Cross-domain integrated fault-tolerant control method suitable for integrated hovercars with various configurations

Abstract

The invention is suitable for the technical field of intelligent chassis control and flight control, and provides a cross-domain integrated fault-tolerant control method suitable for a multi-configuration integrated hovercar, and the method comprises the steps: constructing a hovercar general kinetic equation under a whole vehicle coordinate system, and enabling the state quantity of the hovercar general kinetic equation to be three translation speeds and three rotation speeds of the whole vehicle; the specific control input of the hovercar is virtual vehicle control input, the virtual vehicle control input is driving force in three translation directions and torque in three rotation directions, and the virtual vehicle control input is linearly processed and converted into a form of trimming control quantity plus control variable quantity by adopting Taylor expansion. Virtual vehicle control input is distributed according to the driving state of the hovercar, fault factors are introduced to carry out fault-tolerant control, and finally control quantity distribution of a cross-domain actuator is carried out according to the control variable quantity by adopting a quadratic programming method. According to the invention, when an actuator fault occurs in a certain domain, the same domain or another domain can be dynamically scheduled, so that the redundancy control capability of the hovercar is improved.

Description

Technical Field

[0001] The present application belongs to the field of intelligent chassis control and flight control technology, and in particular relates to a cross-domain integrated fault-tolerant control method applicable to integrated flying cars of various configurations. Background Art

[0002] Integrated flying vehicles (IAVs) combine a ground-based chassis system with an airborne flight control system, offering advantages such as integrated air-ground connectivity, diverse configurations, and flexible maneuverability. These vehicles are typically equipped with chassis-domain actuators for driving, steering, braking, and suspension functions, as well as flight-domain actuators, including multi-rotor, fixed-wing, or propulsor systems, enabling dual-mode ground-air operation. IAVs balance ground and air environments in mission scenarios, enabling diverse applications such as short-distance urban commuting, emergency rescue, and traversing complex terrain. They can also switch configurations based on mission requirements, adapting to multiple operating modes. While breaking through traditional transportation boundaries, IAVs also introduce complex system coupling issues and the need for high-reliability control. Unlike traditional ground vehicles or aircraft, IAVs have dynamic complementarity between their chassis and flight domains. If a partial functional failure in one domain occurs, the other domain can compensate through coordinated control strategies, thereby enhancing the overall system's fault tolerance.

[0003] However, most current control systems are still based on single-domain fault-tolerant design and lack cross-domain fault-tolerant control mechanisms for integrated flying cars, resulting in poor redundant control capabilities for integrated flying cars. Summary of the Invention

[0004] The embodiments of the present application provide a cross-domain integrated fault-tolerant control method applicable to integrated flying vehicles of various configurations. This method can solve the problem that most current control systems are still based on single-domain fault-tolerant designs and lack a cross-domain fault-tolerant control mechanism for integrated flying vehicles, resulting in poor redundant control capabilities of integrated flying vehicles.

[0005] In a first aspect, an embodiment of the present application provides a cross-domain integrated fault-tolerant control method applicable to integrated flying cars of various configurations, including: S1, constructing a general dynamic equation for a multi-configuration integrated flying car in a whole vehicle coordinate system, wherein the state quantities of the general dynamic equation are the three translational speeds and three rotational speeds of the whole flying car, and the specific control input of the flying car is an abstracted virtual whole vehicle control input, wherein the virtual whole vehicle control input is a driving force in three translational directions and a torque in three rotational directions; S2, using Taylor expansion to linearize the virtual whole vehicle control input of S1 and convert it into the form of a balancing control quantity plus a control variation quantity, allocating the virtual whole vehicle control input according to the driving state of the flying car, and introducing a fault factor for fault-tolerant control; S3, using a quadratic programming method to allocate the control quantity of the cross-domain actuator according to the control variation quantity of S2.

[0006] In a possible implementation of the first aspect, step S1 specifically includes:

[0007] Assume that the flying car body is rigid, define m as the mass of the vehicle, E as the 3x3 unit matrix, and I as the 3x3 inertia matrix. is the vehicle mass matrix, g is the acceleration of gravity, T is the transformation matrix from the world coordinate system to the vehicle body coordinate system, p is the angular velocity of the vehicle around the x-axis of the body coordinate system, q is the angular velocity of the vehicle around the y-axis of the body coordinate system, r is the angular velocity of the vehicle around the z-axis of the body coordinate system, v x is the speed of the vehicle on the x-axis of the body coordinate system, v y is the speed of the vehicle on the y-axis of the body coordinate system, v z is the speed of the vehicle on the z-axis of the body coordinate system, F x is the virtual control force of the vehicle on the x-axis of the body coordinate system, F y is the virtual control force of the vehicle on the y-axis of the body coordinate system, F z is the virtual control force of the vehicle on the z-axis of the body coordinate system, M x is the virtual control torque of the vehicle around the x-axis of the body coordinate system, M y is the virtual control torque of the vehicle around the y-axis of the body coordinate system, M z is the virtual control torque of the vehicle around the z-axis of the body coordinate system, v = [v x v y v z ] T is the speed of the vehicle in three directions, ω=[pqr] T is the angular velocity of the vehicle in the three rotation directions, X = [vω] T is the system state, F=[F x F y F z ] Tis the virtual control force of the vehicle in three directions, M F =[M x M y M z ] is the virtual control torque of the whole vehicle in the three rotation directions, u is the specific control input of each actuator in the flight domain and chassis domain of the flying car, P = f (X, u) = [F; M] is the virtual vehicle control input;

[0008] Establish the general dynamics equation:

[0009]

[0010] Among them, E z

[001] T ;

[0011] Abstract the general dynamics equation:

[0012]

[0013] Among them, f(X) is the free response part of the system and is independent of the input quantity P.

[0014] Optionally, in another possible implementation of the first aspect, step S2 specifically includes:

[0015] Taylor expansion is used to expand the virtual vehicle control input P = f (X, u) = [F; M] of S1 in the trim state. Let the trim state be X tr , the balancing control quantity is u tr , the virtual control quantity for balancing is P tr , the state increment from the trim state is ΔX=XX tr , the control increment is Δu=uu tr , the virtual control input increment is ΔP=PP tr ;

[0016] When the flying car is in an airborne state, the control weight of the flight domain actuator in the virtual control input is increased to a first preset threshold; when the flying car is in a ground driving state, the control weight of the chassis domain actuator in the virtual control input is increased to a second preset threshold;

[0017] Adjust the control efficiency transfer matrix Θ according to the ground vertical force of the flying car 6×n , n is the number of all actuators, Θ 6×n The value of each element in ranges from 0 to 1;

[0018] Integrate all fault actuator effectiveness coefficients into the fault actuator effectiveness matrix And the virtual vehicle control input P is expanded in the trim state:

[0019]

[0020] Among them, B is the contribution conversion matrix of each actuator control quantity in the flight domain and chassis domain to the virtual vehicle control input, is the contribution conversion matrix after considering the fault;

[0021] Convert the above formula to:

[0022] P=P tr +ΔP

[0023] Among them, P tr =BΘu tr , ΔP=B f ΘΔu.

[0024] Optionally, in another possible implementation of the first aspect, step S3 specifically includes:

[0025] The cost function is set to the virtual control effectiveness increment ΔP achieved by the increment of all actuators in the real system. sys The squared Euclidean distance of the difference between the virtual control input increment ΔP and the control increment Δu and the desired control increment Δu tar The squared Euclidean distance is as follows:

[0026] J=(ΔP sys -ΔP) 2 +(Δu-Δu tar ) 2

[0027] The cost function is converted into a standard quadratic form and directly solved using the osqp toolbox to obtain the control increments Δu of all actuators.

[0028] Beneficial effect: In the technical solution of the present application, a general dynamic equation of a multi-configuration integrated flying car in the whole vehicle coordinate system is first constructed. The state quantities of the general dynamic equation are the three translational speeds and three rotational speeds of the whole flying car. The specific control input of the flying car is the abstracted virtual whole vehicle control input. The virtual whole vehicle control input is the driving force in the three translational directions and the torque in the three rotational directions. Then, Taylor expansion is used to linearize the virtual whole vehicle control input and convert it into the form of balancing control quantity plus control variation. The virtual whole vehicle control input is allocated according to the driving state of the flying car, and a fault factor is introduced for fault-tolerant control. Finally, according to the control variation, a quadratic programming method is used to allocate the control quantity of the cross-domain actuator. The present application can dynamically schedule the same domain or another domain when an actuator failure occurs in a certain domain, thereby improving the redundant control capability of the flying car. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments or descriptions of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0030] Figure 1 This is a flow chart of a cross-domain integrated fault-tolerant control method applicable to integrated flying vehicles of various configurations, provided in one embodiment of the present application. DETAILED DESCRIPTION

[0031] In the following description, specific details such as specific system structures and techniques are provided for purposes of illustration rather than limitation to facilitate a thorough understanding of the embodiments of the present application. However, it will be apparent to those skilled in the art that the present application may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid obscuring the description of the present application with unnecessary detail.

[0032] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or collections thereof.

[0033] It will also be understood that the term "and / or" used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0034] As used in this specification and the appended claims, the term "if" can be interpreted as "when" or "upon" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "upon determination" or "in response to determining" or "upon detection of [described condition or event]" or "in response to detecting [described condition or event]," depending on the context.

[0035] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0036] References to "one embodiment" or "some embodiments" in this specification mean that a particular feature, structure, or characteristic described in conjunction with that embodiment is included in one or more embodiments of the present application. Thus, phrases such as "in one embodiment," "in some embodiments," "in other embodiments," and "in other embodiments" appearing in various places in this specification do not necessarily refer to the same embodiment, but rather mean "one or more but not all embodiments," unless otherwise specifically emphasized. The terms "including," "comprising," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0037] The cross-domain integrated fault-tolerant control method applicable to integrated flying vehicles of various configurations provided in this application is described in detail below with reference to the accompanying drawings.

[0038] Figure 1 A flow chart of a cross-domain integrated fault-tolerant control method applicable to integrated flying vehicles of various configurations provided in an embodiment of the present application is shown.

[0039] like Figure 1 As shown, the cross-domain integrated fault-tolerant control method applicable to integrated flying vehicles of various configurations includes the following steps:

[0040] S1. Construct a general dynamics equation for a multi-configuration integrated flying car in the vehicle coordinate system. The state variables of the general dynamics equation are the three translational velocities and three rotational velocities of the flying car. The specific control input of the flying car is the abstracted virtual vehicle control input, which is the driving force in the three translational directions and the torque in the three rotational directions.

[0041] Furthermore, in the embodiment of the present application, the above step S1 includes:

[0042] Assume that the flying car body is rigid, define m as the mass of the vehicle, E as the 3x3 unit matrix, and I as the 3x3 inertia matrix. is the vehicle mass matrix, g is the acceleration of gravity, T is the transformation matrix from the world coordinate system to the vehicle body coordinate system, p is the angular velocity of the vehicle around the x-axis of the body coordinate system, q is the angular velocity of the vehicle around the y-axis of the body coordinate system, r is the angular velocity of the vehicle around the z-axis of the body coordinate system, v x is the speed of the vehicle on the x-axis of the body coordinate system, v y is the speed of the vehicle on the y-axis of the body coordinate system, v z is the speed of the vehicle on the z-axis of the body coordinate system, F x is the virtual control force of the vehicle on the x-axis of the body coordinate system, F y is the virtual control force of the vehicle on the y-axis of the body coordinate system, F zis the virtual control force of the vehicle on the z-axis of the body coordinate system, M x is the virtual control torque of the vehicle around the x-axis of the body coordinate system, M y is the virtual control torque of the vehicle around the y-axis of the body coordinate system, M z is the virtual control torque of the vehicle around the z-axis of the body coordinate system, v = [v x v y v z ] T is the speed of the vehicle in three directions, ω=[pqr] T is the angular velocity of the vehicle in the three rotation directions, X = [vω] T is the system state, F=[F x F y F z ] T is the virtual control force of the vehicle in three directions, M F =[M x M y M z ] is the virtual control torque of the whole vehicle in the three rotation directions, u is the specific control input of each actuator in the flight domain and chassis domain of the flying car, P = f (X, u) = [F; M] is the virtual vehicle control input;

[0043] Establish the general dynamics equation:

[0044]

[0045] Among them, E z

[001] T ;

[0046] Abstract the general dynamics equation:

[0047]

[0048] Among them, f(X) is the free response part of the system and is independent of the input quantity P.

[0049] It should be noted that for all-in-one flying vehicles of different configurations, the only thing that needs to be changed in the dynamics model is the form of the control input u. Therefore, this model is universal for all-in-one flying vehicles of different configurations.

[0050] S2: Use Taylor expansion to linearize the virtual vehicle control input of S1 and convert it into the form of balancing control quantity plus control variation quantity. Distribute the virtual vehicle control input according to the driving state of the flying car and introduce fault factors for fault-tolerant control.

[0051] Furthermore, in the embodiment of the present application, the above step S2 includes:

[0052] Taylor expansion is used to expand the virtual vehicle control input P = f (X, u) = [F; M] of S1 in the trim state. Let the trim state be X tr , the balancing control quantity is u tr , the virtual control quantity for balancing is P tr , the state increment from the trim state is ΔX=XX tr , the control increment is Δu=uu tr , the virtual control input increment is ΔP=PP tr ;

[0053] When the flying car is in an airborne state, the control weight of the flight domain actuator in the virtual control input is increased to a first preset threshold; when the flying car is in a ground driving state, the control weight of the chassis domain actuator in the virtual control input is increased to a second preset threshold;

[0054] Adjust the control efficiency transfer matrix Θ according to the ground vertical force of the flying car 6×n , n is the number of all actuators, Θ 6×n The value of each element in ranges from 0 to 1;

[0055] The effectiveness coefficients of all faulty actuators are integrated into the faulty actuator effectiveness matrix θ, and the virtual vehicle control input P is expanded in the trim state:

[0056]

[0057] Among them, B is the contribution conversion matrix of each actuator control quantity in the flight domain and chassis domain to the virtual vehicle control input, is the contribution conversion matrix after considering the fault;

[0058] Convert the above formula to:

[0059] P=P tr +ΔP

[0060] Among them, P tr =BΘu tr , ΔP=B f ΘΔu.

[0061] It should be noted that the specific performance transfer strategy is set according to the configuration of the flying car.

[0062] Since the number of actuators n is generally greater than the number of system states, making the system an overdriven system, there is no set of solutions that can satisfy ΔP = B. f Therefore, an optimization method is needed to allocate the control efficiency. In this application, the quadratic programming method is used for optimization.

[0063] S3. Based on the control variation of S2, the quadratic programming method is used to distribute the control variation across the domain actuators.

[0064] Furthermore, in the embodiment of the present application, the above step S3 includes:

[0065] The cost function is set to the virtual control effectiveness increment ΔP achieved by the increment of all actuators in the real system. sys The squared Euclidean distance of the difference between the virtual control input increment ΔP and the control increment Δu and the desired control increment Δu tar The squared Euclidean distance is as follows:

[0066] J=(ΔP sys -ΔP) 2 +(Δu-Δu tar ) 2

[0067] The cost function is converted into a standard quadratic form and directly solved using the osqp toolbox to obtain the control increments Δu of all actuators.

[0068] It should be noted that through this cost function, the control increment is made as close as possible to the expected control increment while achieving the required virtual control efficiency increment. The expected control increment is set by the designer. If there is no demand, its n elements can be directly set to 0.

[0069] The present application provides a cross-domain integrated fault-tolerant control method applicable to integrated flying vehicles of various configurations. The method first constructs a general dynamics equation for integrated flying vehicles of various configurations in the vehicle coordinate system. The state variables of the general dynamics equation are the three translational velocities and three rotational velocities of the flying vehicle. The specific control input of the flying vehicle is the abstracted virtual vehicle control input, which is the driving force in the three translational directions and the torque in the three rotational directions. The virtual vehicle control input is then linearized using Taylor expansion and converted into the form of a trim control variable plus a control variation. The virtual vehicle control input is allocated according to the driving state of the flying vehicle, a fault factor is introduced for fault-tolerant control, and finally, a quadratic programming method is used to allocate control variables across domains based on the control variation. The present application can dynamically schedule the same domain or another domain when an actuator failure occurs in a certain domain, thereby improving the redundant control capability of the flying vehicle.

[0070] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0071] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. A cross-domain integrated fault-tolerant control method applicable to integrated flying vehicles of various configurations, characterized in that: include: S1. Construct a general dynamics equation for a multi-configuration integrated flying car in a vehicle coordinate system. The state variables of the general dynamics equation are the three translational velocities and three rotational velocities of the flying car. The specific control input of the flying car is the abstracted virtual vehicle control input, which is the driving force in the three translational directions and the torque in the three rotational directions. S2: Use Taylor expansion to linearize the virtual vehicle control input of S1 and convert it into the form of balancing control quantity plus control variation quantity. Distribute the virtual vehicle control input according to the driving state of the flying car and introduce fault factors for fault-tolerant control. S3. Based on the control variation of S2, the quadratic programming method is used to distribute the control variation across the domain actuators.

2. The cross-domain integrated fault-tolerant control method applicable to integrated flying vehicles of various configurations according to claim 1, characterized in that: The step S1 specifically includes: Assume that the flying car body is rigid, define m as the mass of the vehicle, E as the 3x3 unit matrix, and I as the 3x3 inertia matrix. is the vehicle mass matrix, g is the acceleration of gravity, T is the transformation matrix from the world coordinate system to the vehicle body coordinate system, p is the angular velocity of the vehicle around the x-axis of the body coordinate system, q is the angular velocity of the vehicle around the y-axis of the body coordinate system, r is the angular velocity of the vehicle around the z-axis of the body coordinate system, v x is the speed of the vehicle on the x-axis of the body coordinate system, v y is the speed of the vehicle on the y-axis of the body coordinate system, v z is the speed of the vehicle on the z-axis of the body coordinate system, F x is the virtual control force of the vehicle on the x-axis of the body coordinate system, F y is the virtual control force of the vehicle on the y-axis of the body coordinate system, F z is the virtual control force of the vehicle on the z-axis of the body coordinate system, M x is the virtual control torque of the vehicle around the x-axis of the body coordinate system, M y is the virtual control torque of the vehicle around the y-axis of the body coordinate system, M z is the virtual control torque of the vehicle around the z-axis of the body coordinate system, v = [v x v y v z ] T is the speed of the vehicle in three directions, ω=[pqr] T is the angular velocity of the vehicle in the three rotation directions, X = [vω] T is the system state, F=[F x F y F z ] T is the virtual control force of the vehicle in three directions, M F =[M x M y M z ] is the virtual control torque of the whole vehicle in the three rotation directions, u is the specific control input of each actuator in the flight domain and chassis domain of the flying car, P = f (X, u) = [F; M] is the virtual vehicle control input; The general kinetic equation is established: Among them, E z [001] T ; The general dynamics equation is abstracted as follows: Among them, f(X) is the free response part of the system and is independent of the input quantity P.

3. The cross-domain integrated fault-tolerant control method applicable to integrated flying vehicles of various configurations according to claim 2, characterized in that: The step S2 specifically includes: Taylor expansion is used to expand the virtual vehicle control input P = f (X, u) = [F; M] of S1 in the trim state. Let the trim state be X tr , the balancing control quantity is u tr , the virtual control quantity for balancing is P tr , the state increment from the trim state is ΔX=XX tr , the control increment is Δu=uu tr , the virtual control input increment is ΔP=PP tr ; When the flying car is in an airborne state, the control weight of the flight domain actuator in the virtual control input is increased to a first preset threshold; when the flying car is in a ground driving state, the control weight of the chassis domain actuator in the virtual control input is increased to a second preset threshold; Adjust the control efficiency transfer matrix Θ according to the ground vertical force of the flying car 6×n , n is the number of all actuators, Θ 6×n The value of each element in ranges from 0 to 1; The effectiveness coefficients of all faulty actuators are integrated into the faulty actuator effectiveness matrix θ, and the virtual vehicle control input P is expanded in the trim state: Among them, B is the contribution conversion matrix of each actuator control quantity in the flight domain and chassis domain to the virtual vehicle control input, B f =B·θ is the contribution conversion matrix after considering the fault; Convert the above formula to: P=P tr +ΔP Among them, P tr =BΘu tr ,ΔP=B f Good morning.

4. The cross-domain integrated fault-tolerant control method applicable to integrated flying vehicles of various configurations according to claim 3, characterized in that: The step S3 specifically includes: The cost function is set to the virtual control effectiveness increment ΔP achieved by the increment of all actuators in the real system. sys The squared Euclidean distance of the difference between the virtual control input increment ΔP and the control increment Δu and the desired control increment Δu tar The squared Euclidean distance is as follows: J=(ΔP sys -ΔP) 2 +(Δu-Δu tar ) 2 The cost function is converted into a standard quadratic form and directly solved using the osqp toolbox to obtain the control increments Δu of all actuators.

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