Control quantity determination method and device, equipment and storage medium

Abstract

This invention discloses a method, apparatus, device, and storage medium for determining control quantities. The process involves acquiring vehicle data of the target vehicle and the true natural frequency of the actual steering system; assuming the true natural frequency and the ideal natural frequency are the same, based on the vehicle data and the algorithm output of a preset steering control algorithm, calculating the initial adaptive coefficients of the input control quantity of the actual steering system using Lyapunov functions, an ideal response model, and a true response model. These initial adaptive coefficients include a first parameter value; determining whether the true natural frequency has been successfully acquired; if so, determining the second parameter value corresponding to the target adaptive parameter based on the difference between the true and ideal natural frequencies, and replacing the first parameter value with the second parameter value to obtain the target adaptive coefficients; and determining the target input control quantity of the actual steering system based on the target adaptive coefficients. This method simplifies the calculation process while effectively improving the accuracy of control quantity calculation.

Description

Technical Field

[0001] This invention relates to the field of autonomous driving technology, and in particular to a method, apparatus, device, and storage medium for determining control quantities. Background Technology

[0002] With the development of autonomous driving technology, some control algorithms have begun to be used in vehicles, such as linear quadratic regulators and model predictive control algorithms, and the input control quantities of the control system are determined based on the output of the control algorithm.

[0003] However, existing methods for determining control quantities suffer from problems such as cumbersome calculations and inaccurate calculations. Summary of the Invention

[0004] This invention provides a method, apparatus, device, and storage medium for determining control quantities, in order to solve the problems of cumbersome calculations and inaccurate calculations in existing methods for determining control quantities.

[0005] According to one aspect of the present invention, a method for determining a control quantity is provided, characterized in that it includes:

[0006] Acquire vehicle data of the target vehicle and attempt to obtain the true natural frequency of the target vehicle's actual steering system;

[0007] Assuming that the real natural frequency and the ideal natural frequency of the preset ideal steering system corresponding to the target vehicle are the same, the algorithm output control quantity based on vehicle data and preset steering control algorithm is used to calculate the initial adaptive coefficient of the input control quantity of the real steering system using Lyapunov function, ideal response model of preset ideal steering system and real response model of real steering system. The initial adaptive coefficient includes the first parameter value of target adaptive parameter.

[0008] Determine whether the true intrinsic frequency has been successfully acquired;

[0009] If the value has been successfully obtained, the second parameter value corresponding to the target adaptive parameter is determined based on the difference between the true natural frequency and the ideal natural frequency, and the first parameter value in the target adaptive parameter is replaced with the second parameter value to obtain the target adaptive coefficient.

[0010] The target input control quantity of the real steering system is determined based on the target adaptive coefficient.

[0011] According to another aspect of the present invention, a control quantity determining device is provided, characterized in that it comprises:

[0012] The data acquisition module is used to acquire vehicle data of the target vehicle and attempt to acquire the true natural frequency of the actual steering system corresponding to the target vehicle.

[0013] The initial coefficient calculation module is used to calculate the initial adaptive coefficients of the input control quantity of the real steering system based on vehicle data and the algorithm output control quantity of the preset ideal steering system, assuming that the real natural frequency and the preset ideal steering system corresponding to the target vehicle are the same. The module uses Lyapunov function, the ideal response model of the preset ideal steering system and the real response model of the real steering system to calculate the initial adaptive coefficients of the input control quantity of the real steering system. The initial adaptive coefficients include the first parameter value of the target adaptive parameter.

[0014] The frequency determination module is used to determine whether the actual inherent frequency has been successfully acquired.

[0015] The target coefficient determination module is used to determine the second parameter value corresponding to the target adaptive parameter based on the difference between the true natural frequency and the ideal natural frequency if the target has been successfully obtained, and replace the first parameter value in the target adaptive parameter with the second parameter value to obtain the target adaptive coefficient.

[0016] The control quantity determination module is used to determine the target input control quantity of the actual steering system based on the target adaptive coefficient.

[0017] According to another aspect of the present invention, a control quantity determination device is provided, the control quantity determination device comprising:

[0018] At least one processor; and

[0019] A memory that is communicatively connected to at least one processor; wherein,

[0020] The memory stores a computer program that can be executed by at least one processor, such that the at least one processor is able to perform the control quantity determination method of any embodiment of the present invention.

[0021] According to another aspect of the present invention, a computer-readable storage medium is provided, which stores computer instructions for causing a processor to execute and implement the control quantity determination method of any embodiment of the present invention.

[0022] The technical solution provided by this invention involves acquiring vehicle data of a target vehicle and attempting to acquire the true natural frequency of the target vehicle's actual steering system. Assuming the true natural frequency is the same as the ideal natural frequency of a preset ideal steering system corresponding to the target vehicle, based on the vehicle data and the algorithm output control quantity of a preset steering control algorithm, and utilizing a Lyapunov function, the ideal response model of the preset ideal steering system, and the true response model of the actual steering system, the initial adaptive coefficients of the input control quantity of the actual steering system are calculated. These initial adaptive coefficients include the first parameter value of the target adaptive parameter. The system then determines whether the true natural frequency has been successfully acquired. If successfully acquired, the second parameter value corresponding to the target adaptive parameter is determined based on the difference between the true natural frequency and the ideal natural frequency, and the first parameter value in the target adaptive parameter is replaced with the second parameter value to obtain the target adaptive coefficients. Finally, the target input control quantity of the actual steering system is determined based on these target adaptive coefficients. The above technical solution, assuming the true natural frequency and the ideal natural frequency of the target vehicle's corresponding preset ideal steering system are the same, calculates the initial adaptive coefficient of the input control quantity of the true steering system. The initial adaptive coefficient includes the first parameter value of the target adaptive parameter. Then, when the true natural frequency is successfully obtained, the second parameter value corresponding to the target adaptive parameter is determined based on the difference between the true natural frequency and the ideal natural frequency. The first parameter value is then replaced with the second parameter value to obtain the target adaptive coefficient. Compared to the initial adaptive coefficient, the obtained target adaptive coefficient better reflects the actual vehicle situation. Therefore, based on the target adaptive coefficient, the target input control quantity of the true steering system can be determined. This solves the problems of cumbersome calculations and inaccurate control quantity calculations in existing control quantity determination methods, achieving the beneficial effect of simplifying the calculation process while effectively improving the accuracy of control quantity calculation.

[0023] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0024] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 This is a flowchart of a control quantity determination method provided in Embodiment 1 of the present invention;

[0026] Figure 2 This is a flowchart of a control quantity determination method provided in Embodiment 2 of the present invention;

[0027] Figure 3 This is a schematic diagram of a control quantity determination device provided in Embodiment 3 of the present invention;

[0028] Figure 4 This is a schematic diagram of a control quantity determination device provided in Embodiment 4 of the present invention. Detailed Implementation

[0029] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0030] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0031] Example 1

[0032] Figure 1 This is a flowchart of a control quantity determination method provided in Embodiment 1 of the present invention. This embodiment is applicable to determining the control quantity of the steering system in an autonomous vehicle. The method can be executed by a control quantity determination device, which can be implemented in hardware and / or software and can be configured in a control quantity determination equipment. Figure 1 As shown, the method includes:

[0033] S101. Obtain vehicle data of the target vehicle and attempt to obtain the true natural frequency of the actual steering system corresponding to the target vehicle.

[0034] In this embodiment, the target vehicle includes a currently operating autonomous vehicle. Vehicle data may include steering wheel angle, steering wheel angle rate, and vehicle speed. The real steering system can be understood as the power transmission system from the steering wheel to the wheels in the target vehicle. The real natural frequency includes the natural frequency of the steering column and steering wheel of the target vehicle.

[0035] Specifically, in order to effectively control the target vehicle, vehicle data during the driving process is obtained, and an attempt is made to obtain the true natural frequency of the target vehicle's actual steering system.

[0036] S102. Assuming that the real natural frequency and the ideal natural frequency of the preset ideal steering system corresponding to the target vehicle are the same, based on the vehicle data and the algorithm output control quantity of the preset steering control algorithm, the initial adaptive coefficients of the input control quantity of the real steering system are calculated using the Lyapunov function, the ideal response model of the preset ideal steering system and the real response model of the real steering system. The initial adaptive coefficients include the first parameter value of the target adaptive parameter.

[0037] In this embodiment, the preset ideal steering system includes a pre-constructed ideal steering system. The ideal natural frequency includes a natural frequency set based on the ideal steering system. The preset steering control algorithm can control the normal driving of the target vehicle based on relevant steering wheel data; for example, this algorithm can be a linear quadratic regulator (LQR) or a model predictive control (MPC) algorithm. The algorithm output control quantity includes the vehicle control command output by the preset steering control algorithm. The Lyapunov function is used to study the stability of the control system. The ideal response model includes an algorithm model constructed based on the ideal steering system. The real response model includes an algorithm model constructed based on the real steering system. Initial adaptive coefficients are used to determine the input control quantity of the real steering system, wherein the initial adaptive coefficients include the first parameter value of the target adaptive parameter.

[0038] Specifically, in attempting to obtain the true natural frequency of the target vehicle's steering system, it is initially assumed that the true natural frequency is the same as the ideal natural frequency of the target vehicle's preset ideal steering system. Then, the steering wheel angle, steering wheel angular ratio, and the algorithm output control quantity of the preset steering control algorithm from the vehicle data are input into the true response model of the true steering system, and an error dynamic expression is defined. Based on this expression, a Lyapunov function is then defined. To stabilize the control system, the derivative of the Lyapunov function is set to be less than or equal to zero, allowing the derivation of the initial adaptive coefficients of the input control quantity of the true steering system. These initial adaptive coefficients include the first parameter value of the target adaptive parameter, which can be understood as an adaptive parameter related to the true natural frequency. In addition to the first parameter value of the target adaptive parameter, the initial adaptive coefficients also include the parameter value of the preset adaptive parameter, which differs from the target adaptive parameter and can be understood as an adaptive parameter unrelated to the true natural frequency. By assuming that the true natural frequency and the ideal natural frequency are the same, and prioritizing the calculation of the parameter values ​​of each adaptive parameter in the initial adaptive coefficients, the calculation efficiency of the adaptive coefficients can be improved.

[0039] S103. Determine whether the true inherent frequency has been successfully acquired.

[0040] Specifically, it determines in real time whether the true inherent frequency of the steering system corresponding to the target vehicle has been successfully obtained.

[0041] S104. If the value has been successfully obtained, determine the second parameter value corresponding to the target adaptive parameter based on the difference between the true natural frequency and the ideal natural frequency, and replace the first parameter value in the target adaptive parameter with the second parameter value to obtain the target adaptive coefficient.

[0042] In this embodiment, the second parameter value is used to calculate the target adaptive coefficient. The target adaptive coefficient is used to calculate the input control quantity of the control system. The target adaptive coefficient may include the input coefficient of the current state quantity in the actual steering system and the input coefficient of the control quantity in the actual steering system. The state quantity includes the steering wheel angle and steering wheel angle rate of the target vehicle.

[0043] Specifically, if the true natural frequency can be successfully obtained, considering that there may be a certain error between the true natural frequency and the ideal natural frequency of the target vehicle in the actual application scenario, and the target adaptive parameter is affected by the error between the two, the difference between the true natural frequency and the ideal natural frequency is calculated, and the second parameter value corresponding to the target adaptive parameter is determined by using this difference. The first parameter value in the target adaptive parameter is replaced with the second parameter value to obtain the target adaptive coefficient, thereby reducing the impact of error on the target adaptive coefficient.

[0044] S105. Determine the target input control quantity of the real steering system based on the target adaptive coefficient.

[0045] Specifically, the target output of the real steering system can be directly determined through the target adaptive coefficient.

[0046] The technical solution provided in Embodiment 1 of this invention involves acquiring vehicle data of a target vehicle and attempting to acquire the true natural frequency of the actual steering system corresponding to the target vehicle. Assuming the true natural frequency is the same as the ideal natural frequency of a preset ideal steering system corresponding to the target vehicle, based on the vehicle data and the algorithm output control quantity of a preset steering control algorithm, and utilizing the Lyapunov function, the ideal response model of the preset ideal steering system, and the true response model of the actual steering system, the initial adaptive coefficients of the input control quantity of the actual steering system are calculated. These initial adaptive coefficients include the first parameter value of the target adaptive parameter. The system then determines whether the true natural frequency has been successfully acquired. If successfully acquired, the second parameter value corresponding to the target adaptive parameter is determined based on the difference between the true natural frequency and the ideal natural frequency, and the first parameter value in the target adaptive parameter is replaced with the second parameter value to obtain the target adaptive coefficients. Finally, the target input control quantity of the actual steering system is determined based on the target adaptive coefficients. The above technical solution, assuming the true natural frequency and the ideal natural frequency of the target vehicle's corresponding preset ideal steering system are the same, calculates the initial adaptive coefficient of the input control quantity of the true steering system. The initial adaptive coefficient includes the first parameter value of the target adaptive parameter. Then, when the true natural frequency is successfully obtained, the second parameter value corresponding to the target adaptive parameter is determined based on the difference between the true natural frequency and the ideal natural frequency. The first parameter value is then replaced with the second parameter value to obtain the target adaptive coefficient. Compared to the initial adaptive coefficient, the obtained target adaptive coefficient better reflects the actual vehicle situation. Therefore, based on the target adaptive coefficient, the target input control quantity of the true steering system can be determined. This solves the problems of cumbersome calculations and inaccurate control quantity calculations in existing control quantity determination methods, achieving the beneficial effect of simplifying the calculation process while effectively improving the accuracy of control quantity calculation.

[0047] In some embodiments, determining the second parameter value corresponding to the target adaptive parameter based on the difference between the true natural frequency and the ideal natural frequency includes: searching a first target value corresponding to the difference between the true natural frequency and the ideal natural frequency in a first preset lookup table, and determining the first target value as the second parameter value corresponding to the target adaptive parameter. This technical solution effectively improves the efficiency of determining the second parameter value, further enhancing the efficiency of the control quantity determination method.

[0048] In this embodiment, the first target value is used to determine the second parameter value corresponding to the target adaptive parameter. The first preset lookup table is a pre-constructed lookup table, and the contents of the table may include the correspondence between different differences between the true natural frequency and the ideal natural frequency determined based on experience and different first values. The first value is used to indicate the value of the preset target adaptive parameter when the difference between the true natural frequency and the ideal natural frequency is the corresponding difference.

[0049] Specifically, after calculating the difference between the true natural frequency and the ideal natural frequency, the corresponding difference is searched from a pre-built first preset lookup table based on the difference, and then the first value associated with the corresponding difference is used as the first target value, and the first target value is determined as the second parameter value corresponding to the target adaptive parameter.

[0050] Optionally, when searching for a corresponding difference in a pre-built first preset lookup table based on the difference between the true natural frequency and the ideal natural frequency, if no corresponding difference is found in the first preset lookup table, the value closest to the difference between the true natural frequency and the ideal natural frequency is determined as its corresponding difference. This embodiment does not limit the specific method for searching for the corresponding difference in the pre-built first preset lookup table based on the difference between the true natural frequency and the ideal natural frequency.

[0051] In some embodiments, the true natural frequency of the actual steering system corresponding to the target vehicle is obtained by fitting vehicle data using the recursive least squares method. This technical solution effectively reduces computational load and improves the efficiency of obtaining the true natural frequency, further enhancing the efficiency of the control quantity determination method.

[0052] In this embodiment, the recursive least squares method is an algorithm based on the least squares criterion, characterized by its fast convergence speed.

[0053] Specifically, the true natural frequency of the steering system corresponding to the target vehicle can be obtained by real-time identification of the control system. Furthermore, to reduce computational load and improve efficiency, real-time identification of the control system can be achieved by fitting vehicle data using the recursive least squares method, thereby obtaining the true natural frequency of the steering system corresponding to the target vehicle.

[0054] In some embodiments, the control quantity determination method further includes: inputting a target input control quantity into the actual steering system to perform steering control on the target vehicle. Through the above technical solution, steering control of the target vehicle is achieved.

[0055] Specifically, after the target input control quantity is input into the real steering system, the real steering system performs steering control on the target vehicle based on the target input control quantity.

[0056] Example 2

[0057] Figure 2 This is a flowchart of a control quantity determination method provided in Embodiment 2 of the present invention. This embodiment optimizes and extends the above-mentioned optional embodiments. This embodiment describes in detail how to determine the target adaptive coefficient after the true natural frequency is successfully obtained, and details how to determine the target input control quantity based on the target adaptive coefficient. Figure 2 As shown, the method includes:

[0058] S201. Obtain vehicle data of the target vehicle and attempt to obtain the true natural frequency of the actual steering system corresponding to the target vehicle.

[0059] S202. Assuming that the real natural frequency and the ideal natural frequency of the preset ideal steering system corresponding to the target vehicle are the same, based on the vehicle data and the algorithm output control quantity of the preset steering control algorithm, the initial adaptive coefficients of the input control quantity of the real steering system are calculated using the Lyapunov function, the ideal response model of the preset ideal steering system and the real response model of the real steering system. The initial adaptive coefficients include the first parameter value of the target adaptive parameter.

[0060] For example, an ideal response model for a pre-defined ideal steering system is established:

[0061]

[0062] in,

[0063] x m Let δ be a state variable. m Indicates the steering wheel angle. The steering wheel angle is the ratio of the steering wheel angle, command is the output control value of the control algorithm, and w m Set to 10, ξ m Set it to 0.9.

[0064] Assuming the true natural frequency is the same as the ideal natural frequency of the preset ideal steering system corresponding to the target vehicle, the true response model of the true steering system is:

[0065]

[0066] in,

[0067] Assume the calculation equations corresponding to the input control quantities of the controller in a real steering system are defined as follows:

[0068]

[0069] Where u represents the input control quantity. and All of these are coefficients of the equation.

[0070] Define the error variable as: e = x p -x m (4)

[0071] The error dynamic expression can then be determined as:

[0072]

[0073] in, θ *T x and θ *T r These are all coefficients in the calculation equation corresponding to the input control quantity of the controller of the preset ideal steering system.

[0074] Suppose the Lyapunov function is:

[0075]

[0076] For the system to be stable, the derivative of the Lyapunov function should be less than or equal to 0, so the initial adaptive coefficients can be derived.

[0077]

[0078]

[0079] in, All are target adaptive coefficients, γ x For the target adaptive parameters,

[0080] S203. Determine whether the true intrinsic frequency has been successfully acquired. If it has been successfully acquired, proceed to S204-S206; if it has not been successfully acquired, proceed to S207.

[0081] S204. Search for the second target value corresponding to the difference between the true natural frequency and the ideal natural frequency in the second preset lookup table.

[0082] In this embodiment, the second target value is used to determine the second parameter value corresponding to the target adaptive parameter, and the second target value is different from the first target value. The second preset lookup table is pre-constructed, and the contents of the table include the correspondence between different differences between the true natural frequency and the ideal natural frequency determined based on experience and different second values. The second value is used to represent the deviation value of the preset target adaptive parameter when the difference between the true natural frequency and the ideal natural frequency is the corresponding difference value.

[0083] Specifically, after successfully acquiring the true natural frequency, the difference between the true natural frequency and the ideal natural frequency is calculated. Based on this difference, a corresponding difference is searched in a pre-constructed second preset lookup table, and the associated second value is obtained as the second target value. Optionally, when searching for a corresponding difference in the pre-constructed second preset lookup table based on the difference between the true and ideal natural frequencies, if no corresponding difference is found in the second preset lookup table, the value closest to the difference between the true and ideal natural frequencies is determined as its corresponding difference. This embodiment does not limit the specific method for searching for the corresponding difference in the pre-constructed second preset lookup table based on the difference between the true and ideal natural frequencies.

[0084] S205. Determine the second parameter value corresponding to the target adaptive parameter based on the sum of the second target value and the first parameter value.

[0085] Specifically, in order to reduce the impact of error on the target adaptive coefficient, it is necessary to calculate the sum of the second target value and the first parameter value, and use this sum as the second parameter value corresponding to the target adaptive parameter to correct the first parameter value.

[0086] S206. Replace the first parameter value in the target adaptive parameters with the second parameter value to obtain the target adaptive coefficient, and then execute S208.

[0087] S207. Determine the initial adaptive coefficients as the target adaptive coefficients.

[0088] Specifically, when it is determined that the true natural frequency has not been successfully acquired, the initial adaptive coefficient is set as the target adaptive coefficient, thereby quickly determining the target input control quantity and avoiding delays in steering control caused by waiting for the true natural frequency to be acquired.

[0089] S208. Integrate the target adaptive coefficients to obtain the integral adaptive coefficients.

[0090] Specifically, in order to calculate the effective target output control quantity, the target adaptive coefficient is integrated to obtain the integral adaptive coefficient. For example, the obtained target adaptive coefficient... and By integrating, we can obtain the corresponding integral and fitness coefficient. and

[0091]

[0092] S209. Determine the adaptive coefficients using the integral adaptive coefficients and the coefficients of the preset ideal steering system.

[0093] Specifically, the adaptive coefficient is obtained by adding the coefficient of the preset ideal steering system to the obtained integral adaptive coefficient. The calculation is as follows:

[0094]

[0095]

[0096] S210. Using adaptive coefficients, determine the target input control quantity of the actual steering system.

[0097] Specifically, by inputting the adaptive coefficient into the calculation formula of the target input control quantity, that is, by substituting it into the calculation formula (3), the target input control quantity can be determined.

[0098] The technical solution provided in Embodiment 2 of this invention involves, when the true natural frequency is successfully acquired, searching a second target value corresponding to the difference between the true natural frequency and the ideal natural frequency in a second preset lookup table. Based on the sum of the second target value and the first parameter value, a second parameter value corresponding to the target adaptive parameter is determined. The first parameter value in the target adaptive parameter is then replaced with the second parameter value to obtain the target adaptive coefficient. When the true natural frequency is not successfully acquired, the initial adaptive coefficient is determined as the target adaptive coefficient. The target adaptive coefficient is then integrated to obtain the integral adaptive coefficient. Using the integral adaptive coefficient and the coefficient of the preset ideal steering system, the adaptive coefficient is determined. Finally, the target input control quantity of the true steering system is determined using the adaptive coefficient. This method corrects the first parameter and determines the target adaptive coefficient, effectively improving the accuracy of the target adaptive coefficient and further enhancing the accuracy of the control quantity determination method. It also considers both successful and unsuccessful acquisition of the true natural frequency, effectively enhancing the adaptability of the method.

[0099] Example 3

[0100] Figure 3 This is a schematic diagram of a control quantity determination device provided in Embodiment 3 of the present invention. Figure 3 As shown, the device includes a data acquisition module 31, an initial coefficient calculation module 32, a frequency judgment module 33, a target coefficient determination module 34, and a control quantity determination module 35.

[0101] The system includes the following modules: a data acquisition module 31, used to acquire vehicle data of the target vehicle and attempt to acquire the true natural frequency of the actual steering system corresponding to the target vehicle; an initial coefficient calculation module 32, used to calculate the initial adaptive coefficients of the input control quantity of the actual steering system based on the vehicle data and the algorithm output control quantity of the preset steering control algorithm, using the Lyapunov function, the ideal response model of the preset ideal steering system, and the true response model of the actual steering system, assuming that the true natural frequency and the preset ideal steering system are the same; a frequency judgment module 33, used to determine whether the true natural frequency has been successfully acquired; a target coefficient determination module 34, used to determine the second parameter value corresponding to the target adaptive parameter based on the difference between the true natural frequency and the ideal natural frequency if the frequency has been successfully acquired, and to replace the first parameter value in the target adaptive parameter with the second parameter value to obtain the target adaptive coefficient; and a control quantity determination module 35, used to determine the target input control quantity of the actual steering system based on the target adaptive coefficient.

[0102] The technical solution provided in Embodiment 3 of the present invention solves the problems of cumbersome calculation and inaccurate calculation of control quantities in existing methods for determining control quantities, and achieves the beneficial effect of simplifying the calculation process while effectively improving the accuracy of control quantity calculation.

[0103] Optionally, based on the difference between the true natural frequency and the ideal natural frequency, the second parameter value corresponding to the target adaptive parameter is determined, including:

[0104] The first target value corresponding to the difference between the true natural frequency and the ideal natural frequency is found in the first preset lookup table, and the first target value is determined as the second parameter value corresponding to the target adaptive parameter.

[0105] Optionally, based on the difference between the true natural frequency and the ideal natural frequency, the second parameter value corresponding to the target adaptive parameter is determined, including:

[0106] The second target value corresponding to the difference between the true natural frequency and the ideal natural frequency is found in the second preset lookup table;

[0107] The second parameter value corresponding to the target adaptive parameter is determined based on the sum of the second target value and the first parameter value.

[0108] Optionally, the true natural frequency of the actual steering system corresponding to the target vehicle is obtained in the following way:

[0109] By fitting vehicle data using the recursive least squares method, the true natural frequencies of the actual steering system corresponding to the target vehicle are obtained.

[0110] Optionally, the control quantity determination device also includes a frequency not acquired module, which is used to determine the initial adaptive coefficient as the target adaptive coefficient if it is not successfully acquired.

[0111] Optionally, the control quantity determination module 35 includes:

[0112] The first coefficient determination unit is used to integrate the target adaptive coefficients to obtain the integral adaptive coefficients.

[0113] The second coefficient determination unit is used to determine the adaptive coefficients using the integral adaptive coefficients and the coefficients of the preset ideal steering system.

[0114] The control quantity determination unit is used to determine the target input control quantity of the actual steering system using adaptive coefficients.

[0115] Optionally, the control quantity determining device further includes:

[0116] The control input module is used to input the target input control quantity into the actual steering system to control the steering of the target vehicle.

[0117] The control quantity determination device provided in the embodiments of the present invention can execute the control quantity determination method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0118] Example 4

[0119] Figure 4 This is a schematic diagram of a control quantity determination device according to Embodiment 4 of the present invention. This control quantity determination device can be an electronic device, intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0120] like Figure 4As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0121] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0122] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as control quantity determination methods.

[0123] In some embodiments, the control quantity determination method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the control quantity determination method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the control quantity determination method by any other suitable means (e.g., by means of firmware).

[0124] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0125] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0126] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0127] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0128] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0129] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0130] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0131] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A control amount determination method characterized by comprising: include: Acquire vehicle data of the target vehicle and attempt to acquire the true natural frequency of the actual steering system corresponding to the target vehicle; Assuming that the true natural frequency and the ideal natural frequency of the preset ideal steering system corresponding to the target vehicle are the same, based on the vehicle data and the algorithm output control quantity of the preset steering control algorithm, the initial adaptive coefficient of the input control quantity of the real steering system is calculated using the Lyapunov function, the ideal response model of the preset ideal steering system and the true response model of the real steering system, wherein the initial adaptive coefficient includes the first parameter value of the target adaptive parameter; Determine whether the actual inherent frequency has been successfully acquired; If the value has been successfully obtained, the second parameter value corresponding to the target adaptive parameter is determined based on the difference between the true natural frequency and the ideal natural frequency, and the first parameter value in the target adaptive parameter is replaced with the second parameter value to obtain the target adaptive coefficient. The target input control quantity of the real steering system is determined based on the target adaptive coefficient.

2. The method of claim 1, wherein, Based on the difference between the true natural frequency and the ideal natural frequency, the second parameter value corresponding to the target adaptive parameter is determined, including: The first target value corresponding to the difference between the true natural frequency and the ideal natural frequency is found in the first preset lookup table, and the first target value is determined as the second parameter value corresponding to the target adaptive parameter.

3. The method of claim 1, wherein, Based on the difference between the true natural frequency and the ideal natural frequency, the second parameter value corresponding to the target adaptive parameter is determined, including: The second target value corresponding to the difference between the true natural frequency and the ideal natural frequency is found in the second preset lookup table; The second parameter value corresponding to the target adaptive parameter is determined based on the sum of the second target value and the first parameter value.

4. The method of claim 1, wherein, The true natural frequency of the actual steering system corresponding to the target vehicle is obtained in the following way: The vehicle data is fitted using the recursive least squares method to obtain the true natural frequency of the actual steering system corresponding to the target vehicle.

5. The method according to claim 1, characterized in that, After determining whether the true intrinsic frequency has been successfully acquired, the method further includes: If the initial adaptive coefficient is not successfully obtained, it will be determined as the target adaptive coefficient.

6. The method according to any one of claims 1-5, characterized in that, Determining the target input control quantity of the real steering system based on the target adaptive coefficient includes: Integrating the target adaptive coefficients yields the integral adaptive coefficients; The adaptive coefficients are determined using the integral adaptive coefficients and the coefficients of the preset ideal steering system; The target input control quantity of the actual steering system is determined using the adaptive coefficient.

7. The method of claim 1, wherein, Also includes: The target input control quantity is input into the real steering system to perform steering control on the target vehicle.

8. A control amount determining device characterized by comprising: include: The data acquisition module is used to acquire vehicle data of the target vehicle and attempt to acquire the true natural frequency of the actual steering system corresponding to the target vehicle. The initial coefficient calculation module is used to calculate the initial adaptive coefficients of the input control quantity of the real steering system based on the vehicle data and the algorithm output control quantity of the preset steering control algorithm, assuming that the real natural frequency and the preset ideal steering system corresponding to the target vehicle are the same. The initial adaptive coefficients include the first parameter value of the target adaptive parameter. The frequency determination module is used to determine whether the true inherent frequency has been successfully acquired; The target coefficient determination module is used to determine the second parameter value corresponding to the target adaptive parameter based on the difference between the true natural frequency and the ideal natural frequency if the target adaptive parameter has been successfully obtained, and replace the first parameter value in the target adaptive parameter with the second parameter value to obtain the target adaptive coefficient. The control quantity determination module is used to determine the target input control quantity of the actual steering system based on the target adaptive coefficient.

9. A control amount determining device characterized by comprising: The control quantity determination device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the control quantity determination method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the control quantity determination method according to any one of claims 1-7.

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