as the Coulomb friction model and the viscous friction model. While simple, these models have limited applicability in complex environments.

[0004] In recent years, with the in-depth study of the physical properties of lunar soil, some fitting models based on experimental data have been proposed. These models establish more accurate friction characteristic models by experimentally measuring the friction coefficient under different conditions. However, most of these models assume that the friction coefficient is a constant and cannot reflect the dynamic changes of the friction coefficient during actual driving.

[0005] In terms of control optimization, traditional PID control methods are widely used. For example, a PID controller is used to optimize the target steering angle, the target steering angle is calculated through a pure tracking algorithm, and then the stable angle is output; a fractional-order PID control algorithm based on data-driven control is used for control, and its parameters are optimized using a particle swarm optimization (PSO) algorithm, which can effectively overcome the increase in tracking error caused by changes in path curvature; however, when faced with complex environments and dynamic changes, PID control gradually exhibits problems of slow response speed and poor adaptability.

[0006] In order to improve control performance, some advanced control methods such as fuzzy control, adaptive control and model predictive control have been introduced. These methods can better adapt to environmental changes and improve the driving performance of the vehicle by adjusting control parameters in real time. However, it is also necessary to consider the complexity of the algorithm implementation to ensure that the calculation can be completed in real time in the embedded system. By real-time monitoring of the friction between the wheels and the ground and combining the driving status of the vehicle, the control strategy can be dynamically adjusted. Some studies have used sensor networks and machine learning algorithms to realize real-time estimation of the friction coefficient. However, most of these methods rely on complex sensor systems, which increases the cost and complexity of the system.

[0007] Therefore, how to accurately model and optimize the control of sliding friction characteristics to improve the driving performance of the lunar rover in the unstructured terrain on the lunar surface is an urgent problem that technicians in this field need to solve. Summary of the Invention

[0008] In view of this, the present invention provides a method and device for self-sensing sliding friction characteristic modeling and control optimization for unstructured terrain to solve some of the technical problems mentioned in the background technology.

[0009] In order to achieve the above object, the present invention adopts the following technical solutions:

[0010] A self-sensing sliding friction characteristic modeling and control optimization method for unstructured terrain includes the following steps:

[0011] S1. Establish normal stress distribution models and tangential stress distribution models when the wheels contact the lunar soil;

[0012] S2. Adjust the normal stress distribution model and the tangential stress distribution model based on the friction characteristics of the lunar soil, and establish a sliding friction characteristic model based on the physical properties of the lunar soil;

[0013] S3. Based on the sliding friction characteristic model, the wheel traction and driving torque are corrected and fed back into the PID control model. The control input is dynamically adjusted through the error signal of the wheel speed to accurately control the movement process of the lunar rover in real time.

[0014] Preferably, in step S1, based on Bekker theory, a normal stress distribution model and a tangential stress distribution model are established when the wheel contacts the lunar soil.

[0015] Preferably, the specific content of adjusting the normal stress model based on the friction characteristics of lunar soil is:

[0016] The normal stress model was adjusted according to the relationship between the cohesive deformation modulus and friction deformation modulus and the friction coefficient in the normal stress model. The normal stress was corrected based on the changes in the contact area and pressure distribution between the wheel and the lunar soil caused by wheel deformation, and the adjusted normal stress distribution model was obtained.

[0017] Preferably, the specific content of adjusting the tangential stress model based on the friction characteristics of lunar soil is:

[0018] The tangential stress distribution is adjusted based on the relationship between the cohesive stress, internal friction angle and friction coefficient in the tangential stress distribution model. The tangential stress is corrected based on the influence of the change in wheel speed on the relative motion between the wheel and the lunar soil and the friction force, and the adjusted tangential stress distribution model is obtained.

[0019] Preferably, the established sliding friction characteristic model of lunar soil physical properties includes an adjusted normal stress distribution model and a tangential stress distribution model;

[0020] The adjusted normal stress distribution model is:

[0021] when hour,

[0022]

[0023] when hour,

[0024]

[0025] in, is the basic cohesive deformation modulus, is the basic friction deformation modulus, is the friction coefficient, is the soil deformation index, is the wheel radius, is an angle variable, indicating the position of the contact point between the wheel and the lunar soil, 、 、 are the maximum contact angle, minimum contact angle and intermediate contact angle of the contact area between the wheel shape and the soil, τ is the time constant, and Δτ is the change of the time constant;

[0026] The adjusted tangential stress distribution model is:

[0027]

[0028]

[0029] in, is the basic cohesive stress, is the basic internal friction angle, is the normal pressure of the wheel on the lunar soil, is the soil shear deformation modulus, is the shear deformation at the contact surface between the lunar soil and the rim, is the maximum wheel sinking angle, Changes in wheel speed, is the contact angle coefficient.

[0030] Preferably, the corrected wheel traction and driving torque are calculated as:

[0031]

[0032] in, is the corrected traction force, is the corrected driving torque, b is the width of the wheel, is the tangential stress distribution outside the contact area between the wheel and the lunar soil, is the tangential stress distribution on the inner side of the contact area between the wheel and the lunar soil.

[0033] Preferably, the method for dynamically adjusting the control input is:

[0034]

[0035] in, is the target speed of control, is the actual speed, is the error signal between the desired speed and the actual speed, is the control input of the motor torque, 、 、 are proportional, integral and differential control gains respectively, is the change in traction force, is the change in driving torque, and are the feedback gains of traction and driving torque respectively.

[0036] A self-sensing sliding friction characteristic modeling and control optimization device for unstructured terrain, based on the self-sensing sliding friction characteristic modeling and control optimization method for unstructured terrain, includes: a sliding friction characteristic model building and adjustment module, and a dynamically adjusted PID control module;

[0037] The model building and adjustment module is used to establish the normal stress distribution model and the tangential stress distribution model when the wheel contacts the lunar soil. The normal stress distribution model and the tangential stress distribution model are adjusted based on the friction characteristics of the lunar soil to establish a sliding friction characteristic model based on the physical characteristics of the lunar soil.

[0038] The dynamically adjusted PID control module is used to correct the wheel traction and driving torque based on the sliding friction characteristic model, and feed it back into the PID control model. The control input is dynamically adjusted through the error signal of the wheel speed to accurately control the movement process of the lunar rover in real time.

[0039] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements a self-sensing sliding friction characteristic modeling and control optimization method for unstructured terrain.

[0040] A processing terminal includes a memory and a processor. The memory stores a computer program that can be run on the processor. When the processor executes the computer program, the method for modeling and optimizing the self-sensing sliding friction characteristics for unstructured terrain is implemented.

[0041] It can be seen from the above technical solution that compared with the existing technology, the present invention discloses a self-sensing sliding friction characteristic modeling and control optimization method and device for unstructured terrain, which dynamically introduces the physical properties of lunar soil into the modeling of the friction coefficient, establishes a sliding friction characteristic model based on the physical properties of lunar soil, and can predict the change of friction coefficient in real time, providing a more accurate basis for control optimization; and through the coupling of the dynamic state of the wheels and the dynamic feedback mechanism of PID control, it can better adapt to the dynamic changes in complex environments and realize precise control of the driving process of the lunar rover. The present invention not only improves the adaptability and passability of the lunar rover on the complex lunar surface, but also provides theoretical and technical support for the stable driving of manned lunar rover in complex lunar environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0043] Figure 1 A schematic diagram of a self-sensing sliding friction characteristic modeling and control optimization method for unstructured terrain provided by the present invention;

[0044] Figure 2 Schematic diagram of the sliding friction characteristic model provided by the present invention;

[0045] Figure 3 A schematic diagram of the main parameters of sliding movement provided by the present invention;

[0046] Figure 4 A schematic diagram of the actual test route and acceleration and deceleration planning provided by an embodiment of the present invention;

[0047] Figure 5 A schematic diagram comparing actual test sites and test routes provided by an embodiment of the present invention;

[0048] Figure 6 A schematic diagram showing a comparison of key parameters of actual tests conducted under flat terrain conditions according to an embodiment of the present invention;

[0049] Figure 7A schematic diagram showing a comparison of key parameters of actual tests conducted under undulating terrain conditions according to an embodiment of the present invention;

[0050] Figure 8 A schematic diagram of comparison of sideslip angle, distance offset, and speed variance under different algorithms using a flat gravel desert and an undulating mixed desert as examples provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0051] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0052] Example 1

[0053] This embodiment discloses a self-sensing sliding friction characteristic modeling and control optimization method for unstructured terrain, comprising the following steps:

[0054] S1. Establish normal stress distribution models and tangential stress distribution models when the wheels contact the lunar soil;

[0055] S2. Adjust the normal stress distribution model and the tangential stress distribution model based on the friction characteristics of the lunar soil, and establish a sliding friction characteristic model based on the physical properties of the lunar soil;

[0056] S3. Based on the sliding friction characteristic model, the wheel traction and driving torque are corrected and fed back into the PID control model. The control input is dynamically adjusted through the error signal of the wheel speed to accurately control the movement process of the lunar rover in real time.

[0057] To further implement the above technical solution, in step S1, a normal stress distribution model and a tangential stress distribution model are established when the wheel contacts the lunar soil according to Bekker theory.

[0058] Due to the complexity of the lunar soil environment and terrain, only the effect of friction itself on the movement of the lunar rover is considered. It is assumed that the contact area between the lunar rover wheels and the lunar soil is elliptical, and the adhesion of the lunar soil is ignored. Only the sliding friction is considered, such as Figure 2 , the normal stress distribution model is established as:

[0059] when When the normal stress for:

[0060]

[0061] when When the normal stress for:

[0062]

[0063] in, is the cohesive deformation modulus of the soil, is the friction deformation modulus of soil, is the soil deformation index, is the wheel radius, is an angle variable, indicating the position of the contact point between the wheel and the lunar soil, 、 、 is the angle parameter related to the wheel shape and contact area;

[0064] The expression of the tangential stress distribution model is:

[0065]

[0066] The expression of shear deformation is:

[0067]

[0068] in, represents the soil cohesive stress, is the normal pressure of the wheel on the lunar soil, represents the soil internal friction angle, is the soil shear deformation modulus, is the shear deformation at the contact surface between the lunar soil and the rim, is the wheel slip rate, is the maximum wheel sinking angle.

[0069] The physical properties of lunar soil (such as particle size and density) have a significant impact on the friction coefficient. The friction characteristics of lunar soil are further refined into the following model:

[0070]

[0071] in, is the friction coefficient, is the basic friction coefficient, is the density influence coefficient, is the particle irregularity coefficient, is the lunar soil density, It is a function of particle size, usually the inverse of the particle diameter.

[0072] Traditional friction characteristic models usually assume that the friction coefficient is a constant or is only related to the basic physical properties of the soil. The present invention dynamically introduces the physical properties of the lunar soil, such as particle size, density and water content, into the calculation of the friction coefficient, so that the friction coefficient can be adjusted in real time according to the actual physical state of the lunar soil. This dynamic modeling method can more accurately reflect the actual interaction between the lunar soil and the wheels, especially under the complex terrain and environmental conditions on the lunar surface, where the physical properties of the lunar soil may change.

[0073] In order to further implement the above technical solution, the specific content of adjusting the normal stress model based on the friction characteristics of lunar soil is as follows:

[0074] The normal stress model was adjusted based on the relationship between the cohesive deformation modulus and the frictional deformation modulus and the friction coefficient in the normal stress model. The normal stress was corrected based on the changes in the contact area and pressure distribution between the wheel and the lunar soil caused by wheel deformation, resulting in an adjusted normal stress distribution model.

[0075] Cohesive deformation modulus in the normal stress model and friction deformation modulus and friction coefficient The relationship is:

[0076]

[0077] in, and are the basic cohesive deformation modulus and the basic friction deformation modulus;

[0078] The wheel deformation will also cause the contact area and pressure distribution between the wheel and the lunar soil to change. The corrected normal stress is:

[0079]

[0080] Will and Substituting into the established normal stress distribution model formula, the adjusted normal stress distribution model is obtained.

[0081] To further implement the above technical solution, the specific contents of adjusting the tangential stress model based on the friction characteristics of lunar soil are as follows:

[0082] The tangential stress distribution model is based on the relationship between the cohesive stress and the internal friction angle and the friction coefficient. The tangential stress distribution is then adjusted based on the effect of wheel speed changes on the relative motion between the wheel and the lunar soil, as well as the friction force. This results in an adjusted tangential stress distribution model.

[0083] The relationship between the cohesive stress and internal friction angle and the friction coefficient in the tangential stress distribution model is:

[0084]

[0085] in, and are foundation cohesive stress and foundation internal friction angle respectively;

[0086] At the same time, the wheel speed changes It will affect the relative motion between the wheels and the lunar soil, and thus affect the friction. The corrected tangential stress is:

[0087]

[0088] Will and Substituting into the expression of the tangential stress distribution model, the adjusted tangential stress distribution model is obtained.

[0089] In order to further implement the above technical solutions, the sliding friction characteristic model of lunar soil physical properties was established, including the adjusted normal stress distribution model and tangential stress distribution model;

[0090] The adjusted normal stress distribution model is:

[0091] when hour,

[0092]

[0093] when hour,

[0094]

[0095] in, is the basic cohesive deformation modulus, is the basic friction deformation modulus, is the friction coefficient, is the soil deformation index, is the wheel radius, is an angle variable, indicating the position of the contact point between the wheel and the lunar soil, 、 、 are the maximum contact angle, minimum contact angle, and median contact angle of the wheel shape and soil contact area, τ is the time constant, which is used to describe the response speed of the system to input changes, and Δτ is the change of the time constant, which is used to describe the changes of the system dynamic characteristics with time or conditions;

[0096] The maximum contact angle usually corresponds to the starting or ending point of the contact between the wheel and the soil. When calculating the normal stress distribution between the wheel and the soil, it is used to determine the boundary of the contact area. It reflects the contact range of the wheel on the soil surface and is an important parameter affecting the traction and sinking depth of the wheel; the minimum contact angle usually corresponds to the innermost point of contact between the wheel and the soil. It is used to define the inner boundary of the contact area between the wheel and the soil. Starting from the maximum contact angle, it determines the complete area of ​​contact between the wheel and the soil, thereby affecting the traction and driving torque of the wheel; the intermediate angle is usually used to describe the geometric center of the contact area between the wheel and the soil. Under complex soil conditions, the contact area between the wheel and the soil may not be uniform. At this time, the intermediate angle is used to describe the middle position of the contact area, helping to more accurately calculate the distribution of normal stress and tangential stress.

[0097] The adjusted tangential stress distribution model is:

[0098]

[0099]

[0100] in, is the basic cohesive stress, is the basic internal friction angle, is the normal pressure of the wheel on the lunar soil, is the soil shear deformation modulus, is the shear deformation at the contact surface between the lunar soil and the rim, is the maximum wheel sinking angle, Changes in wheel speed, is the contact angle coefficient.

[0101] By dynamically adjusting the friction coefficient, the lunar rover's adaptability and passability under different lunar soil conditions can be improved. This invention not only considers the impact of wheel deformation on friction characteristics, but also introduces the impact of wheel speed changes on friction characteristics. By modifying the formula, the dynamic state of the wheel (such as deformation and speed changes) is coupled with the friction characteristics, so that the friction characteristics can be dynamically adjusted according to the actual operating state of the wheel. This coupling method can more accurately describe the changes in friction characteristics of the lunar rover when driving at high speed or in complex terrain conditions. For example, the wheel may deform when driving at high speed, and the change in speed will also affect the magnitude of the friction force.

[0102] Friction characteristics directly affect the wheel's traction, vertical reaction force, and driving torque. The control of these forces and torques is the basis of lunar rover motion control. During high-speed movement, the main parameter for measuring the degree of sliding movement and deviation from the original trajectory is the horizontal distance deviation. , sideslip angle deviation and the velocity variance within the moving interval ,like Figure 3 ;

[0103] The basic form of the PID control model is:

[0104]

[0105] in, is the control input of the motor torque, is the difference between the desired speed and the actual speed (error signal), 、 、 are proportional, integral and differential control gains respectively.

[0106] The actual friction force distribution is calculated through the normal stress distribution model and the tangential stress distribution model. The friction force distribution directly affects the traction and driving torque between the wheel and the lunar soil. Specifically: the normal stress distribution in the contact area between the wheel and the lunar soil is calculated through the normal stress distribution model, which directly affects the distribution of normal force; the tangential stress distribution in the contact area between the wheel and the lunar soil is calculated through the tangential stress distribution model, which directly affects the distribution of tangential friction force; friction force calculation, calculates the total friction force based on the normal stress and tangential stress distribution; traction force and driving torque correction, uses the calculated friction force distribution to correct the traction force and driving torque.

[0107] In order to further implement the above technical solution, the corrected wheel traction and driving torque are calculated based on the normal stress distribution model and tangential stress distribution model adjusted by friction characteristics:

[0108]

[0109] in, is the corrected traction force, is the corrected driving torque, b is the width of the wheel (the area of ​​the wheel in contact with the lunar soil, which affects the distribution of normal stress and tangential stress). In the friction characteristic modeling of the lunar rover, and It usually represents the tangential stress distribution parameter related to the contact area between the wheel and the lunar soil, and is used to describe the tangential stress distribution in the contact area between the wheel and the lunar soil. Specifically: is the tangential stress distribution outside the wheel-soil contact area (close to the wheel edge), is the tangential stress distribution on the inner side (close to the center of the wheel) of the contact area between the wheel and the lunar soil;

[0110] Feeding back the friction-corrected traction and driving torque into the PID control model allows for dynamic adjustment of control inputs. , the specific formula is:

[0111] ;

[0112] Assume that the target speed of control is , the actual speed is , then the error signal It can be expressed as:

[0113] ;

[0114] In order to further implement the above technical solution, the control input is dynamically adjusted to:

[0115]

[0116] in, is the target speed of control, is the actual speed, is the error signal between the desired speed and the actual speed, is the control input of the motor torque, 、 、 are proportional, integral and differential control gains respectively, is the change in traction force, is the change in driving torque, and are the feedback gains of traction and driving torque respectively.

[0117] By dynamically correcting the friction characteristics, the driving efficiency and stability of the lunar rover can be improved. The present invention directly feeds back the corrected friction characteristics (such as traction and driving torque) into the PID control model to form a closed-loop control system. This feedback mechanism can dynamically adjust the control input according to the real-time changes in the friction characteristics, thereby achieving precise control of the lunar rover's driving process; traditional PID control usually assumes that the friction characteristics are fixed values ​​and cannot adapt to the complex friction environment on the lunar surface. By introducing dynamic feedback of the friction characteristics, the present invention can adjust the control strategy in real time, thereby improving the lunar rover's driving performance and obstacle crossing ability under different lunar soil conditions. This dynamic adjustment mechanism is of great significance to the lunar rover's autonomous navigation and mission execution on the complex lunar surface.

[0118] Example 2

[0119] This embodiment is verified by experiments in a simulated lunar soil environment. Specifically:

[0120] Experimental design:

[0121] Different types of desert areas were selected for experiments, including fine sand desert, gravel desert and mixed desert, to simulate the different terrain and soil characteristics of the lunar surface; a lunar rover sliding friction characteristics test system was built, including deserts simulating different friction forces, a lunar rover model, sensors, and a data acquisition and processing system.

[0122] During the experiment, an aluminum metal wheel was selected for the experiment. The model parameters of the wheel are shown in Table 1 below:

[0123] Table 1 Parameters of lunar rover metal wheels:

[0124]

[0125] The simulated lunar soil is constructed using desert fine sand. Considering the comparison with lunar soil, millimeter-level fine sand combined with water content is used for simulation. The parameters of different simulated lunar soils are shown in Table 2 below:

[0126] Table 2 Simulated lunar soil parameters:

[0127]

[0128] Carry out actual test route and acceleration and deceleration planning, such as Figure 4 During the experiment, the vehicle traveled at a speed of 0.5-3 m / s, weighed 100 kg, and covered a distance of 100-200 m on the test site. A data acquisition system was used to collect real-time data on friction, normal force, and wheel speed, storing it in a computer. The rover's speed and sideslip data were recorded at different times and in different types of deserts, yielding the experimental classification and results shown in Table 3.

[0129] Table 3

[0130]

[0131] It can be seen that when the lunar rover travels at high speeds in fine sand deserts, it experiences significant side slip and a low coefficient of friction. This is because the fine sand is highly fluid, resulting in less friction between the wheels and the sand surface, causing the wheels to slip easily. In gravel deserts, the lunar rover travels at relatively low speeds, experiences less side slip, and has a higher coefficient of friction. This is primarily due to the larger gravel particles and rougher surface, which provide greater friction and prevent the wheels from slipping. Driving performance in mixed deserts is somewhere between fine sand and gravel deserts, with a relatively moderate coefficient of friction and speed.

[0132] like Figure 5In the test site simulating the lunar soil environment, the red-framed area is used to simulate the flat terrain of the lunar surface. The terrain undulation in this area is less than 0.5 meters, the slope is less than 10 degrees, and obstacles such as pits and rocks are less than 10 centimeters, which can effectively simulate the flat terrain of the lunar surface; the blue-framed area is used to simulate the undulating terrain. The terrain undulation in this area is less than 2 meters, the slope is less than 30 degrees, and there are large pits and rocks with a diameter of more than 0.5 meters, which can effectively simulate the undulating terrain of the lunar surface; the dotted line in the figure is the expected route. During the test, a remote-controlled vehicle is used to travel along the expected route at a speed of Figure 4 The solid line is the actual recorded route for comparison with the expected route.

[0133] The test was conducted by manually cleaning and arranging different terrain subdivisions in the red frame, where the green path is a fine sand desert, the purple path is a gravel desert, and the yellow path is a mixed desert; the terrain subdivisions are also arranged in the blue frame, where the khaki is a mixed desert, the light yellow left half is a gravel desert, and the right half is a fine sand desert.

[0134] Performance Comparison

[0135] A detailed analysis and comparison of specific indicators are conducted based on the test results of the actual site, mainly comparing the sideslip angle, distance offset and real-time speed of different algorithms in different test sites.

[0136] Figure 6 Figure (a) shows the distance offset during driving on a flat terrain gravel desert. Figure 6 Figure (b) shows the three types of desert driving routes on flat terrain. Figure 6 (c) is the driving speed in the flat terrain gravel desert. Figure 6 Figure (d) shows the sideslip angle during driving on a flat terrain gravel desert;

[0137] Figure 7 Figure (a) shows the distance offset during driving in a mixed desert with undulating terrain. Figure 7 Figure (b) shows the three types of desert driving routes with undulating terrain. Figure 7 Figure (c) shows the driving speed in a mixed desert with undulating terrain. Figure 7 Figure (d) shows the sideslip angle during driving on undulating terrain mixed desert;

[0138] In this embodiment, the sideslip angle, distance offset and speed variance under different algorithms are compared by taking flat terrain gravel desert and undulating terrain mixed desert as examples. The results are shown in Table 4 and Figure 8 ;

[0139] Table 4:

[0140]

[0141] Figure 8 Figure (a) shows the comparison of sideslip angle, distance offset and speed variance under different algorithms on flat terrain gravel desert. Figure 8 Figure (b) shows the comparison of sideslip angle, distance offset and speed variance under different algorithms for an undulating mixed desert.

[0142] It can be seen that in the mixed desert with undulating terrain, compared with the previous algorithm, the sideslip angle is reduced by an average of 17.59%, the distance offset is reduced by an average of 36.57%, and the speed variance is significantly reduced; in the flat gravel desert, compared with the previous algorithm, the sideslip angle is reduced by an average of 27.76%, the distance offset is reduced by an average of 49.58%, and the speed variance is significantly reduced.

[0143] The present invention comprehensively considers the influence of various physical properties of lunar soil, such as particle size and density, on the friction coefficient, and links these physical properties to the friction coefficient through functional relationships (such as the inverse of particle size, the linear relationship of density, etc.). This comprehensive consideration method can more comprehensively reflect the influence of the physical properties of lunar soil on the friction characteristics; the physical properties of lunar soil may vary significantly in different areas of the lunar surface. By comprehensively considering multiple physical properties, the friction coefficient can be more accurately predicted and adjusted, thereby improving the adaptability and reliability of the lunar rover under different lunar soil conditions; the present invention also verifies the effectiveness of the model through experiments. Through experiments in a simulated lunar soil environment, the actual effects of the dynamic friction characteristic model and PID control strategy are verified, which provides strong support for the practical application of the lunar rover and ensures the effectiveness and reliability of the control strategy in actual missions.

[0144] Example 3

[0145] This embodiment discloses a self-sensing sliding friction characteristic modeling and control optimization device for unstructured terrain, based on a self-sensing sliding friction characteristic modeling and control optimization method for unstructured terrain, including: a sliding friction characteristic model construction and adjustment module, and a dynamically adjusted PID control module;

[0146] The model building and adjustment module is used to establish the normal stress distribution model and the tangential stress distribution model when the wheel contacts the lunar soil. The normal stress distribution model and the tangential stress distribution model are adjusted based on the friction characteristics of the lunar soil to establish a sliding friction characteristic model based on the physical characteristics of the lunar soil.

[0147] The dynamically adjusted PID control module is used to correct the wheel traction and driving torque based on the sliding friction characteristic model, and feed it back into the PID control model. The control input is dynamically adjusted through the error signal of the wheel speed to accurately control the movement process of the lunar rover in real time.

[0148] Example 4

[0149] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements a self-sensing sliding friction characteristic modeling and control optimization method for unstructured terrain.

[0150] Example 5

[0151] A processing terminal includes a memory and a processor. The memory stores a computer program that can be run on the processor. When the processor executes the computer program, a self-sensing sliding friction characteristic modeling and control optimization method for unstructured terrain is implemented.

[0152] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Reference can be made to the common and similar parts between the various embodiments. For the devices disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the method description.

[0153] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A self-sensing sliding friction characteristic modeling and control optimization method for unstructured terrain, characterized by: The following steps are involved: S1. Establish normal stress distribution models and tangential stress distribution models when the wheels contact the lunar soil; S2. Adjust the normal stress distribution model and the tangential stress distribution model based on the friction characteristics of the lunar soil, and establish a sliding friction characteristic model based on the physical properties of the lunar soil; S3. Based on the sliding friction characteristic model, the wheel traction and driving torque are corrected and fed back into the PID control model. The control input is dynamically adjusted using the wheel speed error signal to accurately control the lunar rover's motion in real time. The specific content of adjusting the normal stress model based on the friction characteristics of lunar soil is as follows: The normal stress model was adjusted based on the relationship between the cohesive deformation modulus and the frictional deformation modulus and the friction coefficient in the normal stress model. The normal stress was corrected based on the changes in the contact area and pressure distribution between the wheel and the lunar soil caused by wheel deformation, resulting in an adjusted normal stress distribution model. The specific content of adjusting the tangential stress model based on the friction characteristics of lunar soil is as follows: The tangential stress distribution is adjusted based on the relationship between the cohesive stress, internal friction angle and friction coefficient in the tangential stress distribution model. The tangential stress is corrected based on the influence of the change in wheel speed on the relative motion between the wheel and the lunar soil and the friction force, and the adjusted tangential stress distribution model is obtained.

2. The self-sensing sliding friction characteristic modeling and control optimization method for unstructured terrain according to claim 1 is characterized in that: In step S1, based on Bekker theory, the normal stress distribution model and the tangential stress distribution model when the wheel contacts the lunar soil are established.

3. The self-sensing sliding friction characteristic modeling and control optimization method for unstructured terrain according to claim 1 is characterized in that: The sliding friction characteristic model of lunar soil physical properties established includes the adjusted normal stress distribution model and tangential stress distribution model; The adjusted normal stress distribution model is: When θ m When ≤θ≤θ1, When θ2≤θ≤θ m hour, Among them, K c0 is the basic cohesive deformation modulus, K φ0 is the basic friction deformation modulus, μ is the friction coefficient, n is the soil deformation index, r is the wheel radius, θ is the angle variable, indicating the position of the contact point between the wheel and the lunar soil, θ1, θ2, θ m are the maximum contact angle, minimum contact angle and intermediate contact angle of the contact area between the wheel shape and the soil, τ is the time constant, and Δτ is the change of the time constant; The adjusted tangential stress distribution model is: j=r[(θ0-θ)-(1-s′)(sinθ0-sinθ)] Among them, c0 is the basic cohesive stress, φ0 is the basic internal friction angle, p is the normal pressure of the wheel on the lunar soil, K is the soil shear deformation modulus, j is the shear deformation at the contact surface between the lunar soil and the wheel rim, θ0 is the maximum sinking angle of the wheel, Δv is the change in wheel speed, and s' is the contact angle coefficient.

4. The self-sensing sliding friction characteristic modeling and control optimization method for unstructured terrain according to claim 3 is characterized in that: The corrected wheel traction and driving torque are calculated as: Among them, F x is the corrected traction force, T is the corrected driving torque, b is the width of the wheel, τ′1(θ) is the tangential stress distribution on the outside of the contact area between the wheel and the lunar soil, and τ′2(θ) is the tangential stress distribution on the inside of the contact area between the wheel and the lunar soil.

5. The self-sensing sliding friction characteristic modeling and control optimization method for unstructured terrain according to claim 4 is characterized in that: The method to dynamically adjust the control input is: Among them, v d is the target speed of control, v(t) is the actual speed, e(t)=v d -v(t) is the error signal between the desired speed and the actual speed, u(t) is the control input of the motor torque, K p , K i , K d They are proportional, integral and differential control gains, ΔF x is the change in traction force, ΔT is the change in driving torque, K f and K t are the feedback gains of traction and driving torque respectively.

6. A self-sensing sliding friction characteristic modeling and control optimization device for unstructured terrain, characterized by: A self-sensing sliding friction characteristic modeling and control optimization method for unstructured terrain based on any one of claims 1 to 5, comprising: a sliding friction characteristic model construction and adjustment module, and a dynamically adjusted PID control module; The model building and adjustment module is used to establish the normal stress distribution model and the tangential stress distribution model when the wheel contacts the lunar soil. The normal stress distribution model and the tangential stress distribution model are adjusted based on the friction characteristics of the lunar soil to establish a sliding friction characteristic model based on the physical characteristics of the lunar soil. The dynamically adjusted PID control module is used to correct the wheel traction and driving torque based on the sliding friction characteristic model, and feed it back into the PID control model. The control input is dynamically adjusted through the error signal of the wheel speed to accurately control the movement process of the lunar rover in real time.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for modeling and optimizing the self-sensing sliding friction characteristics for unstructured terrain as described in any one of claims 1 to 5 is implemented.

8. A processing terminal comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, characterized in that: When the processor executes the computer program, it implements the self-sensing sliding friction characteristic modeling and control optimization method for unstructured terrain as described in any one of claims 1 to 5.

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