Steering-by-wire stability control method based on event triggering-H-infinity robustness

Abstract

The invention discloses an event triggering-H-infinity robust steer-by-wire stability control method. The method comprises the following steps: establishing a discrete switching system model of a steer-by-wire system; estimating time-varying parameter items in the discrete switching system model; establishing a non-time-delay closed-loop augmented system model; a state feedback event triggering mechanism is constructed for the steer-by-wire system, and when the steer-by-wire system state error exceeds a given threshold value, the current steer-by-wire system state is fed back through CAN communication; establishing a vehicle two-degree-of-freedom reference model, and representing the vehicle two-degree-of-freedom reference model as a discrete switching linear system model with norm uncertainty and external disturbance influence; and a feedback signal of the event triggering mechanism and an output signal of the vehicle two-degree-of-freedom reference model serve as input of an H-infinity robust controller, and a closed-loop input signal of the steer-by-wire system is obtained. According to the control method, the occupancy rate of communication resources can be reduced, and the steering stability of the CAN bus under the condition of high load rate is improved.

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 approach. Background Art

[0002] The existing steering stability control methods generally use PID control, sliding film control, and fuzzy control. However, the degree of freedom of wire control steering is greater than that of 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 can provide reliable responses to parameter changes and disturbances by minimizing the worst-case gain, thereby improving the overall safety and driving experience of the vehicle.

[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 lead to instability of the steer-by-wire vehicle system 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 jitter 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 wire-controlled steering stability control method is provided to solve 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 load rate of the CAN bus.

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

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

[0007] 1) Establish a linear continuous system model of the wire control 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) The convex polyhedron approximation method is used to estimate the time-varying parameters in the discrete switching system model;

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

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

[0011] 5) Establish a two-degree-of-freedom reference model of the vehicle and express it as a discrete switching linear system model with norm uncertainty and external disturbance influence;

[0012] 6) Solve the controller gain matrix according to 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 wire-controlled steering 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] In the formula, x(t k+1 ) is t k+1 The sampled 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 time, u(t k ) is t k Input signal of the steer-by-wire discrete system model at the triggering moment;

[0020] The discrete model input of the steer-by-wire system is 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 regarded as a discrete switching system model, which is expressed as follows:

[0024]

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

[0026] σ(t k ) is t k The switching signal at the triggering 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 the above step 1), as follows:

[0029]

[0030] In the formula, 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] In the formula, is the state matrix of the convex polyhedron discrete switching system model, and

[0034]

[0035] In the formula, 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 triggering moment, A0 is defined as t k How many fixed sampling intervals T0 have the subsystem corresponding to the switching signal at the triggering moment passed? Θ κ It 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 parameters.

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

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

[0038]

[0039] In the formula, u i The input delay 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] In the formula, 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] In the formula, the switching signal is θ i The augmented state η i =x(t i ), It is 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 , They are θ i The lower and upper bounds of

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

[0049]

[0050] In the formula, ρ i is an uncertain parameter, is the switching signal θ i The corresponding control matrix of the 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 error between the actual state x(t) of the current system and the actual state x(t) of the current system exceeds the trigger threshold, the actual state x(t) of the current system is sent through the CAN bus, and the next trigger time is obtained as follows:

[0055]

[0056] In the formula, 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=0In the formula, k f , k r are the front and rear wheel cornering stiffnesses, a and b are the distances from the front and rear axles to the center of mass, m is the vehicle mass, v is the 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 represented 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 two-degree-of-freedom reference model input; 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)||, 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 and N0 is a natural number. If there exists 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] In the formula,

[0070]

[0071] Where * is a matrix block obtained by matrix symmetry, diag{…} is a 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] In the formula, 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 wire-controlled steering system:

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

[0077] In the formula, 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 moment of triggering.

[0078] Beneficial effects of the present invention:

[0079] The method of the present invention can improve the stability of the wire control steering system under the limited state of CAN bus communication transmission, adopt an event trigger mechanism, and transmit the signal to the communication network only when the trigger condition is met, thereby reducing the broadband occupancy rate of the communication network. At the same time, the CAN communication delay is converted into a switching parameter through an augmented control sequence, so that the anti-interference performance of the entire steering system is better. BRIEF DESCRIPTION OF THE DRAWINGS

[0080] Figure 1 The schematic diagram of the method of the present invention is shown in FIG. DETAILED DESCRIPTION

[0081] In order to facilitate the understanding of those skilled in the art, the present invention is further described below in conjunction with embodiments and drawings. The contents mentioned in the implementation modes are not intended to limit the present invention.

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

[0083] 1) Establish a linear continuous system model of the wire control 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 wire-controlled steering 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] In the formula, x(t k+1 ) is t k+1 The sampled 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 time, u(t k ) is t k Input signal of the steer-by-wire discrete system model at the triggering moment;

[0090] The discrete model input of the steer-by-wire system is 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 regarded as a discrete switching system model, which is expressed as follows:

[0094]

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

[0096] σ(t k ) is t k The switching signal at the triggering 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) The convex polyhedron approximation method is used to estimate the time-varying parameters in the discrete switching system model; 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 the above step 1), as follows:

[0099]

[0100] In the formula, 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] In the formula, is the state matrix of the convex polyhedron discrete switching system model, and

[0104]

[0105] In the formula, 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 triggering moment, A0 is defined as t k How many fixed sampling intervals T0 have the subsystem corresponding to the switching signal at the triggering moment passed? Θ κ It 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 parameters.

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

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

[0108]

[0109] In the formula, u i The input delay 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] In the formula, 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] In the formula, the switching signal is θ i The augmented state η i =x(t i ), It is 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 , They are θ i The lower and upper bounds of

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

[0119]

[0120] In the formula, ρ i is an uncertain parameter, is the switching signal θ i The corresponding control matrix of the 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) Construct a state feedback event trigger mechanism for the steer-by-wire system. When the state error of the steer-by-wire system exceeds a given threshold, the current state of the steer-by-wire system is fed back through CAN communication. Specifically, it includes:

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

[0125]

[0126] In the formula, 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, which is represented as a discrete switching linear system model with norm uncertainty and external disturbance influence; 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] In the formula, k f , k r are the front and rear wheel cornering stiffnesses, a and b are the distances from the front and rear axles to the center of mass, m is the vehicle mass, and v is the 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 represented 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 two-degree-of-freedom reference model input; 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)||, 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 according to 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; specifically, it includes:

[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 the matrix Y i satisfy:

[0139]

[0140] In the formula,

[0141]

[0142] Where * is a matrix block obtained by matrix symmetry, diag{…} is a 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] In the formula, 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 wire-controlled steering system:

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

[0148] In the formula, 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 moment of triggering.

[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 principle of the present invention. These improvements should also be regarded as the protection scope of the present invention.

Claims

1. An event trigger-H ∞ A robust steer-by-wire stability control method, characterized in that: Here are the steps: 1) Establish a linear continuous system model of the wire control 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 delay into the switching parameters of the discrete switching system model and establish a non-delay closed-loop augmented system model; 4) A state feedback event trigger mechanism is built for the steer-by-wire system. When the state error of the steer-by-wire system exceeds a given threshold, the current state of the steer-by-wire system is fed back through CAN communication; 5) Establish a two-degree-of-freedom reference model of the vehicle and express it as a discrete switching linear system model with norm uncertainty and external disturbance influence; 6) Solve the controller gain matrix according to 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.

2. The event triggering method according to claim 1 ∞ A robust steer-by-wire stability control method, characterized in that: The step 1) specifically includes: The linear continuous system model of the wire-controlled steering 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 ) In the formula, x(t k+1 ) is t k+1 The sampled 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 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 time, u(t k ) is t k Input signal of the steer-by-wire discrete system model at the triggering moment; The discrete model input of the steer-by-wire system is 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 regarded as a discrete switching system model, which is expressed as follows: In the formula, is the discrete switching system model state matrix, σ(t k ) is t k The switching signal at the triggering 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? 3. The event trigger according to claim 2 ∞ A robust steer-by-wire stability control method, characterized in that: 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 the above step 1), as follows: In the formula, 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: In the formula, is the state matrix of the convex polyhedron discrete switching system model, and In the formula, 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 triggering moment, A0 is defined as t k How many fixed sampling intervals T0 have the subsystem corresponding to the switching signal at the triggering moment passed? Θ κ It 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 parameters.

4. The event triggering method according to claim 3 ∞ A robust steer-by-wire stability control method, characterized in that: The step 3) specifically includes: There is a transmission delay in the CAN network. The discrete switching system established in step 1) is regarded as a system with input lag, as follows: In the formula, u i The input delay is θ i The discrete switching system model input, η i-θi 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; 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: In the formula, 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: In the formula, the switching signal is θ i The augmented state η i =x(t i ), It is 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 , They are θ i The lower and upper bounds of The discrete switching system model of the steer-by-wire system and the non-delay closed-loop augmented system model composed of the feedback control law are expressed as: In the formula, ρ i is an uncertain parameter, is the switching signal θ i The corresponding control matrix of the 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; 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 triggering method according to claim 4 ∞ A robust steer-by-wire stability control method, characterized in that: 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 error between the actual state x(t) of the current system and the actual state x(t) of the current system exceeds the trigger threshold, the actual state x(t) of the current system is sent through the CAN bus, and the next trigger time is obtained as follows: In the formula, 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 .

6. The event triggering method according to claim 5 ∞ A robust steer-by-wire stability control method, characterized in that: 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; C2=[0-1],D2=0 In the formula, k f , k r are the front and rear wheel cornering stiffnesses, a and b are the distances from the front and rear axles to the center of mass, m is the vehicle mass, and v is the 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 represented as a discrete switched linear 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 system model; u2(t) is the two-degree-of-freedom reference model input; 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)||, 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 triggering method according to claim 6 ∞ A robust steer-by-wire stability control method, characterized in that: The step 6) specifically includes: For any i,j∈ N , given a positive constant α i ,λ4′ i ,λ5′ i ,λ6′ i ,μ,θ and N0, where μ>1 and N0 is a natural number. If there exists 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: In the formula, Where * is a matrix block obtained by matrix symmetry, diag{…} is a 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: In the formula, 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 wire-controlled steering system: u(t k )=K σ(t) x(t k ),t∈[t k ,t k+1 ) In the formula, 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 moment of triggering.

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