CN104972860B - A kind of holographic Optimal Sliding Mode Control device for vehicle active suspension - Google Patents
A kind of holographic Optimal Sliding Mode Control device for vehicle active suspension Download PDFInfo
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Abstract
The present invention disclose a kind of holographic Optimal Sliding Mode Control device for vehicle active suspension, is made up of with the second solver the first solver, and it is which is input intohThe suspension motion state vector of 1 cycle of operation, output are thehThe Suspension control forcer controling power of individual cycle of operation,hIt is the integer more than 0；First solver is output as the input of the second solver, thehThe input of the first solver during individual cycle of operation ish1 cycle of operation suspension motion state vector and thehSuspension control forcer controling power U of 1 cycle of operation(h‑1)The extended mode vector that combination is formed, thehThe output of the second solver during individual cycle of operation is Suspension control forcer controling power, and input to suspension system is completed the of Active suspensionhSecondary control；The present invention considers all of suspension system arrangement information and expected performance information comprehensively, makes Active suspension control system obtain optimal performance and more preferable robust stability.
Description
Technical field
The invention belongs to vehicle suspension control field, more particularly to a kind of controller for vehicle active suspension, the control
Device processed is realized controlling to suspension by producing the active control forcer of active controlling force.
Background technology
Suspension is the general name of force transmission connections between carriage frame (or vehicle body) and axletree (or wheel).According to its work
Make the difference of principle, passive suspension, Active suspension and semi-active suspension can be divided into.Traditional passive suspension limits vehicle performance
Further lifted, semi-active suspension is expected to break through this restriction with Active suspension.Active suspension is on the basis of passive suspension
Increase an active control forcer that can produce active controlling force, be optimal can vehicle ride comfort.Control method
Belong to one of core technology of Active suspension, important impact is produced to the working effect of Active suspension.
Optimal performance and robust performance are to evaluate 2 good and bad leading indicators of control system action effect.Existing suspension
Control mainly includes optimum control, fuzzy control, PID control, sliding formwork control etc., and each control has the advantages that its own,
There is also corresponding deficiency.Optimum control can make suspension system that preferable performance, but robustness are obtained under nominal condition
It is not good enough；Although and fuzzy control and PID control cost are relatively low, having certain adaptive ability, control accuracy is not high enough, nothing
Method makes system obtain optimal performance.And sliding formwork control is a kind of very strong control method of robustness, individually or with other can control
Combination of Methods is used, but it can not make system obtain optimal performance.Sliding-mode control with there is two committed steps：Build
Sliding mode function designs sliding mode controller with according to the sliding mode function.
To obtain optimal performance and good robustness, optimum control is combined with sliding formwork control, formation is so-called most
Excellent sliding formwork control.Vadim I.Utkin exist《Sliding Modes in Control and Optimization》Page 137
Describe to page 139 as follows according to the concrete grammar of Optimal Sliding Mode Control method structure Optimal Sliding Mode manifold function.
1) ask for the state equation of linear systemWith evaluate good and bad secondary of its work
Type performance indicationsWherein X0It is the state vector of n × 1 rank；U0
It is the dominant vector of m × 1 rank；W0It is the perturbation vector of l × 1 rank；A0It is the state matrix of n × n rank；B0It is
The control matrix of one n × m rank；G0It is the interference matrix of n × l rank；Q0It is the state variable weighting square of n × 1 rank
Battle array；N0It is the crossed weight matrix of n × m rank；R0It is the controlled quentity controlled variable weighting matrix of m × m rank；T is net cycle time；t
It is time variable.
2) for state equation and quadratic performance index, build Optimal Sliding Mode flow pattern functionWherein S0Optimal Sliding Mode flow pattern function is represented, system motion state should be from both sides
It is intended to sliding formwork flow pattern function S0=0.ImIt is the unit matrix of m × m rank；T is the nonsingular square matrix of n × n rank, is metA011It is the matrix of one (n-m) × (n-m) ranks, meetsQ011Be one (n-m) ×
(n-m) matrix of rank, Q022It is the matrix of m × m rank, meets P is Li Kati
The unique solution of matrix differential equation, multitude's card put forward matrix differential equation satisfaction
According to the Optimal Sliding Mode flow pattern function S of above-mentioned structure0To design the Optimal Sliding Mode Control device for being applied to Active suspension,
Although the controller can make sliding formwork flow pattern function S0Move near 0, but sliding formwork flow pattern function S0Do not examine in the design process
ConsiderIn A021、A022Comprising part suspension system arrangement information, n × m ranks crossed weight
Matrix N0And the controlled quentity controlled variable weighted matrix R of m × m ranks0Comprising part suspension system expect information.These suspension frame structures are believed
The disappearance of breath causes controller just to lost necessary data in the design process, it is impossible to intactly, definitely describe suspension system
The base attribute of system；And the disappearance of suspension expected performance then causes controller in or not up to expectation dissatisfied to systematic function
In the case of requirement, have references to the performance indications that there is error in itself carries out Real-time Feedback, therefore, according to Optimal Sliding Mode
Flow pattern function S0Come design the controller for being applied to Active suspension cannot make Active suspension obtain real nominal optimal performance with
Good robustness.
The content of the invention
For the existing Optimal Sliding Mode Control device for being applied to Active suspension in its Optimal Sliding Mode flow pattern function building process
Lost part structure and expected performance information, and cause to be made actively according to the controller of the Optimal Sliding Mode flow pattern function design
It is suspended under nominal condition and obtains optimal performance, and the poor defect of robustness under conditions of variable working condition, present invention offer
A kind of holographic Optimal Sliding Mode Control device for not losing any system structure and expected performance information, ensures that Active suspension is obtained
Robust performance under the conditions of real name optimal performance and more preferable variable working condition.
To achieve these goals, the holographic Optimal Sliding Mode Control device for vehicle active suspension of the present invention is adopted
Technical scheme be：The present invention is made up of with the second solver the first solver, and its input is the suspension of h-1 cycle of operation
System motion state vector X(h-1), its output be h-th cycle of operation Suspension control forcer controling power U(h), h be more than
0 integer；First solver is output as the input of the second solver, the input of the first solver during h-th cycle of operation
It is suspension motion state vector X(h-1)With Suspension control forcer controling power U of h-1 cycle of operation(h-1)Combination
Form the suspension motion state vector of extensionThe output of the second solver during h-th cycle of operation
It is Suspension control forcer controling power U(h), by U(h)It is input into suspension system and completes the h secondary controls of Active suspension.
The input of first solver is computed restraining Ue(h)=(Kes+Keb)X1(h-1)Output matrix U after calculatinge(h), Kes、
KebHomogeneous control matrix-vector is extended respectively with extension compensation control matrix-vector, X1(h-1)It is the suspension motion of extension
State vector.
It is described to extend homogeneous control matrix-vector KesWith extension compensation control matrix-vector KebIt is：According to the state side of suspension system
JourneyAnd secondary Performance Evaluating Indexes functionBuild extended mode square
Battle array A1With J is rewritten it isUse transformation matrixCalculate regularization to expand
Exhibition state matrixWith regularization extended mode variable weighting matrix
And piecemeal, use Riccati equation
Ask for multitude's card and put forward solution vector Pe, solution vector P is put forward with multitude's cardeBuild extension Optimal Sliding Mode manifold functionWillIt is abbreviated as Ke, with reference to
Sliding formwork Reaching LawTry to achieve the homogeneous control matrix-vector K of extensiones=-(KeB1)-1KeA1With extension compensation control
Matrix-vector K processedeb=-(KeB1)-1λeKe；Wherein：X is suspension motion state vector, and U is Suspension control forcer control
Power processed, W is perturbation vector, and A is state matrix, and B is control matrix, and G is interference matrix, and Q is state variable weighting matrix, and N is
Crossed weight matrix, R are controlled quentity controlled variable weighting matrixs, IMIt is and the rank such as A
Unit matrix, I is the unit matrix with the rank such as R,T is net cycle time.
The present invention is had an advantageous effect in that after adopting above-mentioned technical proposal：With by existing Optimal Sliding Mode Control method design
Active suspension control device compare, the present invention is by the first solver (extension Optimal Sliding Mode solver) and the second solver
(curved-edge polygons solver) performs complete set Optimal Sliding Mode Control flow process, considers all of suspension system arrangement information and phase comprehensively
Performance information is hoped, so that Active suspension control system obtains real nominal optimal performance and more preferable robust stability.
Description of the drawings
Fig. 1 is a kind of construction block diagram of the holographic Optimal Sliding Mode Control device for vehicle active suspension of the present invention；
Fig. 2 is control principle schematic diagram when being applied to vehicle active suspension when h secondary controls are circulated of the present invention；
Fig. 3 is that the Active suspension of existing Optimal Sliding Mode Control device control (is controlled according to the design of existing Optimal Sliding Mode Control method
The Active suspension of device processed control), the Active suspension that controls of the holographic Optimal Sliding Mode Control device that provides of the present invention be passively suspended in
Suspension quadratic performance index comparison diagram under nominal condition；
Fig. 4 is the Active suspension of existing Optimal Sliding Mode Control device control, the holographic Optimal Sliding Mode Control device of present invention offer
The Active suspension of control be passively suspended in become spring carried mass in the case of suspension quadratic performance index comparison diagram；
Fig. 5 is the Active suspension of existing Optimal Sliding Mode Control device control, the holographic Optimal Sliding Mode Control device of present invention offer
The Active suspension of control and the suspension quadratic performance index comparison diagram being passively suspended under change tire stiffness；
Fig. 6 is the Active suspension of existing Optimal Sliding Mode Control device control, the holographic Optimal Sliding Mode Control device of present invention offer
The Active suspension of control and the suspension quadratic performance index comparison diagram being passively suspended under change speed.
In figure：1. suspension equivalent spring；2. spring carried mass；3. suspension damping；4. spring carried mass motion state sensor；5.
Holographic Optimal Sliding Mode Control device；6. wheel mass motion state sensor；7. Suspension control forcer；8. wheel mass；9.
Tire equivalent spring；10. the first solver；11. second solvers.
Specific embodiment
As shown in figure 1, the present invention for vehicle active suspension holographic Optimal Sliding Mode Control device 5 by the first solver 10 and
Second solver 11 is constituted, and the first solver 10 is extension Optimal Sliding Mode solver, and the second solver 11 is that curved-edge polygons are solved
Device.The input of holographic Optimal Sliding Mode Control device 5 is suspension motion state vector X of h-1 cycle of operation(h-1), it is holographic
The output of Optimal Sliding Mode Control device 5 is Suspension control forcer controling power U of h-th cycle of operation(h), h is whole more than 0
Number.First solver 10 is output as the input of the second solver 11, the input of the first solver 10 during h-th cycle of operation
It is suspension motion state vector X of h-1 cycle of operation(h-1)Occur with the suspension manipulating forces of h-1 cycle of operation
Device controling power U(h-1)Combination forms extended mode vectorThe second solver 11 during h-th cycle of operation
Output be Suspension control forcer controling power U(h).By Suspension control forcer controling power U(h)It is input into suspension system,
Complete the h secondary controls of Active suspension.
First solver 10 is for its inputIt is computed restraining Ue(h)=(Kes+Keb)X1(h-1)Calculate
Go out matrix Ue(h), wherein, Kes、KebHomogeneous control matrix-vector is extended respectively with extension compensation control matrix-vector.By matrix Ue(h)
Used as the input of the second solver 11, the second solver 11 is for its input Ue(h), it is computed ruleHold
Row is solved and is calculated, and Suspension control forcer controling power U is exported after calculating(h)；A and b are the integer more than 0,For U(h)'s
Derivative.
The homogeneous control matrix-vector K of extensionesWith extension compensation control matrix-vector KebIt is the constant value unrelated with cycle-index
Vector, its acquiring method is：
1) state equation of suspension system is asked for firstAnd secondary Performance Evaluating Indexes functionWherein X is state vector；U is dominant vector；W is perturbation vector；A is suspension
Systematic observation matrix；B is suspension system control matrix；G is interference matrix；Q is state variable weighting matrix；N is crossed weight
Matrix；R is controlled quentity controlled variable weighting matrix；T is net cycle time；T is time variable.
X=(x1,x2,x3,x4)T,x1=z1-q,x2=z2-z1,
G=[- 100 0]T,U=[u],
m1For body quality, m2For tire quality；k1For tire equivalent stiffness, k2For suspension equivalent stiffness, csHinder for suspension
Buddhist nun's coefficient；U is suspension system controling power；z1For analysis of wheel vertical displacement,For analysis of wheel vertical speed,Accelerate for analysis of wheel vertical
Degree；z2For vehicle body vertical displacement；For vehicle body vertical speed,For vehicle body normal acceleration.Road surfaces of the wherein q for suspension system
Displacement is input into, and meetsReference frequency n0=0.1m-1, w be road surface white noise function, Gq
(n0) for reference frequency n0Under road surface spectrum, v is Vehicle Speed, lower limiting frequency f0=0.011*v；δ1And δ2Point
It is not to move the related weight coefficient of degree of disturbing to wheel dynamic deformation and suspension；x1=z1- q is that wheel moves deformation, x2=z2-z1It is suspension
Dynamic deflection,It is analysis of wheel vertical speed,Vehicle body vertical speed, they by spring carried mass motion state sensor with
Wheel mass motion state sensor is measured.
2) build extended mode matrix A1With rewrite J,I is the unit matrix with the rank such as R；RewriteQ1It is extended mode variable weighting matrix, meets
X1Extended mode vector, meets
3) utilize transformation matrixCalculate regularization extended mode matrix
With regularization extended mode variable weighting matrixAnd piecemeal, IMIt is and the rank such as A
Unit matrix, AMThe 1st row matrix in block form A of the 1st rowM11And QMThe 1st row matrix in block form Q of the 1st rowM11With the rank such as A (or Q)；AM's
The 2nd row matrix in block form A of 2nd rowM22And QMThe 2nd row matrix in block form Q of the 2nd rowM22With the rank such as R；AMThe 2nd row matrix in block form of the 1st row
AM12And QMThe 2nd row matrix in block form Q of the 1st rowM12With the rank such as B；AMThe 1st row matrix in block form A of the 2nd rowM21And QMThe 2nd row the 1st
Row matrix in block form QM21With the rank such as N.Now have：AM11=A, AM12=bB, QM11=Q, QM12=bN, QM22=b2R。
4) utilize Riccati equation
Ask for multitude's card and put forward solution vector Pe；Then utilize PeBuild extension Optimal Sliding Mode manifold functionWillIt is abbreviated as Ke, with reference to cunning
Mould Reaching Law(λeFor positive number) ask for KesWith KebRespectively Kes=-(KeB1)-1KeA1And Keb=-
(KeB1)-1λeKe, extend dominant vectorX1It is extended mode vector, meets
The present invention is used to control 1/4 car two degrees of freedom car for the holographic Optimal Sliding Mode Control device 5 of vehicle active suspension
During active suspension system, holographic Optimal Sliding Mode Control device 5 is connected to into Suspension control forcer 7, spring carried mass fortune
Dynamic state sensor 4 and wheel mass motion state sensor 6.As shown in Fig. 2 1/4 car two degrees of freedom vehicle active suspension system
In vertical direction, wheel mass 8 constitutes wheel with tire equivalent spring 9 to system, and wheel is located at the lower section of spring carried mass 2, wheel
Suspension equivalent spring 1, suspension damping 3 and Suspension control forcer 7 are parallel between quality 8 and spring carried mass 2, wheel is direct
With ground interaction and make suspension produce vibration；Spring carried mass motion state sensor 4 is fixed with spring carried mass 2,
Wheel mass motion state sensor 6, spring carried mass motion state sensor 4 and wheel matter are fixed with wheel mass 8
Amount motion state sensor 6 is connected to holographic Optimal Sliding Mode Control device 5, Suspension control forcer 7 each via holding wire
Holographic Optimal Sliding Mode Control device 5 is connected to by holding wire, holographic Optimal Sliding Mode Control device 5 passes through Suspension control forcer 7
Suspension system is realized controlling.
Holography Optimal Sliding Mode Control device of the invention 5 considers all of suspension system arrangement and expected performance information, therefore
Real nominal optimal performance and good variable working condition robustness can be obtained.
During practical application, the parameter of suspension system is：Suspension Construction Parameters：Body quality m1=350kg, tire quality m2=
5000kg, tire equivalent stiffness k1=300000N/m, suspension equivalent stiffness k2=505000N/m, suspension damping coefficient cs=
30150Ns/m.The nominal condition of vehicle is to be travelled with the speed of travel speed v=20m/s on C level highways, i.e. road surface spectrum
Gq(n0)=256 × 10-6m2/m-1, weight coefficient δ1=52894, weight coefficient δ2=4405.1, a=1, b=0.001.
In Fig. 3,4,5,6, curve COSMC, Passive, HOSMC are each respectively to represent what existing Optimal Sliding Mode Control device was controlled
The Active suspension controlled by Active suspension, passive suspension and present invention holography Optimal Sliding Mode Control device 5, in each figure, vertical coordinate is main
Dynamic suspension J, abscissa are time coordinate t.
As shown in Figure 3, it is shown that Active suspension, passive suspension and the present invention that existing Optimal Sliding Mode Control device is controlled is holographic
Suspension quadratic performance index of the Active suspension controlled by Optimal Sliding Mode Control device 5 under nominal condition compares.It is existing optimum sliding
The more passive suspension of suspension property of the Active suspension of mould controller control is also poor, and according to holography Optimal Sliding Mode Control of the invention
The Active suspension J values controlled by device 5 obtain minimum, you can make suspension system obtain real nominal optimal performance.
As shown in Figure 4, it is shown that the Active suspension of existing Optimal Sliding Mode Control device control and present invention holography Optimal Sliding Mode
Active suspension and be passively suspended in spring carried mass m that controller 5 is controlled2When working in the case of=6500kg, institute of the present invention
The Active suspension for stating the holographic control of Optimal Sliding Mode Control device 5 makes suspension system quadratic performance index J minimum.
As shown in Figure 5, it is shown that the Active suspension of existing Optimal Sliding Mode Control device control and present invention holography Optimal Sliding Mode
Active suspension and be passively suspended in change tire stiffness k that controller 5 is controlled2When working in the case of=656500N/m, and
The Active suspension controlled by holographic Optimal Sliding Mode Control device of the present invention 5 makes suspension system quadratic performance index J minimum.As schemed
Shown in 6, it is shown that the Active suspension of existing Optimal Sliding Mode Control device control and 5 institute of holographic Optimal Sliding Mode Control device of the present invention
The Active suspension of control and when being passively suspended in C levels road surface and going up the speed of 26m/s respectively and travel, is equally of the present invention complete
The Active suspension controlled by breath Optimal Sliding Mode Control device 5 makes suspension system quadratic performance index J less.
From Fig. 3-6：Compared with existing Optimal Sliding Mode Control device, using holographic Optimal Sliding Mode Control of the present invention
When device 5 is controlled to suspension control system, suspension control system can be made to obtain real nominal optimal performance and more preferable Shandong
Rod.
Claims (5)
1. a kind of holographic Optimal Sliding Mode Control device for vehicle active suspension, is characterized in that：The holographic Optimal Sliding Mode Control
Device is made up of with the second solver the first solver, and its input is the suspension motion state vector of h-1 cycle of operation
X(h-1), output be h-th cycle of operation Suspension control forcer controling power U(h), h is the integer more than 0；First solver
The input of the second solver is output as, the input of the first solver during h-th cycle of operation is suspension motion state
Vectorial X(h-1)With Suspension control forcer controling power U of h-1 cycle of operation(h-1)Combination forms the suspension system of extension
Motion state vectorThe output of the second solver during h-th cycle of operation is Suspension control forcer
Controling power U(h), by U(h)It is input into suspension system and completes the h secondary controls of Active suspension.
2. holographic Optimal Sliding Mode Control device according to claim 1, is characterized in that：The input of first solver is computed
Rule Ue(h)=(Kes+Keb)X1(h-1)Output matrix U after calculatinge(h), Kes、KebHomogeneous control matrix-vector and extension are extended respectively
Compensation control matrix-vector, X1(h-1)It is the suspension motion state vector of extension.
3. holographic Optimal Sliding Mode Control device according to claim 2, is characterized in that：The input of second solver is computed
RuleSuspension control forcer controling power U is exported after calculating(h)；A and b are the integer more than 0,For U(h)Derivative, YeH () is U(h)Calculating rule.
4. holographic Optimal Sliding Mode Control device according to claim 3, is characterized in that：According to the state equation of suspension systemAnd secondary Performance Evaluating Indexes functionBuild extended mode matrix
A1With J is rewritten it isUse transformation matrixCalculate regularization extension shape
State matrixWith regularization extended mode variable weighting matrixAnd
Piecemeal, uses Riccati equationAsk for multitude's card
Put forward solution vector Pe, solution vector P is put forward with multitude's cardeBuild extension Optimal Sliding Mode manifold functionWillIt is abbreviated as Ke, with reference to sliding formwork Reaching LawTry to achieve the homogeneous control square of extension
Battle array vector Kes=-(KeB1)-1KeA1With extension compensation control matrix-vector Keb=-(KeB1)-1λeKe；Wherein：X is suspension system
Motion state vector, U are Suspension control forcer controling powers, and W is perturbation vector, and A is state matrix, and B is to control matrix, G
It is interference matrix, Q is state variable weighting matrix, and N is crossed weight matrix, and R is controlled quentity controlled variable weighting matrix, IMIt is the unit matrix with the rank such as A, I is the unit matrix with the rank such as R,T is net cycle time, λeFor positive number.
5. holographic Optimal Sliding Mode Control device according to claim 4, is characterized in that：
Suspension motion state vector X=(x1,x2,x3,x4)T,x1=z1-q,x2=z2-z1, G=[- 100 0]T,
U=[u],
m1For body quality, m2For tire quality；k1For tire equivalent stiffness, k2For suspension equivalent stiffness, csFor suspension damping system
Number；U is suspension system controling power；z1For analysis of wheel vertical displacement,For analysis of wheel vertical speed,For analysis of wheel vertical acceleration；z2For
Vehicle body vertical displacement；For vehicle body vertical speed,For vehicle body normal acceleration, pavement displacement inputs of the q for suspension system, w
For road surface white noise function, v is Vehicle Speed, x1=z1- q is that wheel moves deformation, x2=z2-z1It is suspension dynamic deflection,It is analysis of wheel vertical speed,It is vehicle body vertical speed,For the first derivative of q, δ1And δ2It is become dynamic with wheel respectively
Shape moves the related weight coefficient of degree of disturbing to suspension.
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| CN108312800B (en) * | 2018-01-23 | 2019-12-13 | 广州大学 | structural control method and control device for automobile active suspension system |
| CN108909396B (en) * | 2018-06-29 | 2020-11-03 | 四川理工学院 | Integrated control device for automobile active suspension and electric power steering system and working method |
| CN112606648B (en) * | 2020-12-28 | 2022-04-26 | 江苏大学 | Construction method of energy feedback type hybrid electromagnetic active suspension composite controller |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1593961A (en) * | 2004-06-29 | 2005-03-16 | 重庆大学 | Automobile semi-active pendant damping control method based on wavelet decomposition |
| EP1932694A1 (en) * | 2006-12-11 | 2008-06-18 | Peugeot Citroën Automobiles Sa | Method for optimising the control logics of suspension systems |
| KR101138758B1 (en) * | 2008-12-03 | 2012-04-24 | 한양대학교 산학협력단 | Method for robust design optimization for ride comfort |
| CN103072440A (en) * | 2013-01-21 | 2013-05-01 | 哈尔滨工业大学 | Control method for automotive active suspension system |
| CN103407341A (en) * | 2013-08-05 | 2013-11-27 | 江苏大学 | Active suspension support vector machine generalized compound inverse controller and construction method thereof |
| CN103754081A (en) * | 2013-12-27 | 2014-04-30 | 广西科技大学 | Optimal fuzzy complex control method of vehicle nonlinear suspension system |
-
2015
- 2015-01-23 CN CN201510034375.4A patent/CN104972860B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1593961A (en) * | 2004-06-29 | 2005-03-16 | 重庆大学 | Automobile semi-active pendant damping control method based on wavelet decomposition |
| EP1932694A1 (en) * | 2006-12-11 | 2008-06-18 | Peugeot Citroën Automobiles Sa | Method for optimising the control logics of suspension systems |
| KR101138758B1 (en) * | 2008-12-03 | 2012-04-24 | 한양대학교 산학협력단 | Method for robust design optimization for ride comfort |
| CN103072440A (en) * | 2013-01-21 | 2013-05-01 | 哈尔滨工业大学 | Control method for automotive active suspension system |
| CN103407341A (en) * | 2013-08-05 | 2013-11-27 | 江苏大学 | Active suspension support vector machine generalized compound inverse controller and construction method thereof |
| CN103754081A (en) * | 2013-12-27 | 2014-04-30 | 广西科技大学 | Optimal fuzzy complex control method of vehicle nonlinear suspension system |
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