Unmanned mining dump truck ABS control method based on active disturbance rejection control

Abstract

The invention discloses an unmanned mining dump truck ABS control method based on active disturbance rejection control. The method comprises the steps that a wheel speed sensor is arranged to monitor and record wheel speed data in real time; acquiring and recording the speed information of the unmanned vehicle in real time by using a vehicle inertial navigation system; converting a slip rate control target into a specific wheel speed control target by defining the slip rate; designing a linear expansion state observer, and estimating the wheel speed and the total disturbance by using the real-time driving torque and the wheel speed data; linear state error feedback control is designed, and a control law is calculated according to real-time vehicle speed, wheel speed estimation and total disturbance estimation; and the control law obtained through calculation serves as a driving torque signal and is transmitted to a throttle valve control unit of the unmanned mine car, the opening degree of a valve is changed, and ABS control is conducted on the unmanned mine car during braking. According to the method, the advantages of PID are developed by adopting an active-disturbance-rejection control method, the defects of the PID are overcome, engineering implementation is easy, robustness is achieved, and the strong anti-disturbance capability is achieved.

Description

Technical Field

[0001] The invention relates to the technical field of unmanned driving in mines, and in particular to an ABS control method for an unmanned mining dump truck based on anti-disturbance control. Background Art

[0002] With the vigorous development of the construction industry at home and abroad in the new era, the demand for raw materials such as ore, sand and stone and finished mining products such as cement has increased rapidly. Against this background, the efficiency and output of traditional mining operations are far from meeting the requirements. Faced with dangerous and complex scene environments such as easy collapse of mines, high temperatures in the open air, strong winds and heavy rains, the work risks of mine car drivers have greatly increased. At the same time, drivers operate mine cars weighing nearly 100 tons or hundreds of tons to frequently and intensively go down the mountain, which is very easy to be distracted and induce accidents. These are challenges to the safe and efficient production of mines. In order to solve the various problems existing in mining operations, unmanned mine cars came into being. The automated transportation capacity not only shortens the handling time of materials, but also effectively reduces energy consumption in the entire mining process through refined energy management. This highly efficient transportation method directly promotes the overall efficiency of mining operations and opens up a new path for the modernization and sustainable development of the mining industry. Among them, anti-skid control has become a key issue restricting the practical application of unmanned mine cars. When faced with complex road conditions such as steep slopes, slippery roads, and soft roads, how to effectively prevent the vehicle from locking and sliding during the downhill process, maintain stability, and reduce the risk of loss of control is the core challenge facing unmanned mining vehicles. Summary of the invention

[0003] The purpose of the present invention is to overcome the shortcomings of the prior art. To achieve the above purpose, an ABS control method for an unmanned mining dump truck based on active anti-disturbance control is adopted to solve the problems raised in the above background technology.

[0004] An ABS control method for an unmanned mining dump truck based on active disturbance rejection control comprises the following steps:

[0005] Step S1, setting a wheel speed sensor to monitor and record wheel speed data in real time;

[0006] Step S2: using the vehicle inertial navigation system to obtain and record the speed information of the driverless vehicle in real time;

[0007] Step S3, by defining the slip ratio, converting the slip ratio control target into a specific wheel speed control target; designing a linear extended state observer, and using the real-time driving torque and wheel speed data to estimate the wheel speed and total disturbance;

[0008] Step S4, designing a linear state error feedback control, and calculating a control law based on the real-time vehicle speed, wheel speed estimation and total disturbance estimation;

[0009] The calculated control law is used as a driving torque signal and transmitted to the throttle control unit of the unmanned mining vehicle to change the valve opening and perform ABS control on the unmanned mining vehicle during braking.

[0010] As a further solution of the present invention: the gear ring part of the wheel speed sensor in step S1 is arranged at the end of the wheel hub of each wheel, and the probe part is fixed on the frame, and the wheel speeds of the front and rear wheels are accurately calibrated.

[0011] As a further solution of the present invention: the specific steps of the unmanned vehicle in step S2 include:

[0012] Based on the four-wheel drive unmanned mining truck, the vehicle model is simplified to a quarter vehicle model; air resistance and rolling resistance are ignored, and the force on the wheels is analyzed to obtain the vehicle dynamics equation:

[0013]

[0014] Among them, T b is the driving torque, F x is the ground driving force, F z is the normal force of the driving wheel, μ is the ground adhesion coefficient, J is the wheel moment of inertia, and M is 1 / 4 of the vehicle mass.

[0015] As a further solution of the present invention: the specific formula for defining the slip rate λ in step S3 is:

[0016]

[0017] In the formula, V, V ω Represent vehicle speed and wheel linear speed respectively; among them, V ω =rω.

[0018] As a further solution of the present invention: the specific steps of converting the slip ratio control target into a specific wheel speed control target in step S3 include:

[0019] Set the optimal slip rate to λ th , and the corresponding maximum road adhesion coefficient μ max ;

[0020] Set the optimal slip rate to λ th Then, the optimal angular velocity ω is obtained by defining the slip rate th , the control of slip rate is converted into the control of wheel speed, the formula is:

[0021]

[0022] Among them, the angular acceleration can be obtained from the above:

[0023]

[0024] remember Will Considered as a disturbance term, recorded as f1(ω,w(t)), we get:

[0025]

[0026] If we estimate b = b0, then it becomes:

[0027]

[0028] Where, f(ω,w(t)) is the total disturbance;

[0029] The linear extended state observer LESO is designed as follows:

[0030]

[0031] in, are the observed values ​​of ω and f respectively; [uy] T are the joint inputs, respectively T b With ω.

[0032] As a further solution of the present invention: the specific steps of designing the linear state error feedback control in step S4 include:

[0033] The linear state error feedback controller LSEF is designed as follows:

[0034]

[0035] but:

[0036]

[0037] The bandwidth method is used to adjust the parameters in ADRC control, ω c is the controller bandwidth, Converge to the target value within the time, take ω c =100;β1=2ω o , β2=ω o 2 ,ω o is the observer bandwidth, usually set to ω c 3 to 5 times of b0; b0 is Estimates.

[0038] Compared with the prior art, the present invention has the following technical effects:

[0039] By adopting the above technical solutions and innovative ABS solutions for mine car skidding, ADRC not only inherits the advantages of PID controllers that are easy to implement and adjust, but also overcomes some inherent limitations of PID controllers through its robustness to model uncertainties and external disturbances. The core of the ADRC method lies in its strong anti-disturbance capability to internal and external disturbances of the system, which makes it almost model-independent and easy to implement in various engineering environments, while maintaining high adaptability to complex dynamic changes.

[0040] Although the methods based on modern control theory have their own advantages in theory, such as the reaching law sliding mode control, which can make the TCS control system have high robustness and accuracy and fast convergence when the road adhesion coefficient and the front and rear axle loads of the mine car change, the actual engineering deployment is not easy. The dominant position of the PID controller is still unique, and the engineering application of the TCS system is still dominated by PID. At the same time, the conventional TCS control method using PID requires manual adjustment of the control parameters according to the specific road conditions and working conditions. Although it can meet the control requirements within a certain range, it is very susceptible to environmental changes, external disturbances and changes in vehicle internal parameters. Faced with this situation, the use of the self-disturbance rejection control method can carry forward the advantages of PID and overcome its shortcomings. It is almost model-independent and easy to implement in engineering. At the same time, it has both robustness and strong anti-disturbance capabilities for internal and external disturbances of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The specific embodiments of the present invention are described in detail below in conjunction with the accompanying drawings:

[0042] Figure 1 A schematic diagram of the steps of the ABS control method of the embodiment disclosed in this application;

[0043] Figure 2 A schematic diagram of force analysis of a vehicle dynamics model according to an embodiment disclosed in the present application;

[0044] Figure 3 This is a system control flow chart of an embodiment disclosed in this application. DETAILED DESCRIPTION

[0045] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0046] Please refer to Figure 1In an embodiment of the present invention, an ABS control method for an unmanned mining dump truck based on active disturbance rejection control comprises the following steps:

[0047] Step S1, setting a wheel speed sensor to monitor and record wheel speed data in real time;

[0048] In this embodiment, a wheel speed sensor is arranged at the wheel hub of the mine car to monitor the wheel speed in real time; specifically, the ring gear part of the wheel speed sensor in step S1 is arranged at the end of the wheel hub of each wheel, and the probe part is fixed on the frame, and the wheel speeds of the front and rear wheels are accurately calibrated.

[0049] Step S2: using the vehicle inertial navigation system to obtain and record the speed information of the driverless vehicle in real time;

[0050] In this embodiment, the specific steps of the unmanned vehicle in step S2 include:

[0051] Based on the four-wheel drive unmanned mining truck, the vehicle model is simplified to a quarter vehicle model; Figure 2 As shown in the figure, it is a schematic diagram of the force analysis of the vehicle dynamics model; ignoring air resistance and rolling resistance, analyzing the force of the wheel, the vehicle dynamics equation is obtained as follows:

[0052]

[0053] Among them, T b is the driving torque, F x is the ground driving force, F z is the normal force of the driving wheel, μ is the ground adhesion coefficient, J is the wheel moment of inertia, and M is 1 / 4 of the vehicle mass.

[0054] Step S3, by defining the slip ratio, converting the slip ratio control target into a specific wheel speed control target; designing a linear extended state observer, and using the real-time driving torque and wheel speed data to estimate the wheel speed and total disturbance;

[0055] In this embodiment, the specific formula for defining the slip rate λ in step S3 is:

[0056]

[0057] In the formula, V, V ω Represent vehicle speed and wheel linear speed respectively; vehicle speed is obtained through vehicle inertial navigation system, wheel linear speed is obtained through wheel speed sensor, V ω =rω.

[0058] In this embodiment, the specific steps of converting the slip ratio control target into a specific wheel speed control target in step S3 include:

[0059] Set the optimal slip rate to λth , and the corresponding maximum road adhesion coefficient μ max ;

[0060] Specifically, the optimal slip rate is set to λ th =0.06, the corresponding maximum road adhesion coefficient μ max =0.2, the sliding adhesion coefficient is 0.135.

[0061] Set the optimal slip rate to λ th Then, the optimal angular velocity ω is obtained by defining the slip rate th , the control of slip rate is converted into the control of wheel speed, the formula is:

[0062]

[0063] Among them, the angular acceleration can be obtained from the above:

[0064]

[0065] remember Will Considered as a disturbance term, recorded as f1(ω,w(t)), we get:

[0066]

[0067] If we estimate b = b0, then it becomes:

[0068]

[0069] Where, f(ω,w(t)) is the total disturbance;

[0070] The linear extended state observer LESO is designed as follows:

[0071]

[0072] in, are the observed values ​​of ω and f respectively; [uy] T are the joint inputs, respectively T b With ω.

[0073] Step S4, designing a linear state error feedback control, and calculating a control law based on the real-time vehicle speed, wheel speed estimation and total disturbance estimation;

[0074] The calculated control law is used as a driving torque signal and transmitted to the throttle control unit of the unmanned mining vehicle to change the valve opening and perform ABS control on the unmanned mining vehicle during braking.

[0075] In this embodiment, the specific steps of designing the linear state error feedback control in step S4 include:

[0076] The linear state error feedback controller LSEF is designed as follows:

[0077]

[0078] but:

[0079]

[0080] The bandwidth method is used to adjust the parameters in ADRC control, ω c is the controller bandwidth, Converge to the target value within the time, take ω c =100;β1=2ω o , β2=ω o 2 ,ω o is the observer bandwidth, usually set to ω c 3 to 5 times of o =5ω c ; b0 is Estimates.

[0081] like Figure 3 As shown, the figure is a system control flow chart;

[0082] Beneficial effects:

[0083] An ABS solution for mine car skidding is designed, specifically by migrating ADRC to the ABS control of mine cars. ADRC not only inherits the advantages of PID controllers that are easy to implement and adjust, but also overcomes some inherent limitations of PID controllers through its robustness to model uncertainties and external disturbances. The core of the ADRC method lies in its strong anti-disturbance ability to internal and external disturbances of the system, which makes it almost model-independent and easy to implement in various engineering environments, while maintaining high adaptability to complex dynamic changes.

[0084] Although the embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents, and all should be included within the scope of protection of the present invention.

Claims

1. An ABS control method for an unmanned mining dump truck based on active disturbance rejection control, characterized in that: The following steps are involved: Step S1, setting a wheel speed sensor to monitor and record wheel speed data in real time; Step S2: using the vehicle inertial navigation system to obtain and record the speed information of the driverless vehicle in real time; Step S3, converting the slip rate control target into a specific wheel speed control target by defining the slip rate; Design a linear extended state observer to estimate the wheel speed and total disturbance using real-time driving torque and wheel speed data; Step S4, designing a linear state error feedback control, and calculating a control law based on the real-time vehicle speed, wheel speed estimation and total disturbance estimation; The calculated control law is used as a driving torque signal and transmitted to the throttle control unit of the unmanned mining vehicle to change the valve opening and perform ABS control on the unmanned mining vehicle during braking.

2. According to claim 1, an ABS control method for an unmanned mining dump truck based on active disturbance rejection control is characterized in that: The gear ring part of the wheel speed sensor in step S1 is arranged at the end of the wheel hub of each wheel, and the probe part is fixed on the frame, and the wheel speeds of the front and rear wheels are accurately calibrated.

3. According to claim 1, the ABS control method for an unmanned mining dump truck based on active disturbance rejection control is characterized in that: The specific steps of the driverless vehicle in step S2 include: Based on the four-wheel drive unmanned mining truck, the vehicle model is simplified to a quarter vehicle model; air resistance and rolling resistance are ignored, and the force on the wheels is analyzed to obtain the vehicle dynamics equation: Among them, T b is the driving torque, F x is the ground driving force, F z is the normal force of the driving wheel, μ is the ground adhesion coefficient, J is the wheel moment of inertia, and M is 1 / 4 of the vehicle mass.

4. According to claim 1, the ABS control method for an unmanned mining dump truck based on active disturbance rejection control is characterized in that: The specific formula for defining the slip rate λ in step S3 is: In the formula, V, V ω Represent vehicle speed and wheel linear speed respectively; among them, V ω =rω.

5. The ABS control method for an unmanned mining dump truck based on active disturbance rejection control according to claim 4 is characterized in that: The specific steps of converting the slip ratio control target into a specific wheel speed control target in step S3 include: Set the optimal slip rate to λ th , and the corresponding maximum road adhesion coefficient μ max ; Set the optimal slip rate to λ th Then, the optimal angular velocity ω is obtained by defining the slip rate th , the control of slip rate is converted into the control of wheel speed, the formula is: Among them, the angular acceleration can be obtained from the above: remember Will Considered as a disturbance term, recorded as f1(ω,w(t)), we get: If we estimate b = b0, then it becomes: Where, f(ω,w(t)) is the total disturbance; The linear extended state observer LESO is designed as follows: in, are the observed values ​​of ω and f respectively; [uy] T are the joint inputs, respectively T b With ω.

6. The ABS control method for an unmanned mining dump truck based on active disturbance rejection control according to claim 1 is characterized in that: The specific steps of designing the linear state error feedback control in step S4 include: The linear state error feedback controller LSEF is designed as follows: but: The bandwidth method is used to adjust the parameters in ADRC control, ω c is the controller bandwidth, Converge to the target value within the time, take ω c =100;β1=2ω o , β2=ω o 2 ,ω o is the observer bandwidth, usually set to ω c 3 to 5 times of b0; b0 is Estimates.

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