Vehicle control method and device

Abstract

The invention provides a vehicle control method and device, and the method comprises the steps: obtaining a structure parameter and a motion parameter of a vehicle and a digital signal outputted by a quantizer, and constructing a state-space equation of an open-loop system of the vehicle based on the structure parameter, the motion parameter and the digital signal; calculating a quantization error of the quantizer according to the digital signal, wherein the quantization error is a bounded value; taking the quantization error as bounded disturbance of a target robust controller model to be constructed, constructing a state-space equation of a closed-loop system of the vehicle based on a standard robust controller model and the state-space equation of the open-loop system, and determining a closed-loop transfer function corresponding to the state-space equation of the closed-loop system, a target robust controller model is constructed; and performing transverse and longitudinal control on the vehicle based on the target robust controller model.

Description

Technical Field

[0001] The present application relates to the field of vehicle technology, and in particular to a vehicle control method and device. Background Art

[0002] In control system theory, it is usually assumed that the signal output by the controller reaches the actuator directly and there is no signal loss during transmission. However, in actual scenarios, considering the actuator's signal requirements and the bandwidth of the transmission link, the transmitted signal needs to be quantized by a quantizer, which leads to an error between the signal output by the controller and the signal received by the actuator.

[0003] When using a quantizer in related technology to quantize a signal, the quantization error is uncontrollable, resulting in the inability to use current controller design methods to design a controller model based on the quantization of the signal, which increases the difficulty of controller design and makes it impossible to guarantee the control accuracy of the vehicle. Summary of the invention

[0004] In view of this, the present application provides a vehicle control method and device to solve the defects existing in the related technology. The technical solution of the present application is as follows:

[0005] According to an embodiment of the first aspect of the present application, there is provided a vehicle control method, comprising:

[0006] Acquire structural parameters and motion parameters of the vehicle and a digital signal output by a quantizer, and construct a state space equation of an open-loop system of the vehicle based on the structural parameters, the motion parameters and the digital signal;

[0007] Calculating a quantization error of the quantizer according to the digital signal, wherein the quantization error is a bounded value;

[0008] Taking the quantization error as a bounded disturbance of a target robust controller model to be constructed, constructing a state space equation of a closed loop system of the vehicle based on a standard robust controller model and a state space equation of the open loop system, and determining a closed loop transfer function corresponding to the state space equation of the closed loop system, and constructing the target robust controller model;

[0009] The vehicle is controlled in the lateral and longitudinal directions based on the target robust controller model.

[0010] According to an embodiment of the second aspect of the present application, there is provided a control device for a vehicle, comprising:

[0011] An acquisition unit, used for acquiring structural parameters and motion parameters of the vehicle and a digital signal output by a quantizer; constructing a state space equation of an open-loop system of the vehicle based on the structural parameters, the motion parameters and the digital signal;

[0012] an error determination unit, configured to calculate a quantization error of the quantizer according to the digital signal, wherein the quantization error is a bounded value;

[0013] A controller construction unit, taking the quantization error as a bounded disturbance of a target robust controller model to be constructed, constructing a state space equation of a closed-loop system of the vehicle based on the standard robust controller model and the state space equation of the open-loop system, and determining a closed-loop transfer function corresponding to the state space equation of the closed-loop system, and constructing the target robust controller model;

[0014] A lateral and longitudinal control unit is used to perform lateral and longitudinal control on the vehicle based on the target robust controller model.

[0015] According to an embodiment of the third aspect of the present application, an electronic device is provided, comprising a memory, a processor, and executable instructions stored in the memory and executable on the processor, wherein the processor implements the method described in the first aspect by executing the executable instructions.

[0016] According to an embodiment of the fourth aspect of the present application, a computer-readable storage medium is provided, on which computer instructions are stored. When the instructions are executed by a processor, the steps of the method described in the first aspect are implemented.

[0017] According to an embodiment of the fifth aspect of the present application, a computer program product is provided, comprising a computer program / instruction, which, when executed by a processor, implements the steps of the method described in the first aspect.

[0018] In the technical solution provided by the present application, the quantization error obtained after the quantizer quantizes the signal is a bounded value. Therefore, in the process of constructing the target robust controller model, the quantization error can be regarded as a bounded disturbance existing in the controller design process for processing, and then the target robust controller model is constructed, and the vehicle is controlled based on the target robust controller model. By applying the technical solution of the present application, the quantization error can be controlled within a bounded range, and then the current controller design method can be used to design the controller model while quantizing the signal, which reduces the difficulty of controller design and ensures the control accuracy of the vehicle.

[0019] It should be understood that the above general description and the following detailed description are merely exemplary and explanatory and do not limit the embodiments of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the embodiments of the present application. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0021] Figure 1 is a schematic diagram of a vehicle networking architecture shown in an exemplary embodiment of the present application;

[0022] Figure 2 is a flow chart of a vehicle control method shown in an exemplary embodiment of the present application;

[0023] Figure 3 is a schematic diagram of a quantization relationship of a quantizer shown in an exemplary embodiment of the present application;

[0024] Figure 4 is a schematic diagram of a controller model shown in an exemplary embodiment of the present application;

[0025] Figure 5 is a schematic diagram of an electronic device shown in an exemplary embodiment of the present application;

[0026] Figure 6 It is a schematic diagram of a vehicle control device shown in an exemplary embodiment of the present application. DETAILED DESCRIPTION

[0027] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with one or more embodiments of the present application. Instead, they are merely examples of devices and methods consistent with some aspects of one or more embodiments of the present application as detailed in the appended claims.

[0028] It should be noted that: in other embodiments, the steps of the corresponding method are not necessarily performed in the order shown and described in this application. In some other embodiments, the steps included in the method may be more or less than those described in this application. In addition, a single step described in this application may be decomposed into multiple steps for description in other embodiments; and multiple steps described in this application may also be combined into a single step for description in other embodiments.

[0029] The user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of relevant countries and regions, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0030] In traditional control systems, it is usually assumed that the state signal of the controlled object can reach the controller directly without loss, and the control signal of the controller can also be transmitted to the actuator without loss. However, in actual environments, due to the use of a large number of digital processors, analog signals and digital signals need to be converted to each other, and this conversion cannot achieve ideal accuracy due to the limitation of the accuracy of the collected data. At the same time, with the development of the network, traditional control has begun to shift to network control. In a network control system, if the amount of transmitted signal data is too large, signal transmission may also be delayed and blocked.

[0031] However, when a smart car is driving, the accuracy and robustness of control are crucial to driving safety, and an effective control strategy is a key technical means to control the vehicle trajectory and improve active safety performance. When the accuracy of signal conversion is not ideal, or when there is network delay or congestion, the vehicle's control accuracy will be greatly reduced, and the safety of autonomous driving will also decrease. Therefore, it is extremely necessary to include the control signal quantization link in the signal transmission process.

[0032] It is understandable that since quantization is the process of converting a continuous analog signal into a piecewise constant signal of a finite set, this results in an error between the digital signal processed by the quantizer and the analog signal input to the quantizer, namely, the quantization error. However, when using a quantizer in the related art to quantize a signal, the quantization error of some quantizers is not controllable, resulting in the inability to use the current controller design method to design a controller model based on the quantization of the signal, which increases the difficulty of controller design.

[0033] In order to solve the above problems, the present application proposes a vehicle control method. In the technical solution provided in the present application, the quantization error obtained after the quantizer quantizes the signal is a bounded value. Therefore, in the process of constructing the target robust controller model, the quantization error can be regarded as a bounded disturbance existing in the controller design process for processing, and then the target robust controller model is constructed, and the vehicle is controlled based on the target robust controller model. By applying the technical solution of the present application, the quantization error can be controlled within a bounded range, and then the current controller design method can be used to design the controller model while quantizing the signal, reducing the difficulty of controller design.

[0034] The technical solutions provided by the embodiments of the present application will be described in detail below with reference to the accompanying drawings.

[0035] Figure 1 1 is a signal processing flow chart shown in an exemplary embodiment of the present application. The main processing node includes a control module 11 and an execution module 12 , and the control module 11 may specifically include a controller 111 and a quantizer 112 .

[0036] First of all, it should be noted that when the execution module 12 controls the target object according to the received control signal, there may be an error between the actual change of the target object and the expected change represented by the control signal. For example, in the case where the execution module is a chassis module of a vehicle, the control signal received by the chassis module indicates that the steering wheel of the vehicle needs to turn left by 30°, but after actual execution, the steering wheel may only turn left by 29°, with an error of 1°, that is, the error between the expected value and the actual value, which can be called a state error.

[0037] In this regard, the control module 11 can readjust the control signal output by itself based on the state error, so that the execution module 12 controls the target object based on the new control signal. Specifically, the control module 11 can use the state error x as the input of the controller 111, and obtain the analog signal u that can represent the expected value after calculation by the controller. After that, u can be input into the quantizer 112 for quantization to obtain the digital signal Q(u) corresponding to the analog signal u after quantization. Finally, Q(u) is transmitted to the execution module 12, so that the execution module 12 controls the target object according to Q(u). It can be understood that after the control module 12 actually performs the control operation, the state error x can be calculated again based on the expected value and the actual value, and the state error x can be used as the input of the controller 111, and the above process is repeated until the actual value is equal to the expected value.

[0038] Figure 2 FIG. 1 is a flow chart of a vehicle control method shown in an exemplary embodiment of the present application, wherein the method specifically comprises the following steps:

[0039] Step 201 , obtaining structural parameters and motion parameters of the vehicle and a digital signal output by a quantizer, and constructing a state space equation of an open-loop system of the vehicle based on the structural parameters, the motion parameters and the digital signal.

[0040] In one embodiment, the state space equation of the open-loop system of the vehicle can be constructed based on the acquired structural parameters and motion parameters of the vehicle and the digital signal output by the quantizer. Among them, the structural parameters of the vehicle are parameters that describe the inherent properties of the vehicle, which are usually determined in the vehicle design and manufacturing stage and remain unchanged throughout the vehicle life cycle, including the vehicle's mass, front overhang length, rear overhang length, moment of inertia around the axis, front wheel lateral stiffness, and rear wheel lateral stiffness. The vehicle motion parameters are parameters that describe the real-time changes of the vehicle during movement, which are usually obtained by real-time measurement by sensors, including the vehicle's speed, position, heading angle, etc. For the above two concepts, the structural parameters and motion parameters of the vehicle are both important parameters that describe the performance of the vehicle. The difference is that the vehicle structural parameters are the inherent properties of the vehicle, which are usually determined in the design stage, while the vehicle motion parameters change in real time, are usually measured by sensors, and reflect the current dynamic state of the vehicle.

[0041] The state space equation of a vehicle is a mathematical model that describes the dynamic behavior of the vehicle, and is usually used to describe the state and state changes of the vehicle at different time points. According to the influence of the vehicle structural parameters on the vehicle state, a vehicle structural parameter model is constructed. Then, according to the kinematic and dynamic laws of the vehicle, a vehicle motion parameter model is constructed. Considering that the analog signal u will be quantized in the present application to obtain a quantized digital signal Q(u), therefore, based on the vehicle's structural parameters, motion parameters, state errors and quantized digital signals, the state space equation ∑1 of the vehicle's open-loop system can be obtained as shown in the following formula (1):

[0042]

[0043] in,

[0044]

[0045] Among them, A is the state transfer matrix, B is the control matrix, in A matrix and B matrix, C af is the front wheel cornering stiffness, C ar is the rear wheel cornering stiffness, l f is the front overhang length, l r is the rear overhang length, I z is the moment of inertia of the vehicle around the z-axis, v x is the longitudinal speed of the vehicle, m is the mass of the vehicle. x is the state error, which is the error between the expected value and the actual value mentioned in the above embodiment, specifically including the lateral error e1, the lateral error change rate Heading error e2, heading error change rate Position error e3 and speed error e4.

[0046] Specifically, the vehicle motion parameters, including the longitudinal velocity v, are measured in real time during the vehicle motion process through speed sensors, accelerometers, gyroscopes and RTK (Real-Time Kinematic). x , position (x, y), heading angle θ, etc. Calculate the lateral error e1 and lateral error change rate based on the position (x, y) Position error e3. Calculate heading error e2 based on heading angle θ, and heading error change rate According to the longitudinal velocity v x Calculate the velocity error e4.

[0047] In one embodiment, the analog signal u is quantized by the quantizer provided in the present application, and then a digital signal Q(u) can be obtained. Since the signal output by the controller includes the analog signal of the steering wheel angle and the analog signal of the acceleration, that is, u = [δ, α] T , δ is the analog signal of the steering wheel angle, and α is the analog signal of the acceleration. Therefore, the quantized signal Q(u) = [q(δ), q(α)] obtained by quantization processing T , q(δ) is the digital signal of the quantized steering wheel angle, and q(α) is the digital signal of the quantized acceleration.

[0048] Specifically, the quantizer provided in the present application includes a first quantization unit and a second quantization unit, and the specific form is shown in the following formula (2):

[0049]

[0050] Among them, u th It is the demarcation threshold, indicating the threshold at which the first quantization unit and the second quantization unit switch each other. The specific value is determined by the technicians according to actual needs and experience, and this application does not limit this.

[0051] When the amplitude of the analog signal u to be quantized is greater than the demarcation threshold, that is, |u|>u th In the case of, the first quantization unit is used to quantize the analog signal u, which is shown in the following formula (3):

[0052]

[0053] For the first quantization unit, the quantization unit is constructed based on a uniform quantizer and an adjustment parameter, wherein the form of the referenced uniform quantizer is shown in the following formula (4):

[0054]

[0055] Int[a] represents the largest integer not greater than a. Determines the quantization density of the uniform quantizer,

[0056] The q contained in the first quantization unit h (u th ) and K(u th ) is the adjustment parameter,

[0057] It can be understood that, since the quantizer provided in the present application includes two quantization units, when the amplitude of the analog signal is the same as the demarcation threshold, the quantization values ​​corresponding to the two sides of the demarcation threshold may jump. Therefore, by combining the adjustment parameter with the uniform quantizer to construct the first quantization unit, when the amplitude of the analog signal u is equal to the demarcation threshold u th In this case, the continuity of the quantized digital signal is maintained.

[0058] The amplitude of the analog signal u to be quantized is not greater than the demarcation threshold, that is, |u|≤u th In the case of, the second quantization unit is used to quantize the analog signal u, which is shown in the following formula (5):

[0059] q(u)=q h (u) (5)

[0060] The q involved in the first quantization unit and the second quantization unit h (u) represents the form of the hysteresis quantizer, as shown in the following equation (6):

[0061]

[0062] In the above formula, u i =ρ 1-i u min , i=1,2,...,u min >0 and 0<ρ<1 determine q h (u) size of the dead zone, q h (u) In the set U = {0, ±u i , ±u i (1+σ)}, ρ is the quantization density. h For details of (u), please refer to the design method of hysteresis quantizer in the related art, which will not be described here.

[0063] It is understandable that no matter what kind of quantizer is used, in the process of converting a continuous analog signal into a piecewise constant signal of a finite set, there must be a quantization error, that is, the error between the digital signal processed by the quantizer and the analog signal input to the quantizer. But generally speaking, the working principle of the uniform quantizer is to divide the amplitude range of the input signal into intervals of the same width, and all samples falling into the same interval are encoded into the same digital signal. If the amplitude of the input signal is small, then the fixed interval range is difficult to meet the requirements of the small amplitude signal for the quantization signal-to-noise ratio; and although the hysteresis quantizer can meet the requirements of the small amplitude signal for the quantization signal-to-noise ratio, as the amplitude of the input signal increases, the quantization error of the hysteresis quantizer will also increase, resulting in uncontrollable quantization error.

[0064] The quantizer provided in this application is designed with reference to the uniform quantizer and hysteresis quantizer in the related art. When the signal amplitude is small, the hysteresis quantizer is used to quantize the analog signal. When the signal amplitude is large, the adjusted uniform quantizer is used to quantize the analog signal. In the case of, the quantization schematic diagram of the quantizer provided in this application is as follows Figure 3 As shown, it can be seen that the quantizer is a linearizable quantizer. Therefore, when the quantizer provided by the present application is used, no matter what the amplitude of the analog signal to be quantized is, the requirement of quantization signal-to-noise ratio can be met, and the quantization error can be controlled.

[0065] Step 202: Calculate a quantization error of the quantizer according to the digital signal, wherein the quantization error is a bounded value.

[0066] In one embodiment, as described above, in the process of converting a continuous analog signal into a piecewise constant signal of a finite number set, there is inevitably a quantization error. Therefore, the quantization error Δq(u) can be calculated based on the quantization result q(u) of any signal u to be quantized by the quantizer provided by the present application, as shown in the following formula (7):

[0067]

[0068] It can be seen from the above formula that the quantization error Δq(u) of the quantizer provided in this application is bounded for any u, that is, there is a positive constant So that |Δq(u)|≤d. In other words, the quantization error of the quantizer provided in the present application must be less than a positive value and greater than a negative value, that is, the quantization error is a bounded value. When the analog signal represented by u is an analog signal of a steering wheel angle, the quantization error corresponding to the steering wheel angle is Δq(δ); when the analog signal represented by u is an analog signal of acceleration, the quantization error corresponding to the acceleration is Δq(α); both Δq(δ) and Δq(α) are bounded values.

[0069] Step 203, using the quantization error as a bounded disturbance of the target robust controller model to be constructed, constructing the state space equation of the closed-loop system of the vehicle based on the standard robust controller model and the state space equation of the open-loop system, and determining the closed-loop transfer function corresponding to the state space equation of the closed-loop system, and constructing the target robust controller model.

[0070] In one embodiment, the design method of the controller in the related art has taken into account the influence of bounded disturbance on the control signal. Therefore, when the quantization error of the quantizer provided in the present application is a bounded value, the quantization error can be directly regarded as a bounded disturbance. Based on the standard robust controller model H ∞ And the state space equation ∑1 of the open-loop system mentioned above, construct the state space equation ∑4 of the closed-loop system of the vehicle.

[0071] Specifically, from Δq(u)=q(u)-u, we can get q(u)=u+Δq(u). Therefore, when the quantization error corresponding to the steering wheel angle is Δq(δ) and the quantization error corresponding to the acceleration is Δq(α), ΔQ(u)=[Δq(δ), Δq(α)] T It represents the quantization error matrix of steering wheel angle and acceleration.

[0072] On this basis, the state space equation ∑1 of the open-loop system can be first transformed into the state space equation ∑2 in the following form, as shown in equation (8):

[0073]

[0074] At this point, in order to use the standard robust controller model to construct the state space equation of the closed-loop system later, the state space equation ∑2 can be converted into the state space equation ∑3, as shown in the following equation (9):

[0075]

[0076] In the above formula, z is the adjustable output, that is, the theoretical output signal vector. y is the measured output, that is, the measured output signal vector. A and B are the state transfer matrix and control matrix mentioned above, respectively. C1 and C2 are the unit matrices with 6 rows and 6 columns, and D 11 , D 12 , D 21 , D 22 is a zero matrix with 6 rows and 1 column.

[0077] Afterwards, the state feedback matrix of the standard robust controller model may be obtained, and the state feedback matrix may be substituted into the state space equation of the open-loop system to construct the state space equation ∑4 of the closed-loop system of the vehicle.

[0078] It should be noted that in the embodiment of the present application, a robust H∞ controller model is used to realize the lateral and longitudinal control of the vehicle. Figure 4 shown.

[0079] exist Figure 4 In the H∞ control problem, K(s) is the controller and G(s) is the controlled object. G(s) is also called a generalized object. The generalized object has two outputs, one is the weighted output z representing the performance requirements, and the other is the output y added to the controller. z is the theoretical output signal vector, and y is the measured output signal vector. The generalized object G(s) also has two inputs, one is all external disturbances w acting on the object, and the other is the control input u acting on the object from the controller output.

[0080] The closed-loop transfer function can describe the relationship between the input and output of the system and can be used to evaluate the performance and stability of the system. Therefore, the goal of H∞ control is to design a controller u(s) = K(s)y(s) so that the closed-loop system is internally stable and the H∞ norm of the closed-loop transfer function from the disturbance input w to the adjustable output z is less than a given performance indicator γ>0, that is, ||T wz (s)|| ∞ <γ.

[0081] It can be understood that the aforementioned embodiment constructs the state-space equation of the open-loop system of the vehicle, and introducing the standard robust controller model into the open-loop system is actually introducing an external control effect into the open-loop system, thereby converting the original open-loop system into a closed-loop system. Therefore, the state-space equation of the closed-loop system can be obtained accordingly, so that the closed-loop system can maintain its stability when facing various uncertainties or disturbances.

[0082] In the embodiment of the present application, the standard robust controller is u=Kx, where K is a matrix of 2 rows and 6 columns, that is, the state feedback matrix of the standard robust controller model. Then, the state feedback matrix K is substituted into the state space equation ∑3 to obtain the state space equation ∑4 of the closed-loop system, as shown in the following equation (10):

[0083]

[0084] The state space equations of the open-loop system are the same as above. C1 and C2 are unit matrices with 6 rows and 6 columns. D 11 , D 12 , D 21 , D 22 is a zero matrix with 6 rows and 1 column. e1 is the lateral error, is the lateral error change rate, e2 is the heading error, is the heading error change rate, e3 is the position error, and e4 is the speed error.

[0085] Furthermore, by performing Laplace transform on the state space equation ∑4 of the closed-loop system, the corresponding closed-loop transfer function, T wz =(C1+D 11 K)[sI-(A+BK)] -1 B+D 12 . T wz The H∞ norm index of (s) is ||T wz (s)|| ∞ <γ, γ is a constant given by the technician.

[0086] On this basis, the target robust controller model can be constructed according to the closed-loop transfer function corresponding to the determined state space equation of the closed-loop system.

[0087] Specifically, a convex optimization inequality can be constructed according to the state space equation of the closed-loop system and the performance index of the closed-loop transfer function, and a target robust controller model can be constructed based on the solution of the convex optimization inequality.

[0088] It is understandable that the closed-loop transfer function describes the relationship between the output and input of the control system. By adjusting the parameters of the closed-loop transfer function, the performance indicators of the system can be optimized. However, the parameter adjustment problem of the closed-loop transfer function is usually a nonlinear optimization problem, which is difficult to solve. Therefore, by converting the closed-loop transfer function parameter adjustment problem into a convex optimization problem, the excellent properties of convex optimization can be used to quickly find the optimal solution.

[0089] Furthermore, based on the state space equation ∑4 of the closed-loop system, the performance index γ, and the necessary and sufficient conditions for the robust H∞ control problem to be solvable, the linear matrix inequality shown in equation (11) can be obtained:

[0090]

[0091] Among them, X is an unknown symmetric positive definite matrix, W is an unknown matrix, and γ is a performance indicator.

[0092] It should be noted that for the performance index γ, its minimum value is generally sought. Therefore, the above robust H∞ control problem can be transformed into the following optimization problem, that is, constructing the original linear matrix shown in equation (12):

[0093]

[0094] The contents are the same as those in the above embodiment, A is the state transfer matrix, B is the control matrix, C1 and C2 are unit matrices with 6 rows and 6 columns, and D 11 , D 12 , D21 , D 22 is a zero matrix with 6 rows and 1 column.

[0095] After that, the interior point penalty function method is used to continue solving the above inequality to obtain the symmetric positive definite matrix X, matrix W, and performance index γ as the solution of the convex optimization inequality, and then the target robust controller is obtained, as shown in the following equation (13):

[0096] u=Kx=WX -1 x (13)

[0097] in, e1 is the lateral error, is the lateral error change rate, e2 is the heading error, is the heading error change rate, e3 is the position error, and e4 is the speed error. u=[δ,α] T , δ is the steering wheel angle, α is the acceleration, which is the analog signal output by the controller.

[0098] Step 104 : Control the vehicle in the lateral and longitudinal directions based on the target robust controller model.

[0099] In one embodiment, the lateral control of the automatic driving refers to the automatic adjustment of the steering wheel angle during the driving process of the vehicle, and the longitudinal control refers to the automatic control of the driving and braking of the vehicle during the driving process to keep the vehicle stable in the lane. In this embodiment, the vehicle can be controlled in the lateral and longitudinal directions according to the output of the target robust controller model, which is specifically reflected in the control of the steering wheel angle and acceleration.

[0100] Specifically, the target robust controller model can output an analog signal of the steering wheel angle and an analog signal of the acceleration when the state error x is taken as input. Afterwards, the analog signal of the steering wheel angle and the analog signal of the acceleration output by the target robust controller model can be quantized by the quantizer provided in the above-mentioned embodiment of the present application to obtain the quantized steering wheel angle and the quantized acceleration. The quantization processing here is the aforementioned process of converting the analog signal into a piecewise constant signal of a finite number set, so the quantized steering wheel angle and the quantized acceleration are both digital signals. Thereafter, the quantized steering wheel angle and the quantized acceleration can be transmitted to the execution module of the vehicle, such as the chassis module, so that the execution module adjusts the working state according to the obtained digital signal, so that the vehicle responds according to the expected operation.

[0101] It can be seen from the above embodiments that the quantization error of the quantizer provided in the present application is regarded as a bounded disturbance, and then a target robust controller is constructed, which makes the controller design process simpler and more efficient, thereby reducing the difficulty of controller design while ensuring the control accuracy of the vehicle.

[0102] Figure 5 is a schematic structural diagram of a device provided by an exemplary embodiment. Figure 5 At the hardware level, the electronic device includes a processor 502, an internal bus 504, a network interface 506, a memory 508, and a non-volatile memory 510, and may also include hardware required for other services. The processor 502 reads the corresponding computer program from the non-volatile memory 510 into the memory 508 and then runs it, forming a health monitoring device at the logical level. Of course, in addition to software implementations, this application does not exclude other implementations, such as logic devices or a combination of software and hardware, etc., that is, the execution subject of the following processing flow is not limited to each logic unit, but can also be hardware or logic devices.

[0103] Corresponding to the above method embodiments, the present application also provides device embodiments. Figure 6 The vehicle control device can be applied to Figure 6 The control device of the vehicle may include an acquisition unit 61, an error determination unit 62, a controller construction unit 63 and a transverse and longitudinal control unit 64, wherein:

[0104] An acquisition unit 61 is used to acquire structural parameters and motion parameters of the vehicle and a digital signal output by a quantizer; and construct a state space equation of an open-loop system of the vehicle based on the structural parameters, the motion parameters and the digital signal;

[0105] an error determination unit 62, configured to calculate a quantization error of the quantizer according to the digital signal, wherein the quantization error is a bounded value;

[0106] A controller construction unit 63 uses the quantization error as a bounded disturbance of a target robust controller model to be constructed, constructs a state space equation of a closed-loop system of the vehicle based on a standard robust controller model and a state space equation of the open-loop system, determines a closed-loop transfer function corresponding to the state space equation of the closed-loop system, and constructs the target robust controller model;

[0107] The lateral and longitudinal control unit 64 is used to perform lateral and longitudinal control on the vehicle based on the target robust controller model.

[0108] Optionally, the horizontal and vertical control unit 64 is specifically used for:

[0109] Inputting the state error of the vehicle into the target robust controller model, and obtaining the steering wheel angle and acceleration of the vehicle output by the model;

[0110] Quantizing the steering wheel angle and acceleration by the quantizer to obtain a quantized steering wheel angle and a quantized acceleration;

[0111] The vehicle is controlled in the lateral and longitudinal directions based on the quantified steering wheel angle and the quantified acceleration.

[0112] Optionally, the quantizer includes a first quantization unit and a second quantization unit, and the quantizer performs quantization processing on any one of the steering wheel angle and the acceleration signal to obtain a corresponding quantized signal, including:

[0113] When the amplitude of any signal is greater than the demarcation threshold, quantizing the signal based on the first quantization unit;

[0114] When the amplitude of any signal is not greater than the demarcation threshold, the signal is quantized based on the second quantization unit.

[0115] Optionally, the first quantization unit is constructed based on a uniform quantizer and an adjustment parameter, and the adjustment parameter is used to maintain the continuity of the quantized digital signal when the amplitude of the analog signal is equal to the demarcation threshold;

[0116] The second quantization unit includes a hysteresis quantizer.

[0117] Optionally, the controller construction unit 63 is specifically used for:

[0118] Obtaining a state feedback matrix of the standard robust controller model;

[0119] The state feedback matrix is ​​substituted into the state space equation of the open loop system to construct the state space equation of the closed loop system of the vehicle.

[0120] Optionally, the controller construction unit 63 is specifically used for:

[0121] Constructing a convex optimization inequality according to the state space equation of the closed-loop system and the performance index of the closed-loop transfer function;

[0122] Based on the solution of the convex optimization inequality, the target robust controller model is constructed.

[0123] Optionally, the solution of the convex optimization inequality is obtained by: solving the convex optimization inequality according to an interior point penalty function method.

[0124] Optional,

[0125] The structural parameters include: vehicle mass, front overhang length, rear overhang length, moment of inertia about the axis, front wheel cornering stiffness, and rear wheel cornering stiffness;

[0126] The motion parameters include: speed, position and heading angle;

[0127] The state error includes: lateral error, lateral error change rate, heading error, heading error change rate, position error and speed error.

[0128] The implementation process of the functions and effects of each unit in the above-mentioned device is specifically described in the implementation process of the corresponding steps in the above-mentioned method, and will not be repeated here.

[0129] For the device embodiment, since it basically corresponds to the method embodiment, the relevant parts can refer to the partial description of the method embodiment. The device embodiment described above is only schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present application scheme. A person of ordinary skill in the art can understand and implement it without paying any creative work.

[0130] Correspondingly, the present application also provides a computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, the operation control method of the vehicle-mounted functional module described in any of the above embodiments is implemented.

[0131] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer, which may be in the form of a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email transceiver, a game console, a tablet computer, a wearable device or a combination of any of these devices.

[0132] In a typical configuration, a computer includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0133] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0134] Computer-readable media include permanent and non-permanent, removable and non-removable media that can be used to store information by any method or technology. Information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, disk storage, quantum memory, graphene-based storage media or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include temporary computer-readable media (transitory media), such as modulated data signals and carrier waves.

Claims

1. A vehicle control method, characterized in that: include: Acquire structural parameters and motion parameters of the vehicle and a digital signal output by a quantizer, and construct a state space equation of an open-loop system of the vehicle based on the structural parameters, the motion parameters and the digital signal; Calculating a quantization error of the quantizer according to the digital signal, wherein the quantization error is a bounded value; Taking the quantization error as a bounded disturbance of a target robust controller model to be constructed, constructing a state space equation of a closed loop system of the vehicle based on a standard robust controller model and a state space equation of the open loop system, and determining a closed loop transfer function corresponding to the state space equation of the closed loop system, and constructing the target robust controller model; The vehicle is controlled in the lateral and longitudinal directions based on the target robust controller model.

2. The method according to claim 1, characterized in that The performing lateral and longitudinal control of the vehicle based on the target robust controller model includes: Inputting the state error of the vehicle into the target robust controller model, and obtaining the steering wheel angle and acceleration of the vehicle output by the model; Quantizing the steering wheel angle and acceleration by the quantizer to obtain a quantized steering wheel angle and a quantized acceleration; The vehicle is controlled in the lateral and longitudinal directions based on the quantified steering wheel angle and the quantified acceleration.

3. The method according to claim 2, characterized in that The quantizer includes a first quantization unit and a second quantization unit. The quantizer performs quantization processing on any one of the steering wheel angle and the acceleration signal to obtain a corresponding quantized signal, including: When the amplitude of any signal is greater than the demarcation threshold, quantizing the signal based on the first quantization unit; When the amplitude of any signal is not greater than the demarcation threshold, the signal is quantized based on the second quantization unit.

4. The method according to claim 3, characterized in that The first quantization unit is constructed based on a uniform quantizer and an adjustment parameter, wherein the adjustment parameter is used to maintain the continuity of the quantized digital signal when the amplitude of the analog signal is equal to the demarcation threshold; The second quantization unit includes a hysteresis quantizer.

5. The method according to claim 1, characterized in that The constructing the state space equation of the closed loop system of the vehicle based on the standard robust controller model and the state space equation of the open loop system comprises: Obtaining a state feedback matrix of the standard robust controller model; The state feedback matrix is ​​substituted into the state space equation of the open loop system to construct the state space equation of the closed loop system of the vehicle.

6. The method according to claim 1, characterized in that The constructing of the target robust controller model comprises: Constructing a convex optimization inequality according to the state space equation of the closed-loop system and the performance index of the closed-loop transfer function; Based on the solution of the convex optimization inequality, the target robust controller model is constructed.

7. The method according to claim 6, characterized in that The solution of the convex optimization inequality is obtained by the following method: solving the convex optimization inequality according to the interior point penalty function method.

8. The method according to claim 1, characterized in that The structural parameters include: vehicle mass, front overhang length, rear overhang length, moment of inertia about the axis, front wheel cornering stiffness, and rear wheel cornering stiffness; The motion parameters include: speed, position and heading angle; The state error includes: lateral error, lateral error change rate, heading error, heading error change rate, position error and speed error.

9. A vehicle control device, characterized in that: The device comprises: An acquisition unit, used for acquiring structural parameters and motion parameters of the vehicle and a digital signal output by a quantizer; constructing a state space equation of an open-loop system of the vehicle based on the structural parameters, the motion parameters and the digital signal; an error determination unit, configured to calculate a quantization error of the quantizer according to the digital signal, wherein the quantization error is a bounded value; A controller construction unit, taking the quantization error as a bounded disturbance of a target robust controller model to be constructed, constructing a state space equation of a closed loop system of the vehicle based on a standard robust controller model and a state space equation of the open loop system, and determining a closed loop transfer function corresponding to the state space equation of the closed loop system, and constructing the target robust controller model; A lateral and longitudinal control unit is used to perform lateral and longitudinal control on the vehicle based on the target robust controller model.

10. An electronic device, characterized in that: The invention comprises a memory, a processor and executable instructions stored in the memory and executable to be executed on the processor, wherein the processor implements the method according to any one of claims 1 to 8 by executing the executable instructions.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-readable instructions, and when the computer-readable instructions are called and executed by the processor, the method according to any one of claims 1 to 8 is implemented.

12. A computer program product, characterized in that The method comprises a computer program / instruction, which, when executed by a processor, implements the steps of the method according to any one of claims 1 to 8.

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