CN109017984A - A kind of track follow-up control method, control system and the relevant apparatus of unmanned vehicle - Google Patents
A kind of track follow-up control method, control system and the relevant apparatus of unmanned vehicle Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B62—LAND VEHICLES FOR TRAVELLING OTHERWISE THAN ON RAILS
- B62D—MOTOR VEHICLES; TRAILERS
- B62D63/00—Motor vehicles or trailers not otherwise provided for
- B62D63/02—Motor vehicles
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B62—LAND VEHICLES FOR TRAVELLING OTHERWISE THAN ON RAILS
- B62D—MOTOR VEHICLES; TRAILERS
- B62D6/00—Arrangements for automatically controlling steering depending on driving conditions sensed and responded to, e.g. control circuits
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/11—Complex mathematical operations for solving equations, e.g. nonlinear equations, general mathematical optimization problems
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
Abstract
The track follow-up control method of a kind of unmanned vehicle provided herein, comprising: utilize vehicle kinematics, establish the motion model of unmanned vehicle, and successively carry out Taylor expansion, Integral Processing and recursion processing, obtain prediction error functions；Then determining, then objective function is converted to input increment is the function of independent variable to determine desired value, it would be desirable to which value is input to drive system, braking system and steering system, realizes the track model- following control of unmanned vehicle using input quantity as the objective function of independent variable.The application converts the constraint of constraint, input and input slew rate and output to state to the constraint to input increment, linear quadratic planning problem is converted by nonlinear quadratic planning problem to solve, relative to traditional control algorithm, have the advantages that computation complexity is low and control error is close.The application also provides track following control system, a kind of computer readable storage medium and a kind of unmanned vehicle of a kind of unmanned vehicle, has above-mentioned beneficial effect.
Description
Technical field
This application involves unmanned field, in particular to the track follow-up control method of a kind of unmanned vehicle, control system,
And a kind of computer readable storage medium and a kind of unmanned vehicle.
Background technique
With the rise of artificial intelligence the relevant technologies, the research and development of unmanned vehicle technology is just like a raging fire to advance
?.Unmanned wheel paths model- following control algorithm also constantly advances as unmanned vehicle key technology, but unmanned vehicle track following control
System is because want coordinated control wire-controlled steering system, line control brake system and motor driven systems, difficulty with higher.
Therefore, how to realize that the Trajectory Tracking Control of effective unmanned vehicle is asking for those skilled in the art's urgent need to resolve
Topic.
Apply for content
The purpose of the application is to provide track follow-up control method, control system and a kind of calculating of a kind of unmanned vehicle
Machine readable storage medium storing program for executing and a kind of unmanned vehicle propose a kind of based on gradually line for the unmanned vehicle track following of fixed route
The adaptive model prediction algorithm of property, effectively has adjusted wire-controlled steering system, line control brake system and motor driven systems
Equal three digest journals, are easy to implement the track following of unmanned vehicle.
In order to solve the above technical problems, the application provides a kind of track follow-up control method of unmanned vehicle, particular technique side
Case is as follows:
Obtain the coordinate of the unmanned vehicle, the angle of the unmanned vehicle and x-axis, front wheel angle, speed and vehicle wheelbase；
According to the coordinate, the angle, the front wheel angle, the speed and the vehicle wheelbase, transported using vehicle
It is dynamic to learn, establish the motion model of the unmanned vehicle；
Taylor expansion is carried out to the motion model, obtains the corresponding linear model of the motion model；
The linear model is integrated, and obtains linearisation discrete model under default qualifications；
Recursion processing is carried out to the linearisation discrete model, obtains prediction error functions；
The objective function changed with input quantity is determined according to the prediction error functions, and the objective function is converted to
To input second objective function of the increment as independent variable；
Desired value is determined according to second objective function, and the desired value is input to the line traffic control system of the unmanned vehicle
System, to carry out the track model- following control of the unmanned vehicle；Wherein, the line control system includes motor driven systems, line traffic control turn
To system and line control brake system.
Wherein, using vehicle kinematics, the motion model for establishing the unmanned vehicle includes:
Using vehicle kinematics, the motion model of the unmanned vehicle is established using differential equation group.
Wherein, the default qualifications are specially that the input quantity of the drive system remains unchanged within the control period.
Wherein, after carrying out recursion processing to the linearisation discrete model, before obtaining prediction error functions further include:
Obtain the reference quantity of fixing line road track reference point；Wherein, the reference quantity participates in the prediction error
The calculating of function.
Wherein, the desired value is input to the line control system of the unmanned vehicle, comprising:
Desired steering angle is input to and described turns wire-controlled steering system, it would be desirable to which torque is input to the motor driven systems
With the line control brake system；Wherein, the desired value includes the expectation steering angle and the expectation torque.
Wherein, further includes:
Judge to break down in the drive system with the presence or absence of any system；
If so, cutting off the power supply of the motor driven systems and braking.
The application also provides a kind of Trajectory Tracking System of unmanned vehicle characterized by comprising
Unmanned vehicle data acquisition module, for obtaining the coordinate of the unmanned vehicle, angle of the unmanned vehicle and x-axis, preceding
Take turns corner, speed and vehicle wheelbase；
Motion model establishes module, for according to the coordinate, the angle, the front wheel angle, the speed and institute
Vehicle wheelbase is stated, using vehicle kinematics, establishes the motion model of the unmanned vehicle；
Linear model establishes module, and for carrying out Taylor expansion to the motion model, it is corresponding to obtain the motion model
Linear model；
Discrete model establishes module, obtains line for integrating to the linear model, and under default qualifications
Property discrete model；
Prediction error functions establish module, for carrying out recursion processing to the linearisation discrete model, obtain prediction and miss
Difference function；
Objective function establishes module, for determining the objective function changed with input quantity according to the prediction error functions,
And the objective function is converted to the second objective function to input increment as independent variable；
Track model- following control module inputs the desired value for determining desired value according to second objective function
To the line control system of the unmanned vehicle, to carry out the track model- following control of the unmanned vehicle；Wherein, the line control system includes
Motor driven systems, wire-controlled steering system and line control brake system.
The application also provides a kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that institute
State the step of track follow-up control method as described above is realized when computer program is executed by processor.
The application also provides a kind of unmanned vehicle, which is characterized in that including memory and processor, has in the memory
Computer program, the processor realize track model- following control as described above when calling the computer program in the memory
The step of method.
A kind of track follow-up control method of unmanned vehicle provided herein, comprising: obtain the unmanned vehicle coordinate,
The unmanned vehicle and the angle of x-axis, front wheel angle, speed and vehicle wheelbase；According to the coordinate, the angle, the front-wheel
Corner, the speed and the vehicle wheelbase establish the motion model of the unmanned vehicle using vehicle kinematics；To the line
Property model integrated, and linearisation discrete model is obtained under default qualifications；The linearisation discrete model is carried out
Recursion processing, obtains prediction error functions；The objective function changed with input quantity is determined according to the prediction error functions, and will
The objective function is converted to the second objective function to input increment as independent variable；The phase is determined according to second objective function
The desired value is input to the line control system of the unmanned vehicle by prestige value, to carry out the track model- following control of the unmanned vehicle；
Wherein, the line control system includes motor driven systems, wire-controlled steering system and line control brake system.
The application successively uses successive linearization to handle by the motion model to unmanned vehicle, model sliding-model control, and
The recursion prediction of system mode is handled, and finally obtains the cost function changed with input increment, at the same by state constraint,
The constraint of input and input slew rate and output is converted into the constraint to input increment, finally turns nonlinear quadratic planning problem
It turns to linear quadratic planning problem to be solved, and then realizes the track model- following control of unmanned vehicle according to solving result.Relative to
Nonlinear optimization control technology, after converting linear model for nonlinear model, calculation amount is significantly reduced, while controlling error phase
Closely, has higher robustness.Relative to traditional Single-point preview control algolithm, there is better speed adaptability, it is lower
Error is controlled, while can explicitly handle the constraint of input, such as the maximum value of driving motor torque and braking moment, steering wheel
Corner and the maximum value of torque etc. introduce constraint and further improve the adaptability and robustness of model.The parameter tune of controller
It is whole, relative to traditional control algolithm, also simpler visual pattern.The track that the application also provides a kind of unmanned vehicle follows control
System, a kind of computer readable storage medium and a kind of unmanned vehicle processed have above-mentioned beneficial effect, and details are not described herein again.
Detailed description of the invention
In order to illustrate the technical solutions in the embodiments of the present application or in the prior art more clearly, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
The embodiment of application for those of ordinary skill in the art without creative efforts, can also basis
The attached drawing of offer obtains other attached drawings.
Fig. 1 is a kind of flow chart of the track follow-up control method of unmanned vehicle provided by the embodiment of the present application；
Fig. 2 is a kind of trajectory planning schematic diagram of unmanned vehicle provided by the embodiment of the present application；
Fig. 3 is a kind of track following control system structural schematic diagram of unmanned vehicle provided by the embodiment of the present application.
Specific embodiment
To keep the purposes, technical schemes and advantages of the embodiment of the present application clearer, below in conjunction with the embodiment of the present application
In attached drawing, the technical scheme in the embodiment of the application is clearly and completely described, it is clear that described embodiment is
Some embodiments of the present application, instead of all the embodiments.Based on the embodiment in the application, those of ordinary skill in the art
Every other embodiment obtained without making creative work, shall fall in the protection scope of this application.
Referring to FIG. 1, Fig. 1 is a kind of process of the track follow-up control method of unmanned vehicle provided by the embodiment of the present application
Figure, detailed process is as follows:
S101: the coordinate of the unmanned vehicle, the angle of the unmanned vehicle and x-axis, front wheel angle, speed and axle for vehicle are obtained
Away from；
Before the track model- following control for carrying out unmanned vehicle, need to obtain the coordinate of unmanned vehicle, the folder of unmanned vehicle and x-axis
The running parameter of the unmanned vehicles such as angle, front wheel angle, speed and vehicle wheelbase.It should be noted that unmanned vehicle and the angle of x-axis refer to
Be x-axis in the longitudinal axis and global coordinate system in vehicle axis system angle.Acquisition modes specific for parameters are not herein
It limits, the data that those skilled in the art can obtain as needed use corresponding tool, such as can pass through unmanned vehicle
IMU Inertial Measurement Unit, GPS, wheel speed, camera, laser radar sensor and steering wheel angle sensor data are worked as
Coordinate value (x, y), speed v, front wheel angle δ and the angle with global coordinate system x-axis of preceding unmanned vehicleAnd vehicle wheelbase l
The factory parameter that unmanned vehicle can be inquired obtains.
It is understood that above several parameters are more important for establishing the motion model of unmanned vehicle in S102
Several parameters may also refer to the other parameters or real-time motion data of unmanned vehicle when establishing motion model in different forms,
This is not limited one by one.
It should be noted that the foundation of the global coordinate system of unmanned vehicle is also not construed as limiting herein, it should be by this field skill
Art personnel choose coordinate origin and reference axis according to the actual motion direction of unmanned vehicle and route etc..
S102: according to the coordinate, the angle, the front wheel angle, the speed and the vehicle wheelbase, vehicle is utilized
Kinematics, establishes the motion model of the unmanned vehicle；
Because the vehicle line of unmanned vehicle is fixed, as fixed route, therefore the fixation route of usually unmanned vehicle
All it is to be pre-stored among the memory inside unmanned vehicle, the storage mode and specific storage medium of fixed route is not made herein
It limits.
This step is intended to establish the motion model of unmanned vehicle using vehicle kinematics, in other words, using mathematical knowledge and
The basic information of unmanned vehicle establishes its motion model.To make each clearer statement of step in the application, dependency number is used below
It learns expression formula to be stated, but represents the expression formula of the mathematic(al) representation or model that occur in the application not as the application skill
Unique form of expression of art scheme, but only as a kind of feasible and preferred embodiment.
The kinematics model of unmanned vehicle can be described with following differential equation group:
For the low speed unmanned vehicle under enclosed environment, the kinetic characteristics of vehicle are negligible, with vehicle kinematics come
The motion process of vehicle is described, deployable formula (1) is following form:
Wherein state vector isK is constant, T be desired torque namely driving moment and braking moment it
With.
In turn, it can be obtained by formula (1):
(3) motion model of formula namely unmanned vehicle.F is Nonlinear System of Equations, component be respectively nonlinear equation F 1,
F2, f3, f4, z are observation vector, i.e., the amount acquired in real time using sensor.U is input control quantity, is rotated before δ steering wheel
Angle, T are the sum of driving motor torque and braking moment.
S103: Taylor expansion is carried out to the motion model, obtains the corresponding linear model of the motion model；
This step is intended to that motion model is unfolded in present operating point with Taylor's formula, and then obtains linear model,
I other words step S101 and step S102 are the processes to nonlinear model successive linearization.
Specifically, being illustrated by taking previous step gained model as an example to this step:
(3) formula is carried out using Taylor's formula in present operating point xc=xOP, u=uOPPlace's progress Taylor expansion obtains as follows
Linear model:
Wherein xLFor the quantity of state of linear system, uLFor the input quantity of linearized system, matrix Ac, Bc, Cc, DcEach member
Element can be expressed with separately available following expression:
It is assumed thatThen formula (4) may be expressed as:
Then formula (6) is linearization of nonlinear system model.
S104: integrating linear model, and linearisation discrete model is obtained under default qualifications；
After realizing the successive linearization to nonlinear system based on both of the aforesaid step, the expectation of system is further sought
Value.This step is intended to obtain the local linearization discrete model of nonlinear system.It should be noted that default qualifications are specific
Correlated condition setting should be made according to linear model or actual demand by those skilled in the art, be not limited thereto.Such as this is pre-
Limiting can remain unchanged within the control period surely for the input quantity of drive system.
Specifically, by taking previous step gained model as an example, and maintained not within the control period with the input quantity of drive system
Become, this step be illustrated:
The state differential equation both sides of formula (6) are integrated simultaneously and are obtained:
Have for moment k and k+1:
Wherein TsTo control the period,
It is assumed that u is in control cycle TsIt inside remains unchanged, then has
Thus the local linearization discrete model of system:
X (k+1)=Adx(k)+BdU (k)+K, y (k)=Cdx(k)+Ddu(k) (10)
And it defines
Wherein y (k+i | k), i=1,2,3 ..., p are prediction of the k moment to the output y at k+i moment, and wherein p is prediction
Step number.
S105: recursion processing is carried out to linearisation discrete model, obtains prediction error functions；
This step is intended to calculate the prediction error in the model- following control of track, specifically, needing to acquiring in previous step
It linearizes discrete model and carries out recursion processing.
Specifically, being illustrated for linearizing discrete model obtained by previous step to this step:
It can be obtained according to formula (10) recursion
Further, it after carrying out recursion processing to the linearisation discrete model, obtains going back before prediction error functions
Include:
Obtain with track reference point reference quantity Rx, Ry,Rv.Referring to fig. 2, Fig. 2 is provided by the embodiment of the present application
A kind of unmanned vehicle trajectory planning schematic diagram.As shown in Fig. 2, by the IMU Inertial Measurement Unit of unmanned vehicle, GPS, wheel speed,
Camera, laser radar sensor and steering wheel angle sensor data obtain coordinate value x, y of current unmanned vehicle, speed v,
Front wheel angle δ, the angle of the vehicle longitudinal axis and global coordinate system x-axisInput to MPC module (Model Predictive
Control, model prediction control).Black dot represents the track reference point that trajectory planning module obtains, MPC module in Fig. 2
Unmanned vehicle, which is obtained, from unmanned vehicle trajectory planning module follows track reference quantity Rx, Ry,Rv, wherein Rx is the direction vehicle x
Reference coordinate, Rx are the reference coordinate in the direction y,For the tangent line of reference locus and the reference angle of x-axis, Rv is vehicle reference
Speed.
Since each point contains corresponding reference quantity, so Rx, Ry,Rv is the vector of p dimension, and wherein p is pre-
Survey step number, definitionThen predict that error can be expressed as:
S106: determining the objective function that changes with input quantity according to the prediction error functions, and by the objective function
Be converted to the second objective function to input increment as independent variable；
This step, which is intended to determination, can calculate the objective function namely cost function of desired value.Specifically, with previous step
Based on gained prediction error functions, this step is illustrated:
According to prediction error functions objective function are as follows:
Wherein Q and R is respectively the weight matrix for predicting error and input, and other parameters and symbol are the contracting of derivation process
It writes, concrete meaning is shown in derivation process.
Obtaining objective function isSecondary cost function:
To reduce steady-state error, while constraint is added to the change rate of input, converts objective function to the variation of input
Amount (namely input increment)Function, specific conversion process is as follows:
Then objective function be expressed as input increment function it is as follows:
Wherein,
In above formula, the meaning of Metzler matrix as described in formula (16) derivation process, G and W matrix as described in formula (14) derivation process,
Subscript T representing matrix transposition operation.
S107: desired value is determined according to second objective function, the desired value is input to the line of the unmanned vehicle
Control system, to carry out the track model- following control of the unmanned vehicle；
The line control system of unmanned vehicle includes motor driven systems, wire-controlled steering system and line control brake system.
Desired value can be obtained according to formula (18)Desired value need to be only input to the line control system of unmanned vehicle at this time
The track model- following control of unmanned vehicle can be realized.
Further, this step can specifically include:
Desired steering angle is input to wire-controlled steering system, it would be desirable to which torque is input to drive system and brake-by-wire system
System；Wherein, desired value includes desired steering angle and desired torque.
By expectation value expression, it is apparent that it is made of expectation steering angle and desired torque.
The application successively uses successive linearization to handle by the motion model to unmanned vehicle, model sliding-model control, most
The objective function to input increment as independent variable is obtained eventually, by the pact of constraint, input and input slew rate to state and output
Beam is converted into the constraint to input increment, finally converts linear quadratic planning problem for nonlinear quadratic planning problem and asks
Solution, and then according to the track model- following control of solving result realization unmanned vehicle.Compared with the existing technology, computation complexity is low and controls
Error is close.
Based on the above embodiment, as preferred embodiment, which can also include:
Judge that event occurs with the presence or absence of any system in motor driven systems, wire-controlled steering system and line control brake system
Barrier；
If so, the power supply and braking of cutting motor driven systems.
The purpose of the present embodiment is that according to the electric current and state of motor drive system controller feedback, steering-by-wire motor
Electric current and system mode and line control brake system pressure and state, judge whether three big line control systems work normally, if there is
System breaks down, then cutting drive system powers and takes brake measure immediately.It is exported in S107 if without failure
Calculated result.Likewise, the working condition of monitoring three digest journals is also to need to need real-time perfoming in unmanned vehicle driving process
Process.
A kind of Trajectory Tracking Control System of unmanned vehicle provided by the embodiments of the present application is introduced below, is described below
Trajectory Tracking Control System can correspond to each other reference with above-described Trajectory Tracking Control method.
Referring to Fig. 3, Fig. 3 is a kind of Trajectory Tracking Control System structural representation of unmanned vehicle provided by the embodiment of the present application
Figure, the application also provide a kind of track following control system of unmanned vehicle, and the adaptive line MPC applied to unmanned vehicle is controlled
Device, comprising:
Unmanned vehicle data acquisition module 100, for obtain the coordinate of the unmanned vehicle, the angle of the unmanned vehicle and x-axis,
Front wheel angle, speed and vehicle wheelbase；
Motion model establishes module 200, for according to the coordinate, the angle, the front wheel angle, the speed and
The vehicle wheelbase establishes the motion model of the unmanned vehicle using vehicle kinematics；
Linear model establishes module 300, for carrying out Taylor expansion to the motion model, obtains the motion model pair
The linear model answered；
Discrete model establishes module 400, obtains for integrating to the linear model, and under default qualifications
Linearize discrete model；
Prediction error functions establish module 500, for carrying out recursion processing to the linearisation discrete model, are predicted
Error function；
Objective function establishes module 600, for determining the target letter changed with input quantity according to the prediction error functions
It counts, and the objective function is converted to the second objective function to input increment as independent variable；
Track model- following control module 700, it is for determining desired value according to second objective function, the desired value is defeated
Enter to the line control system of the unmanned vehicle, to carry out the track model- following control of the unmanned vehicle；Wherein, the line control system packet
Include motor driven systems, wire-controlled steering system and line control brake system.
Present invention also provides a kind of computer readable storage mediums, have computer program thereon, the computer program
It is performed and step provided by above-described embodiment may be implemented.The storage medium may include: USB flash disk, mobile hard disk, read-only deposit
Reservoir (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), magnetic disk or
The various media that can store program code such as CD.
Present invention also provides a kind of unmanned vehicles, may include memory and processor, have calculating in the memory
When the processor calls the computer program in the memory, step provided by above-described embodiment is may be implemented in machine program
Suddenly.Certain unmanned vehicle can also include various network interfaces, the components such as power supply.
Each embodiment is described in a progressive manner in specification, the highlights of each of the examples are with other realities
The difference of example is applied, the same or similar parts in each embodiment may refer to each other.For embodiment provide system and
Speech, since it is corresponding with the method that embodiment provides, so being described relatively simple, related place is referring to method part illustration
?.
Specific examples are used herein to illustrate the principle and implementation manner of the present application, and above embodiments are said
It is bright to be merely used to help understand the present processes and its core concept.It should be pointed out that for the ordinary skill of the art
For personnel, under the premise of not departing from the application principle, can also to the application, some improvement and modification can also be carried out, these improvement
It is also fallen into the protection scope of the claim of this application with modification.
It should also be noted that, in the present specification, relational terms such as first and second and the like be used merely to by
One entity or operation are distinguished with another entity or operation, without necessarily requiring or implying these entities or operation
Between there are any actual relationship or orders.Moreover, the terms "include", "comprise" or its any other variant meaning
Covering non-exclusive inclusion, so that the process, method, article or equipment for including a series of elements not only includes that
A little elements, but also including other elements that are not explicitly listed, or further include for this process, method, article or
The intrinsic element of equipment.In the absence of more restrictions, the element limited by sentence "including a ...", is not arranged
Except there is also other identical elements in the process, method, article or apparatus that includes the element.
Claims (9)
1. a kind of trace tracking method of unmanned vehicle characterized by comprising
Obtain the coordinate of the unmanned vehicle, the angle of the unmanned vehicle and x-axis, front wheel angle, speed and vehicle wheelbase；
According to the coordinate, the angle, the front wheel angle, the speed and the vehicle wheelbase, using vehicle kinematics,
Establish the motion model of the unmanned vehicle；
Taylor expansion is carried out to the motion model, obtains the corresponding linear model of the motion model；
The linear model is integrated, and obtains linearisation discrete model under default qualifications；
Recursion processing is carried out to the linearisation discrete model, obtains prediction error functions；
The objective function changed with input quantity is determined according to the prediction error functions, and the objective function is converted to defeated
Enter the second objective function that increment is independent variable；
Desired value is determined according to second objective function, and the desired value is input to the line control system of the unmanned vehicle, with
Just the track model- following control of the unmanned vehicle is carried out；Wherein, the line control system includes motor driven systems, wire-controlled steering system
And line control brake system.
2. trace tracking method according to claim 1, which is characterized in that utilize vehicle kinematics, establish it is described nobody
The motion model of vehicle includes:
Using vehicle kinematics, the motion model of the unmanned vehicle is established using differential equation group.
3. Trajectory Tracking System according to claim 1, which is characterized in that the default qualifications are specially the drive
The input quantity of dynamic system remains unchanged within the control period.
4. Trajectory Tracking System according to claim 1, which is characterized in that carry out recursion to the linearisation discrete model
After processing, before obtaining prediction error functions further include:
Obtain the reference quantity of fixing line road track reference point；Wherein, the reference quantity participates in the prediction error functions
Calculating.
5. track follow-up control method according to claim 1, which is characterized in that the desired value is input to the nothing
The line control system of people's vehicle, comprising:
Desired steering angle is input to the wire-controlled steering system, it would be desirable to which torque is input to motor driven systems and described
Line control brake system；Wherein, the desired value includes the expectation steering angle and the expectation torque.
6. track follow-up control method according to claim 1-5, which is characterized in that further include:
Judge to break down in the drive system with the presence or absence of any system；
If so, cutting off the power supply of the motor driven systems and braking.
7. a kind of Trajectory Tracking System of unmanned vehicle, which is characterized in that be applied to adaptive line MPC controller, comprising:
Unmanned vehicle data acquisition module, for obtaining the coordinate of the unmanned vehicle, the angle of the unmanned vehicle and x-axis, preceding rotation
Angle, speed and vehicle wheelbase；
Motion model establishes module, for according to the coordinate, the angle, the front wheel angle, the speed and the vehicle
Wheelbase establishes the motion model of the unmanned vehicle using vehicle kinematics；
Linear model establishes module, for carrying out Taylor expansion to the motion model, obtains the corresponding line of the motion model
Property model；
Discrete model establishes module, is linearized for integrating to the linear model, and under default qualifications
Discrete model；
Prediction error functions establish module, for carrying out recursion processing to the linearisation discrete model, obtain prediction error letter
Number；
Objective function establishes module, for determining the objective function changed with input quantity according to the prediction error functions, and will
The objective function is converted to the second objective function to input increment as independent variable；
The desired value is input to institute for determining desired value according to second objective function by track model- following control module
The line control system of unmanned vehicle is stated, to carry out the track model- following control of the unmanned vehicle；Wherein, the line control system includes motor
Drive system, wire-controlled steering system and line control brake system.
8. a kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that the computer program quilt
The step of processor realizes track follow-up control method as claimed in any one of claims 1 to 6 when executing.
9. a kind of unmanned vehicle, which is characterized in that including memory and processor, have computer program, institute in the memory
It states and realizes that track as claimed in any one of claims 1 to 6 follows control when processor calls the computer program in the memory
The step of method processed.
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Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110008514A (en) * | 2019-03-06 | 2019-07-12 | 深兰科技（上海）有限公司 | A kind of method and apparatus carrying out linearization process |
| CN110497407A (en) * | 2019-08-16 | 2019-11-26 | 深圳华数机器人有限公司 | It is a kind of to control integrated Intelligent track system for tracking applied to industrial robot |
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