Vehicle active suspension adaptive control method based on high-order full-drive system method

Abstract

The present application belongs to the technical field of vehicle active suspension control, and particularly relates to a vehicle active suspension adaptive control method based on a high-order all-wheel drive system method, which comprises: S1, for a nonlinear vehicle active suspension system, establishing a vehicle active suspension dynamics model, and determining control variables and state variables; S2, transforming the vehicle active suspension dynamics model through state variable equivalence relationship transformation, and establishing a vehicle active suspension model; S3, designing a vehicle active suspension system adaptive controller, and determining control steps and state variables under high-order state; S4, analyzing the stability of the high-order all-wheel drive system adaptive controller, and completing vehicle active suspension adaptive control. The method proposed in the present application no longer analyzes and designs a controller based on a state space model, but directly designs a controller based on a physical model, simplifying the controller design process, and simulation verification proves that the method can be stably and quickly stabilized within a limited time domain, and has good practical application effect.

Description

Technical Field

[0001] This invention belongs to the field of vehicle active suspension control technology, and specifically relates to a vehicle active suspension adaptive control method based on a high-order all-wheel drive system approach. Background Technology

[0002] Vehicle comfort, economy, and safety are currently widely studied issues in the field of vehicle research. The prerequisite for a vehicle to be on the road is ensuring its safety. Once safety is adequately guaranteed, good economy becomes a further requirement. Currently, thanks to extensive research, vehicle safety and economy have been largely ensured, leading to the development of numerous control algorithms to guarantee safety and economy during vehicle operation. With the development of intelligent vehicle technology, vehicle comfort has also received widespread attention, especially with the maturity of autonomous driving technology. Since the driver's role in autonomous vehicles shifts to that of a passenger, who will perform a series of non-driving tasks inside the vehicle, the comfort of autonomous vehicles needs to be effectively guaranteed for widespread application. In the lateral and longitudinal directions of vehicle movement, frequent starts and stops, sharp turns, and sudden acceleration and deceleration directly affect vehicle comfort. In the vertical direction of vehicle movement, road surface unevenness, suspension operation, and vehicle characteristics directly affect driving comfort. However, most scholars study the decoupling of the vehicle's lateral and longitudinal directions and vertical direction. Significant progress has been made in the field of suspension control. The traditional passive suspension has gradually evolved into semi-active suspension and even active suspension. Due to the high application cost and technical requirements, the application of active suspension is not widespread and is still in the research and development stage. Based on its good performance, active suspension has a good prospect for development and application.

[0003] Active suspension, as a key component for vibration isolation in intelligent vehicles, significantly impacts driving comfort. Previous research has effectively addressed the control problem of active suspension using various algorithms. Active suspension control is generally considered a nonlinear problem, and scholars have proposed model-based predictive control, optimal control, and ceiling / floor control algorithms to further control the actuators of the suspension. These algorithms effectively reduce the peak vertical acceleration and improve vehicle comfort. However, previous control algorithms are all based on state-space representations followed by the design of corresponding controllers. Based on the all-wheel-drive control theory proposed by Academician Duan Guangren, this invention proposes an active suspension control method that directly designs an adaptive controller based on the control model. Simulation comparisons verify the effectiveness of the active suspension control method designed based on all-wheel-drive theory. Currently, similar work on active suspension control has not been conducted in the field of high-order all-wheel-drive control. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a vehicle active suspension adaptive control method based on a high-order all-wheel drive system approach. The method proposed in this invention no longer analyzes and designs the controller based on a state-space model, but instead designs the controller directly based on a physical model, simplifying the controller design process. Simulation verification proves that this method can achieve stable, fast, and stable operation within a finite time domain, and its practical application performance is good.

[0005] To achieve the above objectives, the present invention discloses the following technical solution:

[0006] A vehicle active suspension adaptive control method based on a high-order all-wheel drive system approach, comprising:

[0007] S1: For nonlinear vehicle active suspension systems, establish a vehicle active suspension dynamics model and determine control variables and state variables;

[0008] A dynamic analysis of a nonlinear vehicle active suspension system is conducted, and a dynamic model of the vehicle active suspension is established using Newton's second law. The state variables are defined as vehicle body displacement state variable x1 and suspension displacement state variable x2, which are the control inputs u of the active suspension system. The uncertain road disturbance input control variable is ξ.

[0009] S2: Transform the vehicle active suspension dynamics model by state variable equivalence relations to establish a vehicle active suspension model based on the high-order all-wheel drive system method;

[0010] The active suspension dynamics model in step S1 is converted into an all-wheel drive system, and the state variable equivalence relationship is transformed to obtain the vehicle active suspension model based on the high-order all-wheel drive system:

[0011]

[0012] Where: m u The unsprung mass is the same as the wheel mass; m b ξ represents the sprung mass, which is the vehicle body mass; u is the control input for the active suspension system; and ξ is the road disturbance input control variable. Its first derivative, Its second derivative; c s k is the suspension damping coefficient. t k is the tire damping coefficient. s is the suspension spring stiffness coefficient; z is the intermediate state variable. Its first derivative, Its second derivative, z (3) Its third derivative, z (4) Its fourth derivative;

[0013] S3: Design an adaptive controller for a vehicle active suspension system based on a high-order all-wheel drive system, and determine the control steps and state variables of the adaptive controller in the high-order state.

[0014] S31: Design an adaptive controller for the vehicle active suspension system based on a high-order all-wheel drive system method. Using the vehicle active suspension model established in step S2 based on the high-order all-wheel drive system, the state variable values ​​corresponding to the adaptive controller in the high-order state can be obtained. Specifically, this includes the state variable x in the first high-order state. (4) The variable L(x) in the second higher-order state (0～3) ), the variable q(x) in the third higher-order state (0～3) ) and the external uncertainty disturbance variable H in the fourth higher-order state T (x (0～3) )θ;

[0015] S32: The standard equations of a high-order all-wheel drive system are transformed into a physical model of the vehicle's active suspension in the form of a high-order all-wheel drive system:

[0016]

[0017] in: This is an estimate of the uncertainty disturbance. Its first derivative; P L q(x) is a positive definite matrix in the high-order all-drive system method; u* represents the intermediate equivalent parameter in the controller; (0～3) (x) represents the expression in the all-drive formula excluding the controller part and the disturbance part; (0～3) For the state variables in the third-order state, specifically: A 0 ～3 H is the adjustable gain matrix; H is the coefficient before the disturbance variable; L is the coefficient of the control input u of the active suspension system;

[0018] S33: The high-order all-wheel drive system adaptive controller of the vehicle's active suspension system is:

[0019]

[0020] Among them: A 11 For the first high-order all-wheel drive system adaptive control parameters; A 12 For the second high-order all-wheel drive system adaptive control parameters; A 13 For the third high-order all-wheel drive system adaptive control parameters; A 14 For the fourth high-order all-wheel drive system adaptive control parameters; A 15 For the fifth high-order all-wheel drive system adaptive control parameters; A 16 For the sixth-order high-order all-wheel drive system adaptive control parameters; A17 These are the adaptive control parameters for the seventh-order high-order all-wheel drive system;

[0021] S4: Analyze the stability of the adaptive controller of the high-order all-wheel drive system and complete the vehicle active suspension adaptive control based on the high-order all-wheel drive system method;

[0022] Design a Lyapunov function, analyze its stability based on the closed-loop system equation of the high-order all-wheel drive system adaptive controller obtained in step S33; obtain the road excitation model, input the road excitation signal into the vehicle active suspension physical model, and drive the vehicle active suspension system to move.

[0023] Preferably, in step S1, a dynamic analysis is performed on the nonlinear vehicle active suspension system, and a dynamic model of the vehicle active suspension is established using Newton's second law:

[0024]

[0025] Where: z s It is the vertical displacement between the suspension system and the vehicle's center of gravity when the suspension system is stationary and unloaded. Its first derivative, Its second derivative; z u This is the displacement of the suspension. Its first derivative, Its second derivative; z r Input for road surface disturbance displacement;

[0026] To simplify the expression of the state variables, let x1 = z s x2 = z u , z r =ξ.

[0027] Preferably, in step S2, the active suspension dynamics model from step S1 is converted into an all-wheel drive system, and the state variable equivalence relation transformation is performed, specifically as follows:

[0028] S21: The vehicle active suspension dynamics model can be written as the following expression:

[0029]

[0030] Where: x1 is the vehicle body displacement state variable. Its first derivative, It is its second derivative; x2 is the suspension displacement state variable. Its first derivative, Its second derivative;

[0031] S22: Adding the two equations in step S21 is equivalent to eliminating the control variable u, resulting in the following equation:

[0032]

[0033] S23: Order We can obtain the following formula:

[0034]

[0035] S24: From the formula Furthermore, based on the physical context of this model, it can be concluded that:

[0036]

[0037] S25: Using the formula in step S21 and the formula in step S22 Subtracting them, we can obtain:

[0038]

[0039] S26: From the formula We can conclude that:

[0040]

[0041] The relationship between the suspension displacement state variable x2 and the intermediate state variable z is obtained;

[0042] S27: Based on formula The following equation can be derived:

[0043]

[0044] Substituting the first derivative of the suspension displacement state variable The following relationship was derived:

[0045]

[0046] Similarly, we can conclude that:

[0047]

[0048] S28: Substitute the formula derived above into the following formula:

[0049]

[0050] Substituting the variable equivalence relation in the above formula yields the following equation:

[0051]

[0052] Further simplification yields the following formula:

[0053]

[0054] The fourth derivative z of the intermediate state variable is obtained from the above equation. (4) It is possible to obtain a vehicle active suspension model based on a high-order all-wheel drive system.

[0055] Preferably, the method for obtaining the state variable values ​​of the higher-order state corresponding to the adaptive controller in step S31 is as follows:

[0056] The general formula for expressing a high-order all-wheel drive system is:

[0057] x (n) =H T (x (0～n-1) )θ+q(x (0～n-1) )+L(x (0～n-1) u;

[0058] Where: x (n) H is the nth derivative of the state variable; T (x (0～n-1) ) represents the coefficient before the disturbance; q(x) (0～n-1) ) is an nth-order expression excluding the disturbance and control components;

[0059] Converting the vehicle's active suspension physical model into a high-order all-wheel-drive system, substituting n=4 into the above equation yields:

[0060] x (4) =H T (x (0～3) )θ+q(x (0～3) )+L(x (0～3) u;

[0061] Where: x (4) The fourth derivative of the state variable;

[0062] After mapping this to the all-wheel drive expression of the active suspension physical model, the following equation can be derived:

[0063]

[0064] By simplification, we can obtain the following formula:

[0065]

[0066] The values ​​of the state variables in the four higher-order states are determined as follows:

[0067] The state variables in the first higher-order state are:

[0068] x (4) =z (4) ;

[0069] The variables in the second higher-order state are:

[0070]

[0071] The variables in the third higher-order state are:

[0072]

[0073] The external uncertainty disturbance variable in the fourth higher-order state is:

[0074] H T (x (0～3) θ = 0.

[0075] Preferably, the standard equation for the high-order all-drive system in step S32 is:

[0076]

[0077] in: This is an estimate of the uncertainty disturbance. It is its first derivative.

[0078] Preferably, the method for obtaining the intermediate equivalent parameter u* in the controller in step S32 is as follows:

[0079]

[0080] Where u* represents the intermediate equivalent parameter in the controller.

[0081] Preferably, the adjustable gain matrix A in step S32 0～3 The method for obtaining it is as follows:

[0082] In the parametric design process based on the high-order all-drive system controller, the adjustable gain matrix A 0～3 The calculation method is as follows:

[0083] A 0～3 =-ZF 4 V -1 (Z,F);

[0084] Where: Z is the system order matrix; F is the system order influence matrix; V(Z,F) is the parameter matrix of the adjustable gain matrix;

[0085] The parameter matrix V(Z,F) of the adjustable gain matrix is ​​calculated as follows:

[0086]

[0087] The standard form of the system order influence matrix F is shown below:

[0088]

[0089] Wherein: F n-1 denoted as n-1 power of the system order influence matrix; a is the first parameter of the system order influence matrix; b is the second parameter of the system order influence matrix; c is the third parameter of the system order influence matrix; d is the fourth parameter of the system order influence matrix.

[0090] By adjusting the above four parameters, the system can be further made globally convergent and stabilized, and the adjustable gain matrix A can be finally determined. 0～3 .

[0091] Preferably, the high-order all-wheel drive system adaptive controller of the vehicle active suspension system in step S33 includes the following seven parameters, all of which are related to the physical parameters of the vehicle active suspension system, specifically:

[0092] First-order all-wheel drive system adaptive controller parameter A 11 for:

[0093] A 11 =k t ;

[0094] Second-order all-wheel drive system adaptive controller parameter A 12 for:

[0095]

[0096] Third-order all-wheel drive system adaptive controller parameter A 13 for:

[0097]

[0098] Fourth-order all-wheel drive system adaptive controller parameter A 14 for:

[0099]

[0100] Fifth-order all-wheel drive system adaptive controller parameter A 15 for:

[0101]

[0102] Sixth-order high-performance all-wheel drive system adaptive controller parameter A 16 for:

[0103]

[0104] Parameter A of the seventh-order high-performance all-wheel drive system adaptive controller 17 for:

[0105]

[0106] Preferably, in step S4, a Lyapunov function is designed, and its stability is analyzed based on the closed-loop system equations of the high-order all-drive system adaptive controller obtained in step S33. Specifically:

[0107] S41: The closed-loop system equations of the adaptive controller for the high-order all-wheel drive system are as follows:

[0108]

[0109] Among them: A 0～n-1 Let A be an n-order adjustable gain matrix. 0～n-1 =[A0 A1 ... A n-1 ];x (0～n-1) Let n be the state variables in the nth order state. Its derivative; Φ is the influence function of the state variable; 0 (n-1)r For the nth-order constant term parameter;

[0110] S42: Based on the closed-loop system equations of the adaptive controller for high-order all-drive systems, the Lyapunov function is designed as follows:

[0111]

[0112] Where: V is the Lyapunov function; is the first derivative of the Lyapunov function; P is the positive definite matrix in the high-order all-drive system method;

[0113] S43: By taking the derivative of the Lyapunov function, when the derivative is less than 0, it can be concluded that the adaptive controller of the high-order all-drive system is stable.

[0114] Compared with the prior art, the present invention has the following beneficial effects:

[0115] (1) Compared with the traditional vehicle active suspension control method, the method proposed in this invention no longer analyzes and designs the controller based on the state space model, but directly designs the controller based on the physical model, which simplifies the controller design process.

[0116] (2) The present invention combines a parametric design method, the parameter solution process is numerically stable, and the simulation verification proves that the proposed adaptive control scheme based on a high-order all-drive system can achieve rapid stability in the finite time domain.

[0117] (3) Through model building and simulation verification, this invention proves the effectiveness of the proposed active suspension adaptive control scheme based on the high-order all-drive system method with extended state observer compensation. The controlled active suspension system can significantly reduce overshoot, achieve fast convergence in the finite time domain and maintain good tracking performance. Attached Figure Description

[0118] Figure 1 This is a flowchart of the vehicle active suspension adaptive control method based on a high-order all-wheel drive system method according to the present invention;

[0119] Figure 2 This is a physical model diagram of the vehicle active suspension system of the present invention;

[0120] Figure 3 This is a diagram of the road surface excitation signal of the present invention;

[0121] Figure 4 This is a simulation result diagram of the active suspension control force of the present invention;

[0122] Figure 5 This is a simulation result diagram of the suspension dynamic travel of the present invention;

[0123] Figure 6 This is a simulation result diagram of the wheel travel of the present invention;

[0124] Figure 7 This is a simulation result diagram of the vehicle body acceleration of the present invention;

[0125] Figure 8 The figure shows the simulation results of the vehicle body dynamic displacement according to the present invention. Detailed Implementation

[0126] Exemplary embodiments, features, and aspects of the present invention will now be described in detail with reference to the accompanying drawings. The same reference numerals in the drawings denote elements with the same or similar functions. Although various aspects of the embodiments are shown in the drawings, they are not necessarily drawn to scale unless specifically indicated otherwise.

[0127] This invention provides a vehicle active suspension adaptive control method based on a high-order all-wheel drive system approach, such as... Figure 1 As shown, for a nonlinear vehicle active suspension system, a vehicle active suspension dynamics model is established, and control variables and state variables are determined. The vehicle active suspension dynamics model is transformed using equivalent state variable relations to establish a vehicle active suspension model. An adaptive controller for the vehicle active suspension system is designed, and the control steps and state variables in higher-order states are determined. The stability of the high-order all-wheel drive system adaptive controller is analyzed, and the vehicle active suspension adaptive control is completed. The steps include:

[0128] Step S1: For a nonlinear vehicle active suspension system, establish a vehicle active suspension dynamics model and determine the control variables and state variables.

[0129] A dynamic analysis of a nonlinear vehicle active suspension system is performed, and the dynamic model of the vehicle active suspension is established using Newton's second law:

[0130]

[0131] Where: m u The unsprung mass is the same as the wheel mass; m b Sprout mass is the same as vehicle body mass; c s k is the suspension damping coefficient. t k is the tire damping coefficient. s Z is the suspension spring stiffness coefficient; s It is the vertical displacement between the suspension system and the vehicle's center of gravity when the suspension system is stationary and unloaded. Its first derivative, Its second derivative; z u This is the displacement of the suspension. Its first derivative, Its second derivative; z r is the road surface disturbance displacement input; u is the control input of the active suspension system.

[0132] To simplify the expression of the state variables, let x1 = z s x2 = z u Let z be two state variables. r =ξ is the road disturbance input variable, the explicit state variables are the vehicle displacement state variable x1 and the suspension displacement state variable x2, and the control input variable u of the active suspension system is the uncertain road disturbance input variable ξ.

[0133] Step S2: Transform the vehicle active suspension dynamics model by state variable equivalence relations to establish a vehicle active suspension model based on the high-order all-wheel drive system method.

[0134] The active suspension dynamics model in step S1 is converted into an all-wheel drive system, and the equivalent state variable relationships are transformed, specifically as follows:

[0135] Step S21: The vehicle active suspension dynamics model can be written as the following expression:

[0136]

[0137] Where: x1 is the vehicle body displacement state variable. Its first derivative, It is its second derivative; x2 is the suspension displacement state variable. Its first derivative, Its second derivative; ξ is the road disturbance input control variable.

[0138] Since the vehicle active suspension system has two state variables and one control variable, it is an underdriven system and needs to be converted into an all-drive system. That is, the dynamic formula needs to have one state variable and one control variable to meet the requirements of the all-drive system application.

[0139] Step S22: Adding the two equations from step S21 is equivalent to eliminating the control variable u, resulting in the following equation:

[0140]

[0141] Step S23: Let We can obtain the following formula:

[0142]

[0143] Where z is an intermediate state variable. Its first derivative, Its second derivative, z (3) Its third derivative, z (4) Its fourth derivative.

[0144] Step S24: From the formula Furthermore, based on the physical context of this model, it can be concluded that:

[0145]

[0146] Step S25: Use the formula from step S21 and the formula in step S22 Subtracting them, we can obtain:

[0147]

[0148] Step S26: From the formula We can conclude that:

[0149]

[0150] Where ξ is the road surface disturbance input variable, Its first derivative, It is its second derivative.

[0151] The relationship between the suspension displacement state variable x2 and the intermediate state variable z is obtained.

[0152] Step S27: Based on the formula The following equation can be derived:

[0153]

[0154] Substituting the first derivative of the suspension displacement state variable The following relationship was derived:

[0155]

[0156] Similarly, we can conclude that:

[0157]

[0158] Step S28: Substitute the formula obtained above into the following formula:

[0159]

[0160] Substituting the variable equivalence relation in the above formula yields the following equation:

[0161]

[0162] Further simplification yields the following formula:

[0163]

[0164] The fourth derivative z of the intermediate state variable is obtained from the above equation. (4) The vehicle active suspension model based on the high-order all-wheel drive system can be obtained as follows:

[0165]

[0166] Step S3: Design an adaptive controller for the vehicle active suspension system based on a high-order all-wheel drive system, and determine the control steps and state variables of the adaptive controller in the high-order state.

[0167] Step S31: Design the adaptive controller for the vehicle active suspension system based on the high-order all-wheel drive system method. From the vehicle active suspension model established in Step S2 based on the high-order all-wheel drive system, the method for obtaining the state variable values ​​corresponding to the high-order state of the adaptive controller can be derived as follows:

[0168] The general formula for expressing a high-order all-wheel drive system is:

[0169] x (n) =H T (x (0～n-1) )θ+q(x (0～n-1) )+L(x (0～n-1) )u.

[0170] Where: x (n) H is the nth derivative of the state variable; T (x (0～n-1) ) represents the coefficient before the disturbance; q(x) (0～n-1) ) is an nth-order expression excluding the disturbance and control components; L is the coefficient of the control input u of the active suspension system.

[0171] like Figure 2The diagram shown is a physical model of the vehicle active suspension system of the present invention; by converting the vehicle active suspension physical model into a high-order all-wheel drive system, substituting n=4 into the above formula yields:

[0172] x (4) =H T (x (0～3) )θ+q(x (0～3) )+L(x (0～3) )u.

[0173] Where: x (4) It is the fourth derivative of the state variable.

[0174] After mapping this to the all-wheel drive expression of the active suspension physical model, the following equation can be derived:

[0175]

[0176] By simplification, we can obtain the following formula:

[0177]

[0178] The variable values ​​corresponding to the standard form of the high-order all-wheel drive in the four higher-order states are determined as follows:

[0179] The state variables in the first higher-order state are:

[0180] x (4) =z (4) .

[0181] The variables in the second higher-order state are:

[0182]

[0183] The variables in the third higher-order state are:

[0184]

[0185] The external uncertainty disturbance variable in the fourth higher-order state is:

[0186] H T (x (0～3) θ = 0.

[0187] Step S32: Obtain the standard equations for the high-order all-drive system as follows:

[0188]

[0189] in: This is an estimate of the uncertainty disturbance. It is its first derivative.

[0190] The standard equations of a high-order all-wheel drive system are transformed into a physical model of the vehicle's active suspension in the form of a high-order all-wheel drive system:

[0191]

[0192] in: This is an estimate of the uncertainty disturbance. Its first derivative; P L q(x) is a positive definite matrix in the high-order all-drive system method; u* represents the intermediate equivalent parameter in the controller; (0～3) (x) represents the expression in the all-drive formula excluding the controller part and the disturbance part; (0～3) For the state variables in the third-order state, specifically: A 0 ～3 H is the adjustable gain matrix; H is the coefficient before the disturbance variable; L is the coefficient of the control input u of the active suspension system.

[0193] The method for obtaining the intermediate equivalent parameter u* in the controller is as follows:

[0194]

[0195] Where u* represents the intermediate equivalent parameter in the controller.

[0196] Adjustable gain matrix A 0～3 The method for obtaining it is as follows:

[0197] In the parametric design process based on the high-order all-drive system controller, the adjustable gain matrix A 0～3 The calculation method is as follows:

[0198] A 0～3 =-ZF 4 V -1 (Z,F).

[0199] Where: Z is a matrix related to the system order, and in the embodiment, Z =

[1111] ; F is the system order influence matrix, which is a 4th order matrix; V(Z,F) is the parameter matrix of the adjustable gain matrix.

[0200] The parameter matrix V(Z,F) of the adjustable gain matrix is ​​calculated as follows:

[0201]

[0202] The standard form of the system order influence matrix F is shown below:

[0203]

[0204] Wherein: F n-1denoted as n-1 power of the system order influence matrix; a is the first parameter of the system order influence matrix; b is the second parameter of the system order influence matrix; c is the third parameter of the system order influence matrix; d is the fourth parameter of the system order influence matrix; in the embodiment, the values ​​are a=1, b=8, c=12, d=40.

[0205] By adjusting the above four parameters, the system can be further made globally convergent and stabilized, and the adjustable gain matrix A can be finally determined. 0～3 .

[0206] Step S33: Obtain the high-order all-wheel drive system adaptive controller of the vehicle's active suspension system as follows:

[0207]

[0208] Among them: A 11 For the first high-order all-wheel drive system adaptive control parameters; A 12 For the second high-order all-wheel drive system adaptive control parameters; A 13 For the third high-order all-wheel drive system adaptive control parameters; A 14 For the fourth high-order all-wheel drive system adaptive control parameters; A 15 For the fifth high-order all-wheel drive system adaptive control parameters; A 16 For the sixth-order high-order all-wheel drive system adaptive control parameters; A 17 These are the adaptive control parameters for the seventh-order high-order all-wheel drive system.

[0209] The advanced all-wheel-drive adaptive controller of the vehicle's active suspension system includes seven parameters, all of which are related to the physical parameters of the vehicle's active suspension system. Specifically:

[0210] First-order all-wheel drive system adaptive controller parameter A 11 for:

[0211] A 11 =k t .

[0212] Second-order all-wheel drive system adaptive controller parameter A 12 for:

[0213]

[0214] Third-order all-wheel drive system adaptive controller parameter A 13 for:

[0215]

[0216] Fourth-order all-wheel drive system adaptive controller parameter A 14 for:

[0217]

[0218] Fifth-order all-wheel drive system adaptive controller parameter A 15 for:

[0219]

[0220] Sixth-order high-performance all-wheel drive system adaptive controller parameter A 16 for:

[0221]

[0222] Parameter A of the seventh-order high-performance all-wheel drive system adaptive controller 17 for:

[0223]

[0224] Step S4: Analyze the stability of the adaptive controller of the high-order all-wheel drive system and complete the vehicle active suspension adaptive control based on the high-order all-wheel drive system method.

[0225] Design the Lyapunov function, and analyze its stability based on the closed-loop system equations of the high-order all-drive system adaptive controller obtained in step S33. Specifically:

[0226] Step S41: The closed-loop system equations of the adaptive controller for the high-order all-drive system are as follows:

[0227]

[0228] Among them: A 0～n-1 Let A be an n-order adjustable gain matrix. 0～n-1 =[A0A1...A n-1 ];x (0～n-1) Let n be the state variables in the nth order state. Its derivative; Φ is the influence function of the state variable; 0 (n-1)r For the nth-order constant term parameter.

[0229] Step S42: Design the Lyapunov function based on the closed-loop system equations of the high-order all-drive system adaptive controller as follows:

[0230]

[0231] Where: V is the Lyapunov function; is the first derivative of the Lyapunov function; P is the positive definite matrix in the high-order all-drive system method.

[0232] Step S43: Take the derivative of the Lyapunov function. When the derivative is less than 0, it can be concluded that the adaptive controller of the high-order all-drive system is stable.

[0233] Obtain the road surface excitation model, such as Figure 3 The diagram shows the road surface excitation signal of this invention. The road surface excitation signal is input into the vehicle's active suspension physical model to drive the vehicle's active suspension system. The expression for the road surface excitation signal is as follows:

[0234] z r =0.02sin(6π).

[0235] like Figure 4 The figure shown is a simulation result of the active suspension control force of the present invention. It can be seen from the figure that the active suspension controller can achieve the effect of convergence and stabilization in a very short time, and has the same trend of force change as the road excitation.

[0236] like Figure 5 The figure shown is a simulation result of the suspension dynamic travel of the present invention; through comparative verification, it can be concluded that the proposed controller based on high-order all-wheel drive theory has a better control effect than passive suspension and active suspension under fuzzy PID control. Figure 6 The figure shown is a simulation result of the wheel travel of the present invention; through comparison and verification, it can be concluded that the proposed controller based on high-order all-wheel drive theory has a better control effect than passive suspension and active suspension under fuzzy PID control. Figure 7 The figure shown is a simulation result of the vehicle body acceleration according to the present invention. Comparative verification shows that the proposed controller based on high-order all-wheel drive theory has better control performance compared to passive suspension and active suspension under fuzzy PID control. Figure 8 The figure shown is a simulation result of the vehicle body dynamic displacement according to the present invention. Comparative verification shows that the proposed controller based on high-order all-wheel drive theory has better control performance compared to passive suspension and active suspension under fuzzy PID control. Through a series of model building and simulation verifications, the embodiments of the present invention demonstrate the effectiveness of the proposed active suspension adaptive control scheme based on a high-order all-wheel drive system method with extended state observer compensation. The controlled active suspension system can significantly reduce overshoot, achieve fast convergence within a finite time domain, and maintain good tracking performance. Based on sinusoidal road surface modeling, the established road surface model is used as a reference excitation signal input into the active suspension physical model to drive the motion of the active suspension, verifying that the proposed adaptive controller has good control performance.

[0237] The beneficial effects of this invention are as follows: This invention provides a vehicle active suspension adaptive control method based on a high-order all-wheel drive system approach. Compared with traditional vehicle active suspension control methods, the method proposed in this embodiment no longer analyzes and designs the controller based on a state-space model, but directly designs the controller based on a physical model, simplifying the controller design process. The embodiment incorporates a parametric design method, ensuring numerical stability in the parameter solution process. Simulation verification demonstrates that the proposed adaptive control scheme based on high-order all-wheel drive system theory can achieve stable and rapid stabilization within a finite time domain. Model building and simulation verification prove the effectiveness of the proposed active suspension adaptive control scheme based on a high-order all-wheel drive system approach with extended state observer compensation. The controlled active suspension system significantly reduces overshoot, achieves rapid convergence within a finite time domain, and maintains good tracking performance.

[0238] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Various modifications and improvements made by those skilled in the art to the technical solutions of the present invention without departing from the spirit of the present invention should fall within the protection scope defined by the claims of the present invention.

Claims

1. A vehicle active suspension adaptive control method based on a high-order all-wheel drive system approach, characterized in that, It includes: S1: For nonlinear vehicle active suspension systems, establish a vehicle active suspension dynamics model and determine control variables and state variables; A dynamic analysis of a nonlinear vehicle active suspension system is conducted, and a dynamic model of the vehicle active suspension is established using Newton's second law. The state variables are defined as vehicle body displacement state variable x1 and suspension displacement state variable x2, which are the control inputs u of the active suspension system. The uncertain road disturbance input control variable is ξ. S2: Transform the vehicle active suspension dynamics model by state variable equivalence relations to establish a vehicle active suspension model based on the high-order all-wheel drive system method; The active suspension dynamics model in step S1 is converted into an all-wheel drive system, and the state variable equivalence relationship is transformed to obtain the vehicle active suspension model based on the high-order all-wheel drive system: Where: m u The unsprung mass is the same as the wheel mass; m b ξ represents the sprung mass, which is the vehicle body mass; u is the control input for the active suspension system; and ξ is the road disturbance input control variable. Its first derivative, Its second derivative; c s k is the suspension damping coefficient. t k is the tire damping coefficient. s is the suspension spring stiffness coefficient; z is the intermediate state variable. Its first derivative, Its second derivative, z (3) Its third derivative, z (4) Its fourth derivative; S3: Design an adaptive controller for a vehicle active suspension system based on a high-order all-wheel drive system, and determine the control steps and state variables of the adaptive controller in the high-order state. S31: Design an adaptive controller for the vehicle active suspension system based on a high-order all-wheel drive system method. Using the vehicle active suspension model established in step S2 based on the high-order all-wheel drive system, the state variable values ​​corresponding to the adaptive controller in the high-order state can be obtained. Specifically, this includes the state variable x in the first high-order state. (4) The variable L(x) in the second higher-order state (03) ), the variable q(x) in the third higher-order state (03) ) and the external uncertainty disturbance variable H in the fourth higher-order state T (x (03) )θ; S32: The standard equations of a high-order all-wheel drive system are transformed into a physical model of the vehicle's active suspension in the form of a high-order all-wheel drive system: in: This is an estimate of the uncertainty disturbance. Its first derivative; P L q(x) is a positive definite matrix in the high-order all-drive system method; u* represents the intermediate equivalent parameter in the controller; (03) (x) represents the expression in the all-drive formula excluding the controller part and the disturbance part; (03) For the state variables in the third-order state, specifically: A 03 H is the adjustable gain matrix; H is the coefficient before the disturbance variable; L is the coefficient of the control input u of the active suspension system; S33: The high-order all-wheel drive system adaptive controller of the vehicle's active suspension system is: Among them: A 11 For the first high-order all-wheel drive system adaptive control parameters; A 12 For the second high-order all-wheel drive system adaptive control parameters; A 13 For the third high-order all-wheel drive system adaptive control parameters; A 14 For the fourth high-order all-wheel drive system adaptive control parameters; A 15 For the fifth high-order all-wheel drive system adaptive control parameters; A 16 For the sixth-order high-order all-wheel drive system adaptive control parameters; A 17 These are the adaptive control parameters for the seventh-order high-order all-wheel drive system; S4: Analyze the stability of the adaptive controller of the high-order all-wheel drive system and complete the vehicle active suspension adaptive control based on the high-order all-wheel drive system method; Design a Lyapunov function, analyze its stability based on the closed-loop system equation of the high-order all-wheel drive system adaptive controller obtained in step S33; obtain the road excitation model, input the road excitation signal into the vehicle active suspension physical model, and drive the vehicle active suspension system to move.

2. The vehicle active suspension adaptive control method based on a high-order all-wheel drive system method according to claim 1, characterized in that: In step S1, a dynamic analysis is performed on the nonlinear vehicle active suspension system. The dynamic model of the vehicle active suspension is established using Newton's second law as follows: Where: z s It is the vertical displacement between the suspension system and the vehicle's center of gravity when the suspension system is stationary and unloaded. Its first derivative, Its second derivative; z u This is the displacement of the suspension. Its first derivative, Its second derivative; z r Input for road surface disturbance displacement; To simplify the expression of the state variables, let x1 = z s x2 = z u , z r =ξ.

3. The vehicle active suspension adaptive control method based on a high-order all-wheel drive system method according to claim 1, characterized in that: Step S2 involves converting the active suspension dynamics model from step S1 into an all-wheel drive system and performing a state variable equivalence transformation, specifically: S21: The vehicle active suspension dynamics model can be written as the following expression: Where: x1 is the vehicle body displacement state variable. Its first derivative, It is its second derivative; x2 is the suspension displacement state variable. Its first derivative, Its second derivative; S22: Adding the two equations in step S21 is equivalent to eliminating the control variable u, resulting in the following equation: S23: Order We can obtain the following formula: S24: From the formula Furthermore, based on the physical context of this model, it can be concluded that: S25: Using the formula in step S21 and the formula in step S22 Subtracting them, we can obtain: S26: From the formula We can conclude that: The relationship between the suspension displacement state variable x2 and the intermediate state variable z is obtained; S27: Based on formula The following equation can be derived: Substituting the first derivative of the suspension displacement state variable The following relationship was derived: Similarly, we can conclude that: S28: Substitute the formula derived above into the following formula: Substituting the variable equivalence relation in the above formula yields the following equation: Further simplification yields the following formula: The fourth derivative z of the intermediate state variable is obtained from the above equation. (4) It is possible to obtain a vehicle active suspension model based on a high-order all-wheel drive system.

4. The vehicle active suspension adaptive control method based on a high-order all-wheel drive system method according to claim 1, characterized in that: The method for obtaining the state variable values ​​of the higher-order state corresponding to the adaptive controller in step S31 is as follows: The general formula for expressing a high-order all-wheel drive system is: x (n) =H T (x (0n-1) )θ+q(x (0n-1) )+L(x (0n-1) )u; Where: x (n) H is the nth derivative of the state variable; T (x (0～n-1) ) represents the coefficient before the disturbance; q(x) (0n-1) ) is an nth-order expression excluding the disturbance and control components; Converting the vehicle's active suspension physical model into a high-order all-wheel-drive system, substituting n=4 into the above equation yields: x (4) =H T (x (03) )θ+q(x (03) )+L(x (03) )u; Where: x (4) The fourth derivative of the state variable; After mapping this to the all-wheel drive expression of the active suspension physical model, the following equation can be derived: By simplification, we can obtain the following formula: The values ​​of the state variables in the four higher-order states are determined as follows: The state variables in the first higher-order state are: x (4) =z (4) ; The variables in the second higher-order state are: The variables in the third higher-order state are: The external uncertainty disturbance variable in the fourth higher-order state is: H T (x (03) )θ=0.

5. The vehicle active suspension adaptive control method based on a high-order all-wheel drive system method according to claim 1, characterized in that: The standard equation for the high-order all-drive system in step S32 is: in: This is an estimate of the uncertainty disturbance. It is its first derivative.

6. The vehicle active suspension adaptive control method based on a high-order all-wheel drive system method according to claim 1, characterized in that: The method for obtaining the intermediate equivalent parameter u* in the controller in step S32 is as follows: Where u* represents the intermediate equivalent parameter in the controller.

7. The vehicle active suspension adaptive control method based on a high-order all-wheel drive system method according to claim 1, characterized in that: The adjustable gain matrix A in step S32 03 The method for obtaining it is as follows: In the parametric design process based on the high-order all-drive system controller, the adjustable gain matrix A 03 The calculation method is as follows: A 03 =-ZF 4 V -1 (Z,F); Where: Z is the system order matrix; F is the system order influence matrix; V(Z,F) is the parameter matrix of the adjustable gain matrix; The parameter matrix V(Z,F) of the adjustable gain matrix is ​​calculated as follows: The standard form of the system order influence matrix F is shown below: Wherein: F n-1 denoted as n-1 power of the system order influence matrix; a is the first parameter of the system order influence matrix; b is the second parameter of the system order influence matrix; c is the third parameter of the system order influence matrix; d is the fourth parameter of the system order influence matrix. By adjusting the above four parameters, the system can be further made globally convergent and stabilized, and the adjustable gain matrix A can be finally determined. 03 .

8. The vehicle active suspension adaptive control method based on a high-order all-wheel drive system method according to claim 1, characterized in that: The high-order all-wheel drive system adaptive controller of the vehicle active suspension system in step S33 includes the following seven parameters, all of which are related to the physical parameters of the vehicle active suspension system, specifically: First-order all-wheel drive system adaptive controller parameter A 11 for: A 11 =k t ; Second-order all-wheel drive system adaptive controller parameter A 12 for: Third-order all-wheel drive system adaptive controller parameter A 13 for: Fourth-order all-wheel drive system adaptive controller parameter A 14 for: Fifth-order all-wheel drive system adaptive controller parameter A 15 for: Sixth-order high-performance all-wheel drive system adaptive controller parameter A 16 for: Parameter A of the seventh-order high-performance all-wheel drive system adaptive controller 17 for:

9. The vehicle active suspension adaptive control method based on a high-order all-wheel drive system method according to claim 1, characterized in that: In step S4, the Lyapunov function is designed, and its stability is analyzed based on the closed-loop system equations of the high-order all-drive system adaptive controller obtained in step S33. Specifically: S41: The closed-loop system equations of the adaptive controller for the high-order all-wheel drive system are as follows: x (n) +A 0 n-1 x (0n-1) =0 Among them: A 0 n-1 Let A be an n-order adjustable gain matrix. 0 n-1 =[A0 A1 ... A n-1 ];x (0 n-1) Let n be the state variables in the nth order state. Its derivative; Φ is the influence function of the state variable; 0 (n-1)r For the nth-order constant term parameter; S42: Based on the closed-loop system equations of the adaptive controller for high-order all-drive systems, the Lyapunov function is designed as follows: Where: V is the Lyapunov function; is the first derivative of the Lyapunov function; P is the positive definite matrix in the high-order all-drive system method; S43: By taking the derivative of the Lyapunov function, when the derivative is less than 0, it can be concluded that the adaptive controller of the high-order all-drive system is stable.

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