An event-triggered ∞ Robust steer-by-wire stability control method

Abstract

The present invention discloses an event triggering ‑ H ∞ A robust steer-by-wire stability control method includes: establishing a discrete switching system model of a steer-by-wire system; estimating time-varying parameter terms in the discrete switching system model; establishing a non-delay closed-loop augmented system model; constructing a state feedback event trigger mechanism for the steer-by-wire system, and when the state error of the steer-by-wire system exceeds a given threshold, feeding back the current state of the steer-by-wire system via CAN communication; establishing a two-degree-of-freedom reference model of the vehicle, and expressing it as a discrete switching linear system model with norm uncertainty and external disturbance influence; using the feedback signal of the event trigger mechanism and the output signal of the two-degree-of-freedom reference model of the vehicle as H ∞ The control method of the present invention can reduce the occupancy rate of communication resources and improve the steering stability under high load rate of CAN bus.

Description

Technical Field

[0001] The present invention belongs to the technical field of vehicle steering systems, and in particular relates to an event-triggered H ∞ Robust steer-by-wire stability control method. Background Art

[0002] Existing steering stability control methods generally use PID control, sliding film control, and fuzzy control. However, steer-by-wire has more degrees of freedom than traditional steering. It is difficult to solve the steering instability problem caused by model parameter uncertainty and external disturbances by relying solely on the above controllers. ∞ Robust control minimizes the worst-case gain and provides reliable responses to parameter changes and disturbances, thereby improving the overall safety of the vehicle and the driving experience.

[0003] However, the input and output signals of the steering stability controller of the steer-by-wire system need to be transmitted through the CAN communication network, and the communication resources are objectively limited, and there are problems such as communication delay and packet loss, which in turn cause the steer-by-wire vehicle system to become unstable in actual engineering applications. Chinese invention patent application No. CN202410917139.6 discloses an intelligent steering stability control method, which sets three different stability control modes based on the influence of the driver, vehicle and road, but this method does not consider the impact of limited CAN communication resources on steering stability. Chinese invention patent application No. CN202010765949.6 discloses a stability control method for a steer-by-wire system, which uses sliding mode control to complete the stability control of the steer-by-wire system, but this method will cause vibration problems. Summary of the Invention

[0004] In view of the above-mentioned deficiencies in the prior art, the present invention aims to provide an event-triggered H ∞ A robust steer-by-wire stability control method is proposed to address the problem of control instability caused by disturbances such as system parameter uncertainty and communication delay in the prior art. The control method of the present invention can reduce the occupancy rate of communication resources and improve the steering stability under high CAN bus load conditions.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is as follows:

[0006] An event trigger-H of the present invention ∞ The robust steer-by-wire stability control method has the following steps:

[0007] 1) Establish a linear continuous system model of the wire-controlled steering system with a sampling interval T k Discretize it to get the discrete switching system model of the steer-by-wire system;

[0008] 2) Using convex polyhedron approximation to estimate time-varying parameters in discrete switching system models;

[0009] 3) Convert the CAN communication time delay into the switching parameters of the discrete switching system model and establish a non-delay closed-loop augmented system model;

[0010] 4) Build a state feedback event trigger mechanism for the steer-by-wire system. When the steer-by-wire system state error exceeds a given threshold, the current steer-by-wire system state is fed back via CAN communication.

[0011] 5) Establish a two-degree-of-freedom reference model of the vehicle, which is represented as a discrete switching linear system model with norm uncertainty and external disturbance effects;

[0012] 6) Solve the controller gain matrix based on the non-delay closed-loop augmented system model established in step 3), and use the feedback signal of the event trigger mechanism and the output signal of the vehicle two-degree-of-freedom reference model as H ∞ The input of the robust controller is used to obtain the closed-loop input signal of the wire-controlled steering system.

[0013] Furthermore, the step 1) specifically includes:

[0014] The linear continuous system model of the steer-by-wire system is established as follows:

[0015]

[0016] Where x(t) is the state of the steer-by-wire system at time t, is the state change rate of the steer-by-wire system at time t, A is the state matrix of the steer-by-wire system, B is the control matrix of the steer-by-wire system, and u(t) is the input signal of the steer-by-wire system at time t;

[0017] With sampling interval T k Discretizing the above model, we get the discrete model of the steer-by-wire system as follows:

[0018] x(t k+1 )=A(T k )x(t k )+B(T k )u(t k )

[0019] Where, x(t k+1 ) is t k+1 The sampling state of the steer-by-wire system at the triggering moment, the discrete model state matrix Discrete model control matrix e is a natural constant, s is an integral variable, T k is the kth sampling interval, satisfying T k =tk+1 -t k , T0 is a fixed sampling interval, satisfying T k =n k T0+θ k , n k represents the steer-by-wire discrete system t k How many fixed sampling intervals T0, θ have passed between the trigger moment and the last trigger moment? k t k The residual value of the sampling interval corresponding to the trigger moment, u(t k ) is t k Input signal of the steer-by-wire discrete system model at the triggering moment;

[0020] The discrete model inputs for the steer-by-wire system are as follows:

[0021] u(t k )=Kx(t k )

[0022] Where K is the control matrix of the discrete model input of the steer-by-wire system, x(t k ) is t k The sampling state of the steer-by-wire system at the triggering moment;

[0023] The discrete model of the steer-by-wire system is considered as a discrete switching system model, which is expressed as follows:

[0024]

[0025] Where, is the discrete switching system model state matrix,

[0026] σ(t k ) is t k The switching signal at the trigger moment, A0 is defined as t k How many fixed sampling intervals T0 have passed between the subsystem corresponding to the switching signal at the trigger moment and the last trigger moment?

[0027] Furthermore, the step 2) specifically includes:

[0028] The convex polyhedron approximation method is used to estimate the time-varying terms to be estimated contained in the discrete switching system model established in step 1) above, as follows:

[0029]

[0030] Where, e is a natural constant, θ k t kThe residual value of the sampling interval corresponding to the trigger moment, δ(θ k ) is a convex combination of n polyhedron vertices, δ(θ k )∈co{Θ1,Θ2,…,Θ η},Θ κ is a vertex of a convex polyhedron, κ=1,2,…,η;

[0031] The convex polyhedron discrete switching system model is established as follows:

[0032]

[0033] Where, is the state matrix of the convex polyhedron discrete switching system model, and

[0034]

[0035] Where, For a convex polyhedron, the vertices are Θ κ The state matrix of the convex polyhedron discrete switching system model, σ(t k ) is t k The switching signal at the trigger moment, A0 is defined as t k How many fixed sampling intervals T0 have the subsystem corresponding to the switching signal at the trigger moment passed? Θ κ is a vertex of the convex polyhedron. As the observation data is obtained, the convex polyhedron is continuously adjusted to obtain the estimated value of the time-varying parameter.

[0036] Furthermore, the step 3) specifically includes:

[0037] The CAN network has transmission delay. The discrete switching system established in step 1) is regarded as a system with input lag, as follows:

[0038]

[0039] Where u i The input lag is θ i The discrete switching system model input is is the time-delay state of the discrete switching system model, K is the control matrix of the discrete switching system model input, θ i is the input lag time;

[0040] Get the load rate on the CAN bus network The input delay time θ i Designed for k The switching signal σ(t k), when the CAN bus load rate is greater than 30%, there is a delay; when the CAN bus load rate is less than 30%, there is no delay, as shown below:

[0041]

[0042] Where, is the average delay time of the CAN bus, is the CAN bus load rate; T sendcycle The cycle time for sending CAN messages, is the upper bound of the switching signal;

[0043] Establish the switching signal as θ i The augmented state vector z i and feedback control law u i for:

[0044]

[0045] Where, the switching signal is θ i The augmented state η i =x(t i ), Expressed as:

[0046]

[0047] In the formula, K is in the first (θ i +1) th Column, θ i is a switching signal and satisfies θ i 、 are θ i The lower and upper bounds of

[0048] The non-delay closed-loop augmented system model composed of the discrete switching system model and the feedback control law of the steer-by-wire system is expressed as:

[0049]

[0050] Where, ρ i is an uncertain parameter, is the switching signal θ i The control matrix of the corresponding augmented system model; is the state matrix of the augmented system model, is the control matrix of the augmented system model, z i is the switching signal θ i The corresponding augmented state vector, z i+1 is the switching signal θ i+1 The corresponding augmented state vector;

[0051]

[0052] Where I is the unit matrix, A(ρ i ) is the state matrix of the discrete switching system model with uncertain parameters, B(ρ i ) is the control matrix of the discrete switching system model with uncertain parameters.

[0053] Furthermore, the step 4) specifically includes:

[0054] Construct a state feedback event trigger mechanism. When the steer-by-wire system samples the state x(t k ) and the current system actual state x(t) exceeds the trigger threshold, the current system actual state x(t) is sent through the CAN bus, and the next trigger time is obtained as follows:

[0055]

[0056] Where, is the error between the sampling state of the steer-by-wire system and the actual state of the current system, α i is the trigger threshold when the switching signal σ(t)=i, α i ≥0;Ω i is a symmetric positive definite matrix when the switching signal σ(t) = i, i∈ N .

[0057] Furthermore, the step 5) specifically includes:

[0058] The state space equation of the established vehicle two-degree-of-freedom reference model is expressed as:

[0059]

[0060] Where x2(t) is the state of the two-degree-of-freedom reference model, is the state change rate of the two-degree-of-freedom reference model, u2(t) is the two-degree-of-freedom reference model input, A2 is the two-degree-of-freedom reference model state matrix, B2 is the two-degree-of-freedom reference model control matrix, C2 is the two-degree-of-freedom reference model output matrix, D2 is the two-degree-of-freedom reference model direct transfer matrix, and y2(t) is the measurement output of the two-degree-of-freedom reference model;

[0061] C2=[0-1], D2=0, where k f 、k r are the lateral stiffness of the front and rear wheels respectively, a and b are the distances from the front and rear axles to the center of mass respectively, m is the mass of the vehicle, v x is the longitudinal speed, I zis the moment of inertia of the vehicle around the z-axis;

[0062] The two-degree-of-freedom reference model is expressed as a discrete switched linear system model with norm uncertainty and external disturbance effects as follows:

[0063]

[0064] z2(t)=C σ(t) x2(t)+D σ(t) u2(t)

[0065] Where x2(t) is the state of the two-degree-of-freedom reference model, is the state change rate of the two-degree-of-freedom system model; u2(t) is the input of the two-degree-of-freedom reference model; the switching signal is expressed as σ(t):[0,∞)→ N ={1,2,…,N}; ω(t) is an external disturbance that satisfies the condition ||ω(t)||≤W||x(t)||, where W is a non-negative parameter; z2(t) is the controlled output of the two-degree-of-freedom reference model, which is also the desired state of the steer-by-wire system; A σ(t) ,B σ(t) ,B 1σ(t) ,C σ(t) ,D σ(t) is a constant matrix of appropriate dimension; ΔA σ(t) and ΔB σ(t) is the system uncertainty matrix.

[0066] Furthermore, the step 6) specifically includes:

[0067] For any i,j∈N, given a positive constant α i ,λ4′ i ,λ5′ i ,λ6′ i ,μ,θ and N0, where μ>1, N0 is a natural number, if there is a positive constant λ k ' i ,k∈{1,2,3}, so that the symmetric positive definite matrix X i ,X j ,Ω i ′ and matrix Y i satisfy:

[0068]

[0069] Where,

[0070]

[0071] Where * is the matrix block obtained by matrix symmetry, diag{…} is the diagonal matrix, I is the identity matrix, and A i 、Bi 、B 1i 、C i 、D i 、E i 、Y i 、F 1i 、F 2i is a known real constant matrix of appropriate dimension;

[0072] Based on the non-delay closed-loop augmented system model, the corresponding H ∞ The robust controller gain matrix is ​​as follows:

[0073]

[0074] Where K i H ∞ Robust controller gain matrix, X i is a symmetric positive definite matrix, Y i is a known real constant matrix of appropriate dimension;

[0075] The feedback signal of the event trigger mechanism and the output signal of the vehicle two-degree-of-freedom reference model are used as H ∞ The input of the robust controller is the closed-loop input signal of the steer-by-wire system:

[0076] u(t k )=K σ(t) x(t k ),t∈[t k ,t k+1 )

[0077] Where K σ(t) is the control matrix of the steer-by-wire system, t k is the kth triggering moment, x(t k ) is t k The sampling state of the steer-by-wire system at the triggering moment, u(t k ) is t k Closed-loop input signal to the steer-by-wire system at the triggering moment.

[0078] Beneficial effects of the present invention:

[0079] The proposed method can improve the stability of steer-by-wire systems under conditions where CAN bus communication is limited. By employing an event-triggered mechanism, signals are transmitted to the communication network only when trigger conditions are met, reducing the bandwidth utilization of the communication network. Furthermore, by converting CAN communication delays into switching parameters through augmented control sequences, the overall steering system's anti-interference performance is enhanced. BRIEF DESCRIPTION OF THE DRAWINGS

[0080] Figure 1 1 is a flow chart of the principle of the method of the present invention. DETAILED DESCRIPTION

[0081] In order to facilitate understanding by those skilled in the art, the present invention will be further described below with reference to embodiments and drawings. The contents mentioned in the embodiments are not intended to limit the present invention.

[0082] Reference Figure 1 As shown, an event trigger-H ∞ The robust steer-by-wire stability control method has the following steps:

[0083] 1) Establish a linear continuous system model of the wire-controlled steering system with a sampling interval T k The discrete switching system model of the steer-by-wire system is obtained by discretizing it; specifically, it includes:

[0084] The linear continuous system model of the steer-by-wire system is established as follows:

[0085]

[0086] Where x(t) is the state of the steer-by-wire system at time t, is the state change rate of the steer-by-wire system at time t, A is the state matrix of the steer-by-wire system, B is the control matrix of the steer-by-wire system, and u(t) is the input signal of the steer-by-wire system at time t;

[0087] With sampling interval T k Discretizing the above model, we get the discrete model of the steer-by-wire system as follows:

[0088] x(t k+1 )=A(T k )x(t k )+B(T k )u(t k )

[0089] Where, x(t k+1 ) is t k+1 The sampling state of the steer-by-wire system at the triggering moment, the discrete model state matrix Discrete model control matrix e is a natural constant, s is an integral variable, T k is the kth sampling interval, satisfying T k =t k+1 -t k , T0 is a fixed sampling interval, satisfying T k =n k T0+θ k , n k represents the steer-by-wire discrete system t kHow many fixed sampling intervals T0, θ have passed between the trigger moment and the last trigger moment? k t k The residual value of the sampling interval corresponding to the trigger moment, u(t k ) is t k Input signal of the steer-by-wire discrete system model at the triggering moment;

[0090] The discrete model inputs for the steer-by-wire system are as follows:

[0091] u(t k )=Kx(t k )

[0092] Where K is the control matrix of the discrete model input of the steer-by-wire system, x(t k ) is t k The sampling state of the steer-by-wire system at the triggering moment;

[0093] The discrete model of the steer-by-wire system is considered as a discrete switching system model, which is expressed as follows:

[0094]

[0095] Where, is the discrete switching system model state matrix,

[0096] σ(t k ) is t k The switching signal at the trigger moment, A0 is defined as t k How many fixed sampling intervals T0 have passed between the subsystem corresponding to the switching signal at the trigger moment and the last trigger moment?

[0097] 2) Using convex polyhedron approximation to estimate time-varying parameters in discrete switching system models; specifically:

[0098] The convex polyhedron approximation method is used to estimate the time-varying terms to be estimated contained in the discrete switching system model established in step 1) above, as follows:

[0099]

[0100] Where, e is a natural constant, θ k t k The residual value of the sampling interval corresponding to the trigger moment, δ(θ k ) is a convex combination of n polyhedron vertices, δ(θ k )∈co{Θ1,Θ2,…,Θ η},Θ κis a vertex of a convex polyhedron, κ=1,2,…,η;

[0101] The convex polyhedron discrete switching system model is established as follows:

[0102]

[0103] Where, is the state matrix of the convex polyhedron discrete switching system model, and

[0104]

[0105] Where, For a convex polyhedron, the vertices are Θ κ The state matrix of the convex polyhedron discrete switching system model, σ(t k ) is t k The switching signal at the trigger moment, A0 is defined as t k How many fixed sampling intervals T0 have the subsystem corresponding to the switching signal at the trigger moment passed? Θ κ is a vertex of the convex polyhedron. As the observation data is obtained, the convex polyhedron is continuously adjusted to obtain the estimated value of the time-varying parameter.

[0106] 3) Converting the CAN communication time delay into the switching parameters of the discrete switching system model and establishing a non-delay closed-loop augmented system model; specifically,

[0107] The CAN network has transmission delay. The discrete switching system established in step 1) is regarded as a system with input lag, as follows:

[0108]

[0109] Where u i The input lag is θ i The discrete switching system model input is is the time-delay state of the discrete switching system model, K is the control matrix of the discrete switching system model input, θ i is the input lag time;

[0110] Get the load rate on the CAN bus network The input delay time θ i Designed for k The switching signal σ(t k ), when the CAN bus load rate is greater than 30%, there is a delay; when the CAN bus load rate is less than 30%, there is no delay, as shown below:

[0111]

[0112] Where, is the average delay time of the CAN bus, is the CAN bus load rate; T sendcycle The cycle time for sending CAN messages, is the upper bound of the switching signal;

[0113] Establish the switching signal as θ i The augmented state vector z i and feedback control law u i for:

[0114]

[0115] Where, the switching signal is θ i The augmented state η i =x(t i ), Expressed as:

[0116]

[0117] In the formula, K is in the first (θ i +1) th Column, θ i is a switching signal and satisfies θ i 、 are θ i The lower and upper bounds of

[0118] The non-delay closed-loop augmented system model composed of the discrete switching system model and the feedback control law of the steer-by-wire system is expressed as:

[0119]

[0120] Where, ρ i is an uncertain parameter, is the switching signal θ i The control matrix of the corresponding augmented system model; is the state matrix of the augmented system model, is the control matrix of the augmented system model, z i is the switching signal θ i The corresponding augmented state vector, z i+1 is the switching signal θ i+1 The corresponding augmented state vector;

[0121]

[0122] Where I is the unit matrix, A(ρ i) is the state matrix of the discrete switching system model with uncertain parameters, B(ρ i ) is the control matrix of the discrete switching system model with uncertain parameters.

[0123] 4) A state feedback event trigger mechanism is built for the steer-by-wire system. When the steer-by-wire system state error exceeds a given threshold, the current steer-by-wire system state is fed back via CAN communication. This includes:

[0124] Construct a state feedback event trigger mechanism. When the steer-by-wire system samples the state x(t k ) and the current system actual state x(t) exceeds the trigger threshold, the current system actual state x(t) is sent through the CAN bus, and the next trigger time is obtained as follows:

[0125]

[0126] Where, is the error between the sampling state of the steer-by-wire system and the actual state of the current system, α i is the trigger threshold when the switching signal σ(t)=i, α i ≥0;Ω i is a symmetric positive definite matrix when the switching signal σ(t)=i, i∈N.

[0127] 5) Establish a two-degree-of-freedom reference model of the vehicle, representing it as a discrete switching linear system model with norm uncertainty and external disturbance influences; specifically including:

[0128] The state space equation of the established vehicle two-degree-of-freedom reference model is expressed as:

[0129]

[0130] Where x2(t) is the state of the two-degree-of-freedom reference model, is the state change rate of the two-degree-of-freedom reference model, u2(t) is the two-degree-of-freedom reference model input, A2 is the two-degree-of-freedom reference model state matrix, B2 is the two-degree-of-freedom reference model control matrix, C2 is the two-degree-of-freedom reference model output matrix, D2 is the two-degree-of-freedom reference model direct transfer matrix, and y2(t) is the measurement output of the two-degree-of-freedom reference model;

[0131] C2=[0-1],D2=0

[0132] Where k f 、k r are the lateral stiffness of the front and rear wheels respectively, a and b are the distances from the front and rear axles to the center of mass respectively, m is the mass of the vehicle, v x is the longitudinal speed, Iz is the moment of inertia of the vehicle around the z-axis;

[0133] The two-degree-of-freedom reference model is expressed as a discrete switched linear system model with norm uncertainty and external disturbance effects as follows:

[0134]

[0135] z2(t)=C σ(t) x2(t)+D σ(t) u2(t)

[0136] Where x2(t) is the state of the two-degree-of-freedom reference model, is the state change rate of the two-degree-of-freedom system model; u2(t) is the input of the two-degree-of-freedom reference model; the switching signal is expressed as σ(t):[0,∞)→ N ={1,2,…,N}; ω(t) is an external disturbance that satisfies the condition ||ω(t)||≤W||x(t)||, where W is a non-negative parameter; z2(t) is the controlled output of the two-degree-of-freedom reference model, which is also the desired state of the steer-by-wire system; A σ(t) ,B σ(t) ,B 1σ(t) ,C σ(t) ,D σ(t) is a constant matrix of appropriate dimension; ΔA σ(t) and ΔB σ(t) is the system uncertainty matrix.

[0137] 6) Solve the controller gain matrix based on the non-delay closed-loop augmented system model established in step 3), and use the feedback signal of the event trigger mechanism and the output signal of the vehicle two-degree-of-freedom reference model as H ∞ The robust controller is fed with the closed-loop input signal of the steer-by-wire system. Specifically, the following are involved:

[0138] For any i,j∈ N , given a positive constant α i ,λ′ 4i ,λ′ 5i ,λ′ 6i ,μ,θ and N0, where μ>1, N0 is a natural number, if there exists a positive constant λ′ ki ,k∈{1,2,3}, so that the symmetric positive definite matrix X i ,X j ,Ω′ i and matrix Y i satisfy:

[0139]

[0140] Where,

[0141]

[0142] Where * is the matrix block obtained by matrix symmetry, diag{…} is the diagonal matrix, I is the identity matrix, and A i 、B i 、B 1i 、C i 、D i 、E i 、Y i 、F 1i 、F 2i is a known real constant matrix of appropriate dimension;

[0143] Based on the non-delay closed-loop augmented system model, the corresponding H ∞ The robust controller gain matrix is ​​as follows:

[0144]

[0145] Where K i H ∞ Robust controller gain matrix, X i is a symmetric positive definite matrix, Y i is a known real constant matrix of appropriate dimension;

[0146] The feedback signal of the event trigger mechanism and the output signal of the vehicle two-degree-of-freedom reference model are used as H ∞ The input of the robust controller is the closed-loop input signal of the steer-by-wire system:

[0147] u(t k )=K σ(t) x(t k ),t∈[t k ,t k+1 )

[0148] Where K σ(t) is the control matrix of the steer-by-wire system, t k is the kth triggering moment, x(t k ) is t k The sampling state of the steer-by-wire system at the triggering moment, u(t k ) is t k Closed-loop input signal to the steer-by-wire system at the triggering moment.

[0149] The present invention has many specific application paths. The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements can be made without departing from the principles of the present invention. These improvements should also be considered as the scope of protection of the present invention.

Claims

1. An event trigger-H ∞ A robust steer-by-wire stability control method is characterized by: Here are the steps: 1) Establish a linear continuous system model of the wire-controlled steering system with a sampling interval T k Discretize it to get the discrete switching system model of the steer-by-wire system; 2) Estimation of time-varying parameters in discrete switching system models; 3) Convert the CAN communication time delay into the switching parameters of the discrete switching system model and establish a non-delay closed-loop augmented system model; Get the load rate on the CAN bus network The input delay time θ i Designed for t k The switching signal σ(t k ), when the CAN bus load rate is greater than 30%, there is a delay; when the CAN bus load rate is less than 30%, there is no delay, as shown below: Where, is the average delay time of the CAN bus, is the CAN bus load rate; T sendcycle The cycle time for sending CAN messages, is the upper bound of the switching signal; Establish the switching signal as θ i The augmented state vector z i and feedback control law u i for: Where, the switching signal is θ i The augmented state η i =x(t i ), Expressed as: In the formula, K is in the first (θ i +1) th Column, θ i is a switching signal and satisfies θ i 、 are θ i The lower and upper bounds of The non-delay closed-loop augmented system model composed of the discrete switching system model and the feedback control law of the steer-by-wire system is expressed as: Where, ρ i is an uncertain parameter, is the switching signal θ i The control matrix of the corresponding augmented system model; is the state matrix of the augmented system model, is the control matrix of the augmented system model, z i is the switching signal θ i The corresponding augmented state vector, z i+1 is the switching signal θ i+1 The corresponding augmented state vector; 4) Build a state feedback event trigger mechanism for the steer-by-wire system. When the steer-by-wire system state error exceeds a given threshold, the current steer-by-wire system state is fed back via CAN communication. 5) Establish a two-degree-of-freedom reference model of the vehicle, which is represented as a discrete switching linear system model with norm uncertainty and external disturbance effects; 6) Solve H according to the non-delay closed-loop augmented system model established in step 3) ∞ The robust controller gain matrix is ​​the feedback signal of the event trigger mechanism and the output signal of the vehicle two-degree-of-freedom reference model as H ∞ The input of the robust controller is used to obtain the closed-loop input signal of the wire-controlled steering system.

2. The event trigger-H according to claim 1 ∞ A robust steer-by-wire stability control method is characterized by: The step 1) specifically includes: The linear continuous system model of the steer-by-wire system is established as follows: Where x(t) is the state of the steer-by-wire system at time t, is the state change rate of the steer-by-wire system at time t, A is the state matrix of the steer-by-wire system, B is the control matrix of the steer-by-wire system, and u(t) is the input signal of the steer-by-wire system at time t; With sampling interval T k Discretizing the above model, we get the discrete model of the steer-by-wire system as follows: x(t k+1 )=A(T k )x(t k )+B(T k )u(t k ) Where, x(t k+1 ) is t k+1 The sampling state of the steer-by-wire system at the triggering moment, the discrete model state matrix Discrete model control matrix e is a natural constant, s is an integral variable, T k is the kth sampling interval, satisfying T k =t k+1 -t k , T0 is a fixed sampling interval, satisfying T k =n k T0+θ k , n k Represents the discrete model t k How many fixed sampling intervals T0, θ have passed between the trigger moment and the last trigger moment? k t k The residual value of the sampling interval corresponding to the trigger moment, u(t k ) is t k The input signal of the discrete model at the triggering moment; The discrete model inputs for the steer-by-wire system are as follows: u(t k )=Kx(t k ) Where K is the control matrix of the discrete model input of the steer-by-wire system, x(t k ) is t k The sampling state of the steer-by-wire system at the triggering moment; The discrete model of the steer-by-wire system is considered as a discrete switching system model, which is expressed as follows: Where, is the discrete switching system model state matrix, σ(t k ) is t k The switching signal at the trigger moment, A0 is defined as t k How many fixed sampling intervals have passed between the discrete switching system corresponding to the switching signal at the trigger moment and the last trigger moment? 3. The event trigger-H according to claim 2 ∞ A robust steer-by-wire stability control method is characterized by: The step 2) specifically includes: The convex polyhedron approximation method is used to estimate the time-varying terms to be estimated contained in the discrete switching system model established in step 1) above, as follows: Where, e is a natural constant, θ k t k The residual value of the sampling interval corresponding to the trigger moment, δ(θ k ) is a convex combination of n polyhedron vertices, δ(θ k )∈co{Θ1,Θ2,…,Θ η },Θ κ is a vertex of a convex polyhedron, κ=1,2,…,η; The convex polyhedron discrete switching system model is established as follows: Where, is the state matrix of the convex polyhedron discrete switching system model, and Where, For a convex polyhedron, the vertices are Θ κ The state matrix of the convex polyhedron discrete switching system model, σ(t k ) is t k The switching signal at the trigger moment, A0 is defined as t k How many fixed sampling intervals has the discrete switching system corresponding to the switching signal at the trigger moment passed? Θ κ is a vertex of the convex polyhedron. As the observation data is obtained, the convex polyhedron is continuously adjusted to obtain the estimated value of the time-varying parameter.

4. The event trigger-H according to claim 3 ∞ A robust steer-by-wire stability control method is characterized by: In the step 3): The CAN network has transmission delay. The discrete switching system established in step 1) is regarded as a system with input lag, as follows: Where u i The input lag is θ i The discrete switching system model input is is the time-delay state of the discrete switching system model, K is the control matrix of the discrete switching system model input, θ i is the input lag time; Where I is the unit matrix, A(ρ i ) is the state matrix of the discrete switching system model with uncertain parameters, B(ρ i ) is the control matrix of the discrete switching system model with uncertain parameters.

5. The event trigger-H according to claim 4 ∞ A robust steer-by-wire stability control method is characterized by: The step 4) specifically includes: Construct a state feedback event trigger mechanism. When the steer-by-wire system samples the state x(t k ) and the current system actual state x(t) exceeds the trigger threshold, the current system actual state x(t) is sent through the CAN bus, and the next trigger time is obtained as follows: Where, is the error between the sampling state of the steer-by-wire system and the actual state of the current system, α i is the trigger threshold when the switching signal σ(t)=i, α i ≥0;Ω i is a symmetric positive definite matrix when the switching signal σ(t) = i, i∈ N , N ={1,2,…,N}.

6. The event trigger-H according to claim 5 ∞ A robust steer-by-wire stability control method is characterized by: The step 5) specifically includes: The state space equation of the established vehicle two-degree-of-freedom reference model is expressed as: Where x2(t) is the state of the two-degree-of-freedom reference model, is the state change rate of the two-degree-of-freedom reference model, u2(t) is the two-degree-of-freedom reference model input, A2 is the two-degree-of-freedom reference model state matrix, B2 is the two-degree-of-freedom reference model control matrix, C2 is the two-degree-of-freedom reference model output matrix, D2 is the two-degree-of-freedom reference model direct transfer matrix, and y2(t) is the measurement output of the two-degree-of-freedom reference model; Where k f 、k r are the lateral stiffness of the front and rear wheels respectively, a and b are the distances from the front and rear axles to the center of mass respectively, m is the mass of the vehicle, v x is the longitudinal speed, I z is the moment of inertia of the vehicle around the z-axis; The two-degree-of-freedom reference model is expressed as a discrete switching system model with norm uncertainty and external disturbance effects as follows: z2(t)=C σ(t) x2(t)+D σ(t) u2(t) Where x2(t) is the state of the two-degree-of-freedom reference model, is the state change rate of the two-degree-of-freedom reference model; u2(t) is the input of the two-degree-of-freedom reference model; the switching signal is expressed as σ(t):[0,∞)→ N ={1,2,…,N}; ω(t) is an external disturbance that satisfies the condition ||ω(t)||≤W||x(t)||, where W is a non-negative parameter; z2(t) is the controlled output of the two-degree-of-freedom reference model, which is also the desired state of the steer-by-wire system; A σ(t) ,B σ(t) ,B 1σ(t) ,C σ(t) ,D σ(t) is a constant matrix of appropriate dimension; ΔA σ(t) and ΔB σ(t) is the system uncertainty matrix.

7. The event trigger-H according to claim 6 ∞ A robust steer-by-wire stability control method is characterized by: The step 6) specifically includes: For any i,j∈ N , given a positive constant α i ,λ′ 4i ,λ′ 5i ,λ′ 6i ,μ,θ and N0, where μ>1, N0 is a natural number, if there exists a positive constant λ′ ki ,k∈{1,2,3}, so that the symmetric positive definite matrix X i ,X j ,Ω′ i and matrix Y i satisfy: Where, Where * is the matrix block obtained by matrix symmetry, diag{…} is the diagonal matrix, I is the identity matrix, and A i 、B i 、B 1i 、C i 、D i 、E i 、Y i 、F 1i 、F 2i is a known real constant matrix of appropriate dimension; Based on the non-delay closed-loop augmented system model, the corresponding H ∞ The robust controller gain matrix is ​​as follows: Where K i H ∞ Robust controller gain matrix, X i is a symmetric positive definite matrix, Y i is a known real constant matrix of appropriate dimension; The feedback signal of the event trigger mechanism and the output signal of the vehicle two-degree-of-freedom reference model are used as H ∞ The input of the robust controller is the closed-loop input signal of the steer-by-wire system: u(t k )=K σ(t) x(t k ),t∈[t k ,t k+1 ) Where K σ(t) is the control matrix of the steer-by-wire system, t k is the kth triggering moment, x(t k ) is t k The sampling state of the steer-by-wire system at the triggering moment, u(t k ) is t k Closed-loop input signal to the steer-by-wire system at the triggering moment.

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