CN111058952A - Electronic throttle control method and system based on self-adaptive fuzzy technology and vehicle - Google Patents

Electronic throttle control method and system based on self-adaptive fuzzy technology and vehicle Download PDF

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CN111058952A
CN111058952A CN201911368234.0A CN201911368234A CN111058952A CN 111058952 A CN111058952 A CN 111058952A CN 201911368234 A CN201911368234 A CN 201911368234A CN 111058952 A CN111058952 A CN 111058952A
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electronic throttle
control
adaptive
fuzzy
throttle valve
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孙波
刘一鸣
陈晶
张承慧
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Shandong University
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    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
    • F02D—CONTROLLING COMBUSTION ENGINES
    • F02D41/00—Electrical control of supply of combustible mixture or its constituents
    • F02D41/0002—Controlling intake air
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
    • F02D—CONTROLLING COMBUSTION ENGINES
    • F02D11/00—Arrangements for, or adaptations to, non-automatic engine control initiation means, e.g. operator initiated
    • F02D11/06—Arrangements for, or adaptations to, non-automatic engine control initiation means, e.g. operator initiated characterised by non-mechanical control linkages, e.g. fluid control linkages or by control linkages with power drive or assistance
    • F02D11/10—Arrangements for, or adaptations to, non-automatic engine control initiation means, e.g. operator initiated characterised by non-mechanical control linkages, e.g. fluid control linkages or by control linkages with power drive or assistance of the electric type
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
    • F02D—CONTROLLING COMBUSTION ENGINES
    • F02D41/00—Electrical control of supply of combustible mixture or its constituents
    • F02D41/02—Circuit arrangements for generating control signals
    • F02D41/14—Introducing closed-loop corrections
    • F02D41/1401—Introducing closed-loop corrections characterised by the control or regulation method
    • F02D41/1402—Adaptive control
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
    • F02D—CONTROLLING COMBUSTION ENGINES
    • F02D41/00—Electrical control of supply of combustible mixture or its constituents
    • F02D41/02—Circuit arrangements for generating control signals
    • F02D41/14—Introducing closed-loop corrections
    • F02D41/1401—Introducing closed-loop corrections characterised by the control or regulation method
    • F02D41/1404—Fuzzy logic control
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
    • F02D—CONTROLLING COMBUSTION ENGINES
    • F02D41/00—Electrical control of supply of combustible mixture or its constituents
    • F02D41/02—Circuit arrangements for generating control signals
    • F02D41/14—Introducing closed-loop corrections
    • F02D41/1401—Introducing closed-loop corrections characterised by the control or regulation method
    • F02D2041/1433—Introducing closed-loop corrections characterised by the control or regulation method using a model or simulation of the system

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  • Engineering & Computer Science (AREA)
  • Chemical & Material Sciences (AREA)
  • Combustion & Propulsion (AREA)
  • Mechanical Engineering (AREA)
  • General Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Fuzzy Systems (AREA)
  • Mathematical Physics (AREA)
  • Software Systems (AREA)
  • Combined Controls Of Internal Combustion Engines (AREA)
  • Control Of Throttle Valves Provided In The Intake System Or In The Exhaust System (AREA)

Abstract

The disclosure provides an electronic throttle control method, system and vehicle based on self-adaptive fuzzy technology, wherein a mathematical model of an electronic throttle system is constructed, and a self-adaptive controller of the electronic throttle system is designed by adopting a self-adaptive algorithm; constructing a tracking error system, taking the tracking error of the system and the derivative of the tracking error as the input quantity of a fuzzy controller, and selecting proper first control parameters and second control parameters by adopting a fuzzy control algorithm; the self-adaptive controller calculates the optimal control voltage of the electronic throttle valve according to the first control parameter and the second control parameter output by the fuzzy controller, and further outputs the ideal output angle of the electronic throttle valve; the method can adjust the parameters of the self-adaptive controller in real time in the running process of the system, reduces the influence of the uncertainty of the parameters of the electronic throttle valve and the nonlinear characteristic of the throttle valve control system on the control of the electronic throttle valve, and has the characteristics of high control precision and high response speed.

Description

Electronic throttle control method and system based on self-adaptive fuzzy technology and vehicle
Technical Field
The disclosure relates to the technical field of electronic throttle control, in particular to an electronic throttle control method and system based on an adaptive fuzzy technology and a vehicle.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
The electronic throttle valve is a controllable valve for controlling air to enter the engine, and is composed of a direct current motor, a position sensor, a return spring, a valve plate and the like, and the air can be mixed with gasoline into a combustible mixed gas after entering an air inlet pipe, so that the combustible mixed gas can be combusted to apply work. Thus, the performance of the electronic throttle determines the response of engine torque and the accuracy of the fuel/air (F/A) ratio. The control effect of the electronic throttle directly affects the dynamic property, economy and emission of the engine, so the stability and accuracy of the throttle control are important for the smooth running of the engine and the protection of the ecological environment.
The inventor of the present invention finds, through search, that the chinese invention patent CN101408133A "a control method of an electronic throttle valve of an engine" controls the opening of a valve plate of the electronic throttle valve by using a PID control method, and realizes the rapid and stable operation of the valve plate of the electronic throttle valve. However, this method is not high in control accuracy. The Chinese patent CN109184925A electronic throttle control method based on the adaptive integral terminal sliding mode technology obtains the optimal output angle of the throttle through the adaptive integral terminal sliding mode control algorithm of the uncertainty observer, and improves the control precision of the electronic throttle. The Chinese invention patent CN107701315A electronic throttle control method based on the adaptive sliding mode technology utilizes the adaptive robust sliding mode control algorithm to calculate the optimal control voltage of the throttle, and solves the problem of the influence of the nonlinearity of the gear clearance torque on the electronic throttle control system. Although various adaptive control algorithms are proposed by a plurality of scholars aiming at the electronic throttle valve, the existing adaptive control method of the electronic throttle valve has the following defects: the adjustable parameters in the traditional self-adaptive control system cannot be adjusted in real time in the running process of the system, and the optimal control effect cannot be achieved.
Disclosure of Invention
In order to solve the defects of the prior art, the invention provides an electronic throttle control method, an electronic throttle control system and a vehicle based on an adaptive fuzzy technology, which can adjust the parameters of an adaptive controller in real time in the running process of the system, reduce the influence of the uncertainty of the parameters of the electronic throttle and the nonlinear characteristic of a throttle control system on the control of the electronic throttle, and have the characteristics of high control precision and high response speed.
In order to achieve the purpose, the following technical scheme is adopted in the disclosure:
the first aspect of the disclosure provides an electronic throttle control method based on an adaptive fuzzy technology.
An electronic throttle control method based on an adaptive fuzzy technology comprises the following steps:
constructing a mathematical model of the electronic throttle system to obtain a state space expression of the electronic throttle system;
constructing a first error variable and a second error variable, and designing an adaptive controller of the electronic throttle system by adopting an adaptive algorithm to obtain a control law of the optimal control voltage of the adaptive controller;
constructing a tracking error system, processing the first error variable and the second error variable to obtain a state space expression of the tracking error system of the electronic throttle valve, and obtaining the relation between the first control parameter and the second control parameter of the adaptive controller and the system tracking error;
acquiring a preset opening degree and a real-time opening degree of the electronic throttle valve, taking a tracking error of a system and a derivative of the tracking error as input quantities of a fuzzy controller, and selecting proper first control parameters and second control parameters by adopting a fuzzy control algorithm;
and the self-adaptive controller calculates the optimal control voltage of the electronic throttle valve according to the first control parameter and the second control parameter output by the fuzzy controller, and further outputs the ideal output angle of the electronic throttle valve.
As some possible implementations, the mathematical model of the electronic throttle system is specifically:
Figure BDA0002339009180000031
y＝x1。
as a further limitation, the first error variable is specifically:
ε1＝x1-yr
wherein, yrIs the throttle opening to be tracked.
As a further limitation, the second error variable is specifically:
Figure BDA0002339009180000032
wherein k is1Is a normal number.
As a further limitation, the control law of the optimal control voltage of the adaptive controller specifically includes:
Figure BDA0002339009180000033
wherein k is1And k2Is a normal number.
As some possible implementation manners, the attenuation speed of the system tracking error is related to the selection of the first control parameter, and when the value of the first control parameter is larger, the attenuation speed is higher; the tracking static difference of the system is related to the selection of the second control parameter, and when the value of the second control parameter is larger, the tracking static difference is smaller.
As some possible implementation manners, a fuzzy control algorithm is adopted to select appropriate first control parameters and second control parameters, specifically:
defining a fuzzy set of tracking errors and derivatives of the tracking errors of the system;
fuzzifying the input quantity and output quantity parameters by adopting a triangular membership function method;
formulating a fuzzy rule and carrying out fuzzy reasoning;
and performing deblurring processing by using an average weighting method, and outputting a first control parameter and a second control parameter of the self-adaptive controller.
A second aspect of the present disclosure provides an electronic throttle control system based on adaptive fuzzy technology.
An electronic throttle control system based on adaptive fuzzy technology, comprising:
a model building module configured to: constructing a mathematical model of the electronic throttle system to obtain a state space expression of the electronic throttle system;
an adaptive controller building module configured to: constructing a first error variable and a second error variable, and designing an adaptive controller of the electronic throttle system by adopting an adaptive algorithm to obtain a control law of the optimal control voltage of the adaptive controller;
a tracking error system construction module configured to: constructing a tracking error system, processing the first error variable and the second error variable to obtain a state space expression of the tracking error system of the electronic throttle valve, and obtaining the relation between the first control parameter and the second control parameter of the adaptive controller and the system tracking error;
a blur calculation module configured to: acquiring a preset opening degree and a real-time opening degree of the electronic throttle valve, taking a tracking error of a system and a derivative of the tracking error as input quantities of a fuzzy controller, and selecting proper first control parameters and second control parameters by adopting a fuzzy control algorithm;
a control parameter calculation and output module configured to: and the self-adaptive controller calculates the optimal control voltage of the electronic throttle valve according to the first control parameter and the second control parameter output by the fuzzy controller, and further outputs the ideal output angle of the electronic throttle valve.
A third aspect of the present disclosure provides an electronic device including the adaptive fuzzy technology-based electronic throttle control system according to the second aspect of the present disclosure.
A fourth aspect of the present disclosure provides a vehicle including an adaptive fuzzy technology-based electronic throttle control system according to the second aspect of the present disclosure.
Compared with the prior art, the beneficial effect of this disclosure is:
1. the method can adjust the parameters of the self-adaptive controller in real time in the running process of the system, reduces the influence of the uncertainty of the parameters of the electronic throttle valve and the nonlinear characteristic of the throttle valve control system on the control of the electronic throttle valve, and has the characteristics of high control precision and high response speed.
2. The self-adaptive control method and the self-adaptive controller have the advantages that the self-adaptive controller can adapt to the change of a system more intelligently through the real-time online setting of the parameters of the self-adaptive controller by the fuzzy controller, so that the optimal control effect on the opening degree of the electronic throttle valve is achieved, and meanwhile, the control strategy based on the self-adaptive fuzzy technology is higher in control precision and higher in response speed.
Drawings
Fig. 1 is a block diagram of an electronic throttle control strategy based on adaptive fuzzy technology provided in embodiment 1 of the present disclosure.
Fig. 2 is a schematic flowchart of an electronic throttle control method based on an adaptive fuzzy technique according to embodiment 1 of the present disclosure.
Detailed Description
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present disclosure. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
The embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict.
Example 1:
as shown in fig. 1-2, embodiment 1 of the present disclosure provides an electronic throttle control method based on an adaptive fuzzy technique, which includes the following specific steps:
step 1: and (5) establishing a mathematical model of the electronic throttle system.
Selecting a state vector
Figure BDA0002339009180000061
Establishing a state space expression of the electronic throttle system:
Figure BDA0002339009180000062
y＝x1
wherein J is n2Jm+JgAnd B ═ n2Bm+BtRespectively the equivalent total inertia and the damping constant,
Figure BDA0002339009180000063
theta is a rotation angle of the throttle valve sheet, kspIs the elastic coefficient of the return spring, n is the ideal transmission ratio of the reduction gear, RaIs the internal resistance of the drive motor, u is the input voltage of the drive motor, JmIs the moment of inertia of the drive motor, JgIs the moment of inertia of the throttle flap shaft, BmIs the damping coefficient of the drive motor, BtIs the damping coefficient of the throttle valve, kbIs the back electromotive force constant, k, of the drive motortIs the torque constant of the drive motor, θ0Is the initial opening of the valve plate of the door body, FsIs the Coulomb friction coefficient, kpreIs the pre-tightening force coefficient of the return spring.
Step 2: aiming at the nonlinear characteristic of the system, a nonlinear controller of the electronic throttle system is designed by adopting an adaptive algorithm.
The basic steps for designing an electronic throttle controller based on an adaptive algorithm are as follows:
first, a first error variable is defined:
ε1＝x1-yr
wherein, yrIs to be followedThe opening degree of a throttle valve is tracked.
The Lyapunov function is chosen to be:
Figure BDA0002339009180000071
the derivative is:
Figure BDA0002339009180000072
to make it
Figure BDA0002339009180000073
Negative definite, then x is selected2For virtual control, the ideal virtual control value is:
Figure BDA0002339009180000074
wherein k is1Is a normal number, then a second error variable is defined:
Figure BDA0002339009180000075
the Lyapunov function is chosen to be:
Figure BDA0002339009180000076
deriving it yields:
Figure BDA0002339009180000077
to make it possible to
Figure BDA0002339009180000078
Negative determination, such that:
Figure BDA0002339009180000079
wherein k is2Is a normal number.
Obtaining a control law of the controller:
Figure BDA00023390091800000710
and step 3: and establishing a tracking error system and analyzing.
Two error variables are derived:
Figure BDA00023390091800000711
Figure BDA0002339009180000081
and (3) arranging to obtain an electronic throttle tracking error system state space expression:
Figure BDA0002339009180000082
and has the following components:
Figure BDA0002339009180000083
in summary, the decay rate and k of the tracking error of the system1The larger the value of (c), the faster the decay rate. Tracking static error and k of system2The larger the value of (c), the smaller the tracking static error. But large k1And k2A high gain of the controller is caused which causes problems of amplifying the interference signal and overshoot.
And 4, step 4: selecting proper k by adopting fuzzy control algorithm1And k2。
In a fuzzy logic system, a tracking error ε of the system is set1And derivative of tracking error
Figure BDA0002339009180000084
As input for fuzzy controlQuantity, two parameters k to be adaptively controlled1And k2As output variables and defines the value ranges of the input and output quantity parameters according to the actual output of the system. The specific method comprises the following steps:
step 4-1: defining the tracking error epsilon of the system1And derivative of tracking error
Figure BDA0002339009180000085
The fuzzy sets of (a) are: { NB (negative large), NM (negative medium), ZO (zero), PS (positive small), PB (positive large) }, two parameters k defining the adaptive control1And k2The fuzzy sets of (a) are: { PS (positive small), PM (positive middle), PB (positive large) };
step 4-2: fuzzifying the input quantity and output quantity parameters by adopting a triangular membership function method;
step 4-3: formulating a fuzzy rule and carrying out fuzzy reasoning;
step 4-4: using average weighting method to perform deblurring processing and output two parameters k of self-adaptive control1And k2。
In step 4-3, the fuzzy rule is shown in tables 1 and 2.
Table 1: first fuzzy rule
Figure BDA0002339009180000091
Table 2: second fuzzy rule
Figure BDA0002339009180000092
And 5: the adaptive controller outputs a parameter k according to the fuzzy controller1And k2And calculating the optimal control voltage u of the electronic throttle valve so as to output the ideal output angle of the electronic throttle valve.
Example 2:
the embodiment 2 of the present disclosure provides an electronic throttle control system based on an adaptive fuzzy technology.
An electronic throttle control system based on adaptive fuzzy technology, comprising:
a model building module configured to: constructing a mathematical model of the electronic throttle system to obtain a state space expression of the electronic throttle system;
an adaptive controller building module configured to: constructing a first error variable and a second error variable, and designing an adaptive controller of the electronic throttle system by adopting an adaptive algorithm to obtain a control law of the optimal control voltage of the adaptive controller;
a tracking error system construction module configured to: constructing a tracking error system, processing the first error variable and the second error variable to obtain a state space expression of the tracking error system of the electronic throttle valve, and obtaining the relation between the first control parameter and the second control parameter of the adaptive controller and the system tracking error;
a blur calculation module configured to: acquiring a preset opening degree and a real-time opening degree of the electronic throttle valve, taking a tracking error of a system and a derivative of the tracking error as input quantities of a fuzzy controller, and selecting proper first control parameters and second control parameters by adopting a fuzzy control algorithm;
a control parameter calculation and output module configured to: and the self-adaptive controller calculates the optimal control voltage of the electronic throttle valve according to the first control parameter and the second control parameter output by the fuzzy controller, and further outputs the ideal output angle of the electronic throttle valve.
Example 3:
the embodiment 3 of the present disclosure provides an electronic device including an electronic throttle control system based on an adaptive fuzzy technology according to the embodiment 2 of the present disclosure.
Example 4:
the embodiment 4 of the present disclosure provides a vehicle including an electronic throttle control system based on adaptive fuzzy technology according to the embodiment 2 of the present disclosure.
The above description is only a preferred embodiment of the present disclosure and is not intended to limit the present disclosure, and various modifications and changes may be made to the present disclosure by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present disclosure should be included in the protection scope of the present disclosure.
Although the present disclosure has been described with reference to specific embodiments, it should be understood that the scope of the present disclosure is not limited thereto, and those skilled in the art will appreciate that various modifications and changes can be made without departing from the spirit and scope of the present disclosure.

Claims (10)

1. An electronic throttle control method based on an adaptive fuzzy technology is characterized by comprising the following steps:
constructing a mathematical model of the electronic throttle system to obtain a state space expression of the electronic throttle system;
constructing a first error variable and a second error variable, and designing an adaptive controller of the electronic throttle system by adopting an adaptive algorithm to obtain a control law of the optimal control voltage of the adaptive controller;
constructing a tracking error system, processing the first error variable and the second error variable to obtain a state space expression of the tracking error system of the electronic throttle valve, and obtaining the relation between the first control parameter and the second control parameter of the adaptive controller and the system tracking error;
acquiring a preset opening degree and a real-time opening degree of the electronic throttle valve, taking a tracking error of a system and a derivative of the tracking error as input quantities of a fuzzy controller, and selecting proper first control parameters and second control parameters by adopting a fuzzy control algorithm;
and the self-adaptive controller calculates the optimal control voltage of the electronic throttle valve according to the first control parameter and the second control parameter output by the fuzzy controller, and further outputs the ideal output angle of the electronic throttle valve.
2. The electronic throttle control method based on the adaptive fuzzy technology as claimed in claim 1, wherein the mathematical model of the electronic throttle system is specifically:
Figure FDA0002339009170000011
y＝x1
wherein J is n2Jm+JgAnd B ═ n2Bm+BtRespectively the equivalent total inertia and the damping constant,
Figure FDA0002339009170000012
theta is a rotation angle of the throttle valve sheet, kspIs the elastic coefficient of the return spring, n is the ideal transmission ratio of the reduction gear, RaIs the internal resistance of the drive motor, u is the input voltage of the drive motor, JmIs the moment of inertia of the drive motor, JgIs the moment of inertia of the throttle flap shaft, BmIs the damping coefficient of the drive motor, BtIs the damping coefficient of the throttle valve, kbIs the back electromotive force constant, k, of the drive motortIs the torque constant of the drive motor, θ0Is the initial opening of the valve plate of the door body, FsIs the Coulomb friction coefficient, kpreIs the pre-tightening force coefficient of the return spring.
3. The electronic throttle control method based on the adaptive fuzzy technology as claimed in claim 2, wherein the first error variable is specifically:
ε1＝x1-yr
wherein, yrIs the throttle opening to be tracked.
4. The electronic throttle control method based on the adaptive fuzzy technology as claimed in claim 2, wherein the second error variable is specifically:
Figure FDA0002339009170000021
wherein k is1Is a normal number.
5. The electronic throttle control method based on the adaptive fuzzy technology as claimed in claim 2, wherein the control law of the optimal control voltage of the adaptive controller is specifically:
Figure FDA0002339009170000022
wherein k is1And k2Is a normal number.
6. The electronic throttle control method based on the adaptive fuzzy technique of claim 1, wherein the decay rate of the system tracking error is related to the selection of the first control parameter, and the decay rate is faster when the value of the first control parameter is larger; the tracking static difference of the system is related to the selection of the second control parameter, and when the value of the second control parameter is larger, the tracking static difference is smaller.
7. The electronic throttle valve control method based on the adaptive fuzzy technology as claimed in claim 1, wherein the fuzzy control algorithm is adopted to select the appropriate first control parameter and second control parameter, specifically:
defining a fuzzy set of tracking errors and derivatives of the tracking errors of the system;
fuzzifying the input quantity and output quantity parameters by adopting a triangular membership function method;
formulating a fuzzy rule and carrying out fuzzy reasoning;
and performing deblurring processing by using an average weighting method, and outputting a first control parameter and a second control parameter of the self-adaptive controller.
8. An electronic throttle control system based on adaptive fuzzy technology, comprising:
a model building module configured to: constructing a mathematical model of the electronic throttle system to obtain a state space expression of the electronic throttle system;
an adaptive controller building module configured to: constructing a first error variable and a second error variable, and designing an adaptive controller of the electronic throttle system by adopting an adaptive algorithm to obtain a control law of the optimal control voltage of the adaptive controller;
a tracking error system construction module configured to: constructing a tracking error system, processing the first error variable and the second error variable to obtain a state space expression of the tracking error system of the electronic throttle valve, and obtaining the relation between the first control parameter and the second control parameter of the adaptive controller and the system tracking error;
a blur calculation module configured to: acquiring a preset opening degree and a real-time opening degree of the electronic throttle valve, taking a tracking error of a system and a derivative of the tracking error as input quantities of a fuzzy controller, and selecting proper first control parameters and second control parameters by adopting a fuzzy control algorithm;
a control parameter calculation and output module configured to: and the self-adaptive controller calculates the optimal control voltage of the electronic throttle valve according to the first control parameter and the second control parameter output by the fuzzy controller, and further outputs the ideal output angle of the electronic throttle valve.
9. An electronic device characterized by comprising the electronic throttle control system based on the adaptive fuzzy technology of claim 8.
10. A vehicle comprising the adaptive fuzzy technology-based electronic throttle control system of claim 8.
CN201911368234.0A 2019-12-26 2019-12-26 Electronic throttle control method and system based on self-adaptive fuzzy technology and vehicle Pending CN111058952A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117555224A (en) * 2024-01-09 2024-02-13 冠县新瑞实业有限公司 Wheat gluten production control method based on decoupling control system

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5524599A (en) * 1994-01-19 1996-06-11 Kong, Deceased; Hakchul H. Fuzzy logic air/fuel controller
CN102953842A (en) * 2011-08-29 2013-03-06 比亚迪股份有限公司 Control method of electronic throttle valve
CN104192146A (en) * 2014-09-12 2014-12-10 辽宁工业大学 Fuzzy control based automotive intelligent cruise assisted driving system control method
CN106321255A (en) * 2016-09-30 2017-01-11 张家港长安大学汽车工程研究院 Stepping motor-based automatic control system for open degree of throttle gate of automobile
CN107605608A (en) * 2017-08-30 2018-01-19 山东大学 Petrol engine method for controlling number of revolution for hydraulic-driven leg legged type robot
CN109098862A (en) * 2018-07-31 2018-12-28 合肥工业大学 Electronic Throttle Control method based on continuous quickly non-singular terminal sliding mode technology

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5524599A (en) * 1994-01-19 1996-06-11 Kong, Deceased; Hakchul H. Fuzzy logic air/fuel controller
CN102953842A (en) * 2011-08-29 2013-03-06 比亚迪股份有限公司 Control method of electronic throttle valve
CN104192146A (en) * 2014-09-12 2014-12-10 辽宁工业大学 Fuzzy control based automotive intelligent cruise assisted driving system control method
CN106321255A (en) * 2016-09-30 2017-01-11 张家港长安大学汽车工程研究院 Stepping motor-based automatic control system for open degree of throttle gate of automobile
CN107605608A (en) * 2017-08-30 2018-01-19 山东大学 Petrol engine method for controlling number of revolution for hydraulic-driven leg legged type robot
CN109098862A (en) * 2018-07-31 2018-12-28 合肥工业大学 Electronic Throttle Control method based on continuous quickly non-singular terminal sliding mode technology

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
张国飞: "汽车电子节气门检测平台控制系统设计", 《中国优秀硕士学位论文全文数据库》 *
陈虹 等: "基于backstepping方法的电子节气门控制", 《控制理论与应用》 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117555224A (en) * 2024-01-09 2024-02-13 冠县新瑞实业有限公司 Wheat gluten production control method based on decoupling control system
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