CN110209175A - More intelligent vehicle formation methods based on distributed finite time state observer - Google Patents
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Abstract
The present invention relates to a kind of more intelligent vehicle formation methods based on distributed finite time state observer, comprising steps of S1, according to intelligent vehicle kinematics model, the kinematics character of intelligent vehicle is described；The client/server of S2, the more intelligent vehicles of building, and the topological structure based on directed spanning tree establishes the communication network architecture between more intelligent vehicles；The distributed finite time state observer of S3, design independent of world coordinates information, to obtain observation；S4, observation is inputted into more intelligent vehicle distribution formation control devices, to realize the automatic formation of more intelligent vehicles.Compared with prior art, the present invention obtains the relative position between vehicle by laser radar and gyroscope, make control errors in millimetre range, it ensure that observation is more nearly actual value, the convergence that ensure that observer using directed spanning tree building communication network architecture simultaneously, finally can effectively promote the precision and safety of intelligent vehicle formation.
Description
Technical field
The present invention relates to more intelligent vehicle Collaborative Controls fields, more particularly, to one kind based on distributed finite time state
More intelligent vehicle formation methods of observer.
Background technique
With deepening continuously to intelligent driving vehicle research, single intelligent vehicle performance (imitate by such as load capacity, work
Rate, detection visual field etc.) finiteness be progressively exposed out, the ability of monomer can be overcome using the advantage that multi-agent synergy works
Limitation improves overall system performance, compares single intelligent body, and multi-agent system has irreplaceable superiority:
For complicated task and environment, multi-agent system can appoint complicated Task-decomposing at multiple simple sons
Business, is then distributed in different regions using multiple intelligent bodies and is worked at the same time, to improve working efficiency；
Multiple intelligent bodies are distributed in the biggish environment in region, surrounding environment are respectively perceived, by between intelligent body
The shared information respectively perceived of communication, greatly expands multi-agent system to the sensing range of environment；
The redundancy of multi-agent system quantitatively, can be improved the robustness of whole system；
Multi-agent system also has scalability, can be extended according to different requirements to itself, to complete new
Task.
Therefore, carry out the Collaborative Control research of more intelligent vehicles, there is highly important research significance, in more intelligent vehicles
In Collaborative Control research, common cooperative control method includes being formed with the navigator's method, Behavior-based control method, virtual structure method, artificial of following
Potential field method etc., these cooperative control methods can be divided into two kinds of frames: centralized frame and Distributed Architecture.Both frames one
As be all based on host-guest architecture, i.e., some intelligent vehicle in intelligent vehicle system, is being chosen more than one as host, other vehicles are made
For slave, connection is established between host and slave by wireless communication.
Centralized frame refers to be communicated between host and all slaves, all environmental informations of host grasp, and to
The advantages of all slaves send control signal and transmit data, centralized frame is that its is clear in structure, easy to accomplish, disadvantage
It is that system is excessively high to host dependency degree, when host breaks down, will lead to the paralysis of whole system, due to the concentration of signal
Processing and transmission can carry out great calculation amount to host tape and communication is born, therefore calculating to host and communication performance require very
The scalability of height, system is weaker.
Distributed structure/architecture refers to that host is only communicated with part slave, can also there is phase intercommunication between slave and slave
Letter, the communication topology of whole system exist in the form of a kind of digraph or non-directed graph, and each of system intelligent vehicle is only
Whole collaboration target is realized by obtaining the status information of its neighbour and itself, this distributed framework has flexible
Property it is good, have the advantages that stronger extended capability and fault-tolerant ability, the environment that can adapt to various change, in addition, distribution be
In system, it is generally not present biggish calculation amount and communication burden, is advised since distributed system solves integrated system in system
Mould existing various restriction problems when expanding, thus the research in relation to more intelligent vehicle Collaborative Controls at present is also in past distribution side
To development, wherein the distributed formation control technology of more intelligent vehicles receives the extensive pass of researcher because of its potential immense value
Note.
In the distributed formation control of more intelligent vehicles, due to the non-linear and complexity of auto model, distribution is compiled
The design of team's controller is often the Major Difficulties in research.With deepening continuously for Recent study personnel, it has been found that point
The introducing of cloth state observer can greatly reduce the design difficulty of distributed formation control device, because distributions are seen
The information that device can help all slaves to obtain host is surveyed, herein on basis, complicated distributed formation control problem is past
It is past to can simplify into a relatively simple bicycle control problem.In the research of distributions observer, the property of observer
It can often can judge from two angles: first, if it can converge to the true value of object being observed, second, it converges to
Time required for object being observed true value.In existing research, the observation of the true value of object being observed can be converged to
Device is generally divided into asymptotic convergence, exponential convergence and finite time convergence control by its convergence time or effect, wherein asymptotic convergence and
Exponential convergence requires the time and tends to infinitely great Shi Caineng and converge to true value, and finite time convergence control can be in a certain determination
True value is converged in time.Thus, distributed finite time state observer is a kind of more preferably observer.
In existing distributed finite time state observer, slave often directly observes the global position letter of host
Breath, but since the global position information that host itself can be provided generally relies on GPS acquisition, precision generally can only achieve rice
Grade, in addition the influence that the position error of slave itself and environmental factor (such as tunnel, high building) generate positioning accuracy, it will
Cause the accuracy of observation of existing distributed finite time state observer poor, the observation of the observer is applied to more intelligence
When the distributed formation control of energy vehicle, it may result in vehicle and collide, be unable to reach expected formation target.
Summary of the invention
It is an object of the present invention to overcome the above-mentioned drawbacks of the prior art and provide one kind to be had based on distribution
More intelligent vehicle formation methods of state observer between in limited time.
The purpose of the present invention can be achieved through the following technical solutions: one kind is based on distributed finite time state observation
More intelligent vehicle formation methods of device, comprising the following steps:
S1, according to intelligent vehicle kinematics model, the kinematics character of intelligent vehicle is described；
The client/server of S2, the more intelligent vehicles of building, and the topological structure based on directed spanning tree establishes more intelligent vehicles
Between communication network architecture；
The distributed finite time state observer of S3, design independent of world coordinates information, to obtain observation；
S4, observation is inputted into more intelligent vehicle distribution formation control devices, to realize the automatic formation of more intelligent vehicles.
Preferably, in the step S1 intelligent vehicle kinematics character are as follows:
Wherein, xiIndicate the lateral position of intelligent vehicle, yiIndicate the lengthwise position of intelligent vehicle, θiIndicate intelligent vehicle
Orientation angles,X is corresponded to respectivelyi, yi, θiDerivative, viIndicate the linear velocity of intelligent vehicle, ωiIndicate intelligence
The angular speed of vehicle.
Preferably, the step S2 specifically includes the following steps:
A vehicle in S21, the more intelligent vehicles of selection is as host, remaining vehicle is as slave；
S22, communication connection between communication connection, host and slave between slave is described respectively using digraph；
Preferably, the communication connection in the step S22 between slave specifically:
Wherein,Indicate slave digraph,Indicate that subordinate computer node, N indicate the quantity of subordinate computer node, ε is indicated between slave
The set of directed edge, i and j respectively indicate different subordinate computer nodes；
Communication connection between host and slave specifically:
Wherein,Indicate principal and subordinate's digraph,Indicate host node 0 and subordinate computer nodeUnion,It indicates between slave
The union of directed edge between directed edge and slave.
Preferably, the step S3 specifically includes the following steps:
S31, according to formation target, obtain the practical formation error of slave；
S32, slave is chosen to the estimated value of position of host machine and angle, obtain the estimation formation error of slave；
Relative position between S33, acquisition vehicle, and based on estimation formation error, design distributed finite time State Viewpoint
Device is surveyed, to obtain the observation comprising observation state and observation speed.
Preferably, formation target in the step S31 specifically:
Wherein, xi(t) and x0(t) lateral position of slave and host, y are respectively indicatedi(t) and y0(t) slave is respectively indicated
With the lengthwise position of host, θi(t) and θ0(t) angle of slave and host is respectively indicated,WithIt is opposite to respectively indicate slave
In the transverse direction amount of being desired offset from and longitudinal amount of being desired offset from of host；
Practical formation error are as follows:
Wherein,The actual lateral formation error of slave is respectively indicated, longitudinal formation error and angle are missed
Difference.
Preferably, it is chosen in the step S32As slave to position of host machine and angle [x0,y0,θ0]T's
Estimated value；
Estimate formation error are as follows:
Wherein,The lateral formation error, longitudinal formation error and angle for respectively indicating slave estimation are missed
Difference.
Preferably, the relative position in the step S33 between vehicle is obtained by laser radar and gyroscope, described
Relative position between vehicle specifically includes:
xji=xj-xi
yji=yj-yi
x0i=x0-xi
y0i=y0-yi
Wherein, xjiIndicate lateral distance of the slave j relative to slave i, yjiIndicate slave j relative to slave i it is longitudinal away from
From x0iIndicate lateral distance of the host relative to slave i, y0iIndicate fore-and-aft distance of the host relative to slave i；
The distributed finite time state observer of design are as follows:
sigα(p)=| p |αSgn (p), α > 0
Wherein, η1,η2,η3,η4,a1,a2,a3,a4For adjustable constant parameter, and meet η1,η2,η3,η4> 0 and 0
< a1,a2,a3,a4< 1；
It indicates the set of slave i and its neighbour, i.e., establishes the set of other slaves of communication connection with slave i；
aijThe communication link ad valorem between slave is indicated, if having communication connection between slave i and slave j, then aijIt is 1, otherwise
aijIt is 0；
biThe communication link ad valorem between host and slave is indicated, if there is communication connection between slave and host, then biIt is 1, it is no
Then biIt is 0；
Sgn (p) indicates the sign function of standard, when parameter p > 0, sgn (p)=1；When parameter p < 0, sgn (p)=- 1；
When parameter p=0, sgn (p)=0；
Obtained observation isWherein, observation state isObservation speed is
Preferably, distributed formation control implement body in the step S4 are as follows:
Wherein, whereinWithThe maximum line velocity and minimum linear velocity of the permission of host own controller are respectively indicated,WithThe maximum angular rate and minimum angular speed of the permission of host own controller are respectively indicated,WithIt is respectivelyConversion variable, vmaxAnd vminRespectively indicate the maximum line velocity and minimum linear velocity of intelligent vehicle, ωmaxIt indicates
The maximum angular rate of intelligent vehicle, k1, k2, k3It is the constant that can be set, and value is positive number；
Sat (a, b, c) is a saturation function, and parameter b and c are the bound of variable a respectively, if a > b, Sat (a,
B, c)=b；If a < c, Sat (a, b, c)=c；Otherwise Sat (a, b, c)=a.
Compared with prior art, the invention has the following advantages that
One, the present invention obtains the relative position between intelligent vehicle using laser radar sensor and gyroscope, and precision can
To reach grade, the accuracy of observer output observation can guarantee, observation is more nearly actual value, to effectively improve
The precision that intelligent vehicle is formed into columns.
Two, the present invention is based on digraph theories, construct the communication network topology between host and slave, slave, on the one hand
On the other hand the observation convergence that ensure that distributions observer can be reduced unnecessary communication connection in system.
It three, can be directly true to slave the present invention is based on estimation formation tolerance design distribution finite time state observer
Real formation error amount and the angle of host, speed, angular speed is observed, and guarantees that observation is received rapidly in finite time
True value is held back, i.e. observation error asymptotic convergence substantially reduces the influence that observation error forms into columns to intelligent vehicle, make intelligence in 0
Energy platooning can be rapidly reached target, while enhance the safety of intelligent vehicle formation.
Detailed description of the invention
Fig. 1 is flow chart of the method for the present invention；
Fig. 2 is the kinematics model of intelligent vehicle；
Fig. 3 is the communication network architecture in embodiment between intelligent vehicle；
Fig. 4 is the simulation result diagram that intelligent vehicle is formed into columns in embodiment；
Fig. 5 a observation error schematic diagram between the lateral formation error and actual value of observation state in embodiment；
Fig. 5 b observation error schematic diagram between the longitudinal formation error and actual value of observation state in embodiment；
Fig. 5 c observation error schematic diagram between the angular error and actual value of observation state in embodiment；
Fig. 6 a observation error schematic diagram between the linear velocity and actual value of observation speed in embodiment；
Fig. 6 b observation error schematic diagram between the angular speed and actual value of observation speed in embodiment；
Specific embodiment
The present invention is described in detail with specific embodiment below in conjunction with the accompanying drawings.
As shown in Figure 1, a kind of more intelligent vehicle formation methods based on distributed finite time state observer, including with
Lower step:
S1, according to intelligent vehicle kinematics model, the kinematics character of intelligent vehicle is described, wherein intelligent vehicle movement
Learn model as shown in Fig. 2, intelligent vehicle kinematics character are as follows:
In formula, xiIndicate the lateral position of intelligent vehicle, yiIndicate the lengthwise position of intelligent vehicle, θiIndicate intelligent vehicle
Orientation angles,X is corresponded to respectivelyi, yi, θiDerivative, viIndicate the linear velocity of intelligent vehicle, ωiIndicate intelligence
The angular speed of energy vehicle；
The client/server of S2, the more intelligent vehicles of building, and the topological structure based on directed spanning tree establishes more intelligent vehicles
Between communication network architecture, wherein the number of the group of multiple intelligent vehicles composition is [R0,R1,..,Ri..,RN], utilize master
Group is grouped from the thought of framework, one is chosen from group and is used as host, marked as R0, remaining is accordingly to be regarded as slave Ri,
In order to guarantee the stability of system, the root node of directed spanning tree is necessary for host R0, host R0With slave RiBetween by wireless
Communication network carries out data transmission, host R0Main function be to obtain global object, the entire Vehicular system of leader moves,
More intelligent vehicle groups of the present embodiment include host R0With slave R1~R5, communication network architecture is as shown in figure 3, from root node
Host R0To the slave R of any one other node1~R5Between all at least exist a directed connection channel；
The distributed finite time state observer of S3, design independent of world coordinates information, to obtain observation, tool
Body the following steps are included:
S31, according to formation target, obtain slave RiPractical formation error；
S32, slave R is choseniTo host R0The estimated value of position and angle obtains slave RiEstimation formation error；
Relative position between S33, acquisition vehicle, and based on estimation formation error, design distributed finite time State Viewpoint
Device is surveyed, to obtain the observation comprising observation state and observation speed；
Wherein, formation target are as follows:
In formula, xi(t) and x0(t) slave R is respectively indicatediWith host R0Lateral position, yi(t) and y0(t) it respectively indicates
Slave RiWith host R0Lengthwise position, θi(t) and θ0(t) slave R is respectively indicatediWith host R0Angle,WithTable respectively
Show slave RiRelative to host R0The transverse direction amount of being desired offset from and longitudinal amount of being desired offset from；
Practical formation error are as follows:
In formula,Respectively indicate slave RiActual transverse direction formation error, longitudinal formation error and angle
Error；
It choosesAs slave RiTo host R0Position and angle [x0,y0,θ0]TEstimated value, estimation form into columns miss
Difference are as follows:
In formula,Respectively indicate slave RiThe lateral formation error of estimation, longitudinal formation error and angle
Error；
Relative position between vehicle is obtained by laser radar and gyroscope, is specifically included:
In formula, xjiIndicate slave RjRelative to slave RiLateral distance, yjiIndicate slave RjRelative to slave RiLongitudinal direction
Distance, x0iIndicate host R0Relative to slave RiLateral distance, y0iIndicate host R0Relative to slave RiFore-and-aft distance；
The distributed finite time state observer of design are as follows:
sigα(p)=| p |αSgn (p), α > 0
In formula, η1,η2,η3,η4,a1,a2,a3,a4For adjustable constant parameter, and meet η1,η2,η3,η4> 0 and 0
< a1,a2,a3,a4< 1；
It indicates the set of slave i and its neighbour, i.e., establishes the set of other slaves of communication connection with slave i；
aijThe communication link ad valorem between slave is indicated, if having communication connection between slave i and slave j, then aijIt is 1, otherwise
aijIt is 0；
biThe communication link ad valorem between host and slave is indicated, if there is communication connection between slave and host, then biIt is 1, it is no
Then biIt is 0；
Sgn (p) indicates the sign function of standard, when parameter p > 0, sgn (p)=1；When parameter p < 0, sgn (p)=- 1；
When parameter p=0, sgn (p)=0；
Obtained observation isWherein, observation state isObservation speed is
S4, observation is inputted into more intelligent vehicle distribution formation control devices, to realize the automatic formation of more intelligent vehicles,
Wherein, distributed formation control implement body are as follows:
In formula, whereinWithThe maximum line velocity and minimum linear velocity of the permission of host own controller are respectively indicated,WithThe maximum angular rate and minimum angular speed of the permission of host own controller are respectively indicated,WithIt is respectivelyConversion variable, vmaxAnd vminRespectively indicate the maximum line velocity and minimum linear velocity of intelligent vehicle, ωmaxIt indicates
The maximum angular rate of intelligent vehicle, k1, k2, k3It is the constant that can be set, and value is positive number；
Sat (a, b, c) is a saturation function, and parameter b and c are the bound of variable a respectively, if a > b, Sat (a,
B, c)=b；If a < c, Sat (a, b, c)=c；Otherwise Sat (a, b, c)=a.
The present embodiment is using the communication network architecture between directed spanning tree building intelligent vehicle, it is however generally that, communication network
Topology can be divided into non-directed graph and digraph, and the communication connection of foundation required for the communication topology using digraph is than based on undirected
Communication topology will be lacked and (can generally reduce 50% or so), and the topological structure of use directed spanning tree is (based on root node need
Machine) it can on the one hand guarantee the observation convergence of designed distributions observer, it on the other hand can be in reduction system
Unnecessary communication connection；
It is mounted on laser radar and gyroscope on each intelligent vehicle of the present embodiment, wherein gyroscope is to each
A intelligent vehicle provides identical reference direction and angle information, and laser radar can provide each intelligent vehicle and its neighbour saves
Relative position between point, based on estimation formation errorEach slave RiHave using distribution shown in formula (6)
State observer is believed between in limited time to observe itself relative to the formation error of host and angle, speed, the angular speed of host etc.
Breath；
It carves at the beginning, each intelligent vehicle RiThe initial value that Host Status can be estimated with arbitrary initialEach intelligent vehicle RiIt can be obtained in real time by laser radar and gyroscope
Itself relative position [x between its neighbourj-xi,yj-ji]T(i.e. [xji,yji]T), and it is obtained by communication equipment in real time
Each neighbours' intelligent vehicle RjStatus informationIt is calculated in real time according to formula (6)Value, while updating each intelligent vehicle RiStatus informationThe frequency of update is to update once for every 0.01 second；
Slave is omitted in state observer shown in formula (6) to the angular speed state observer of host, this is because intelligence
The derivative of energy vehicle heading angleIt is the angular velocity omega of owni, in state observer, slave in order to real-time update from
Estimated value of the body to perspectiveIt needs to use intermediate variableThe intermediate variable is practical be exactly angular speed observation
The lateral formation error that each slave is observedLongitudinal formation errorAngular errorLinear velocityAngular speedIt is applied in the distributed formation control device of more intelligent vehicles, the wire velocity control device of input type (7) and angle speed
Controller formula is spent, more intelligent vehicles formation independent of world coordinates system can be realized.
In the present embodiment, the control parameter of more intelligent vehicle distribution formation control devices is respectively set as k1=1.5, k2
=0.05, k3=0.45, more intelligent vehicle formation simulation result diagrams are as shown in figure 4, be specifically by 1 host R0With with 5 slaves
R1~R5Distributed formation control effect of the formation troop constituted in 100s: formation target be by the formation troop from appoint
The original state (including any position and any angle) of meaning, by utilizing distributed finite time State Viewpoint proposed by the present invention
Device is surveyed, and combines distributed formation control device, realizes that all slaves can follow host motion, keeps desired formation with host
Formation (rectangle in such as Fig. 4, as form into columns during a certain moment formation), and guarantee system formation error asymptotic convergence in
0。
The convergence for proving the distributed finite time state observer that the present invention designs seeks to prove observationIts corresponding true value can be converged within finite timeWhereinIt is equal to
The angular velocity omega of intelligent vehiclei, it was demonstrated that process is as follows:
Proving first can be withIt is arrived in Finite-time convergenceFirst equation in formula (7) be equivalent to as
Under form:
It is available according to formula (4):
In conjunction with formula (8) and (9), may further obtain:
Choose a liapunov functionIt, can and to the liapunov function derivation
To obtain following formula:
According to stability in finite time theory, available Vi *It can be in finite timeWithin receive
It holds back to 0, this shows as t >=Ti *When, defined error variancePerseverance is 0；
DefinitionIt is available:
In formula (13), due to matrixIt is reversible, then as t >=Ti *When,Further according to formula
(4), it may further obtain:
In the same way, it can prove that there are finite time T**, as t >=T**When, Choose T0=max { T*,T**, then available:
By proving above, the finite time distributions designed by the present invention independent of world coordinates information are seen
The stability for surveying device is proven.
Pass through simulating, verifying, Fig. 5 a~5c observation error schematic diagram between observation state and actual value, by Fig. 5 a~5c
It is found that the lateral formation error of observationLongitudinal formation errorAngular errorIt is fast in the finite time less than 20s
Speed converges to actual value, i.e., it is to see in embodiment that the observation error between observation state value and actual value, which converges on 0, Fig. 6 a~6b,
Observation error schematic diagram between degree of testing the speed and actual value, by Fig. 6 a~6b it is found that the linear velocity of observationAnd angular speedSmall
In converging to actual value in the finite time of 20s rapidly, i.e. observation error between observation speed value and actual value converges on 0,
Shown in method proposed by the present invention by simulation result, the observation error of observer converges on 0, controls to final platooning
System influences almost ignore, and can be rapidly achieved expected formation target, and more intelligent vehicles volumes can be effectively improved by demonstrating the present invention
The precision and safety of team.
Claims (9)
1. a kind of more intelligent vehicle formation methods based on distributed finite time state observer, which is characterized in that including with
Lower step:
S1, according to intelligent vehicle kinematics model, the kinematics character of intelligent vehicle is described；
The client/server of S2, the more intelligent vehicles of building, and the topological structure based on directed spanning tree is established between more intelligent vehicles
Communication network architecture；
The distributed finite time state observer of S3, design independent of world coordinates information, to obtain observation；
S4, observation is inputted into more intelligent vehicle distribution formation control devices, to realize the automatic formation of more intelligent vehicles.
2. a kind of more intelligent vehicle formation sides based on distributed finite time state observer according to claim 1
Method, which is characterized in that the kinematics character of intelligent vehicle in the step S1 are as follows:
Wherein, xiIndicate the lateral position of intelligent vehicle, yiIndicate the lengthwise position of intelligent vehicle, θiIndicate the orientation of intelligent vehicle
Angle,X is corresponded to respectivelyi, yi, θiDerivative, viIndicate the linear velocity of intelligent vehicle, ωiIndicate intelligent vehicle
Angular speed.
3. a kind of more intelligent vehicle formation sides based on distributed finite time state observer according to claim 1
Method, which is characterized in that the step S2 specifically includes the following steps:
A vehicle in S21, the more intelligent vehicles of selection is as host, remaining vehicle is as slave；
S22, communication connection between communication connection, host and slave between slave is described respectively using digraph.
4. a kind of more intelligent vehicle formation sides based on distributed finite time state observer according to claim 3
Method, which is characterized in that the communication connection in the step S22 between slave specifically:
Wherein,Indicate slave digraph,Indicate that subordinate computer node, N indicate the quantity of subordinate computer node, ε indicates oriented between slave
The set on side, i and j respectively indicate different subordinate computer nodes；
Communication connection between host and slave specifically:
Wherein,Indicate principal and subordinate's digraph,Indicate host node 0 and subordinate computer nodeUnion,Indicate oriented between slave
The union of directed edge between side and slave.
5. a kind of more intelligent vehicle formation sides based on distributed finite time state observer according to claim 2
Method, which is characterized in that the step S3 specifically includes the following steps:
S31, according to formation target, obtain the practical formation error of slave；
S32, slave is chosen to the estimated value of position of host machine and angle, obtain the estimation formation error of slave；
Relative position between S33, acquisition vehicle, and based on estimation formation error, distributed finite time state observer is designed,
To obtain the observation comprising observation state and observation speed.
6. a kind of more intelligent vehicle formation sides based on distributed finite time state observer according to claim 5
Method, which is characterized in that formation target in the step S31 specifically:
Wherein, xi(t) and x0(t) lateral position of slave and host, y are respectively indicatedi(t) and y0(t) slave and master are respectively indicated
The lengthwise position of machine, θi(t) and θ0(t) angle of slave and host is respectively indicated,WithSlave is respectively indicated relative to master
The transverse direction amount of being desired offset from of machine and longitudinal amount of being desired offset from；
Practical formation error are as follows:
Wherein,Respectively indicate the actual lateral formation error of slave, longitudinal formation error and angular error.
7. a kind of more intelligent vehicle formation sides based on distributed finite time state observer according to claim 6
Method, which is characterized in that chosen in the step S32As slave to position of host machine and angle [x0,y0,θ0]TEstimate
Evaluation；
Estimate formation error are as follows:
Wherein,Respectively indicate the lateral formation error, longitudinal formation error and angular error of slave estimation.
8. a kind of more intelligent vehicle formation sides based on distributed finite time state observer according to claim 7
Method, which is characterized in that the relative position in the step S33 between vehicle is obtained by laser radar and gyroscope, described
Relative position between vehicle specifically includes:
xji=xj-xi
yji=yj-yi
x0i=x0-xi
y0i=y0-yi
Wherein, xjiIndicate lateral distance of the slave j relative to slave i, yjiIndicate fore-and-aft distance of the slave j relative to slave i,
x0iIndicate lateral distance of the host relative to slave i, y0iIndicate fore-and-aft distance of the host relative to slave i；
The distributed finite time state observer of design are as follows:
sigα(p)=| p |αSgn (p), α > 0
Wherein, η1,η2,η3,η4,a1,a2,a3,a4For adjustable constant parameter, and meet η1,η2,η3,η4> 0 and 0 < a1,
a2,a3,a4< 1；
It indicates the set of slave i and its neighbour, i.e., establishes the set of other slaves of communication connection with slave i；
aijThe communication link ad valorem between slave is indicated, if having communication connection between slave i and slave j, then aijIt is 1, otherwise aijFor
0；
biThe communication link ad valorem between host and slave is indicated, if there is communication connection between slave and host, then biIt is 1, otherwise bi
It is 0；
Sgn (p) indicates the sign function of standard, when parameter p > 0, sgn (p)=1；When parameter p < 0, sgn (p)=- 1；Parameter p
When=0, sgn (p)=0；
Obtained observation isWherein, observation state isObservation speed is
9. a kind of more intelligent vehicle formation sides based on distributed finite time state observer according to claim 8
Method, which is characterized in that distributed formation control implement body in the step S4 are as follows:
Wherein,WithThe maximum line velocity and minimum linear velocity of the permission of host own controller are respectively indicated,WithRespectively
Indicate the maximum angular rate and minimum angular speed that host own controller allows,WithIt is respectively's
Convert variable, vmaxAnd vminRespectively indicate the maximum line velocity and minimum linear velocity of intelligent vehicle, ωmaxIndicate intelligent vehicle
Maximum angular rate, k1, k2, k3It is the constant that can be set, and value is positive number；
Sat (a, b, c) is a saturation function, and parameter b and c are the bound of variable a respectively, if a > b, Sat (a, b, c)
=b；If a < c, Sat (a, b, c)=c；Otherwise Sat (a, b, c)=a.
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