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ResearchArticle 
Adaptivebacksteppingslidingmodecontrolwithfuzzymonitoring 
strategyforakindofmechanicalsystem 
Zhankui Song n, KaibiaoSun 
Faculty ofElectronicInformationandElectricalEngineering,DalianUniversityofTechnology,GanjingziDistrict,Dalian116024,China 
a rticleinfo 
Article history: 
Received2September2012 
Receivedinrevisedform 
26 July2013 
Accepted29July2013 
Availableonline21September2013 
This paperwasrecommendedfor 
publication byDr.A.B.Rad 
Keywords: 
Backstepping 
Sliding modecontrol 
Fuzzy monitoringstrategy 
Finite-time 
a b s t r a c t 
A noveladaptivebacksteppingslidingmodecontrol(ABSMC)lawwithfuzzymonitoringstrategyis 
proposed forthetracking-controlofakindofnonlinearmechanicalsystem.TheproposedABSMC 
scheme combiningtheslidingmodecontrolandbacksteppingtechniqueensurethattheoccurrenceof 
the slidingmotionin finite-time andthetrajectoryoftracking-errorconvergetoequilibriumpoint.To 
obtain abetterperturbationrejectionproperty,anadaptivecontrollawisemployedtocompensatethe 
lumped perturbation.Furthermore,weintroducefuzzymonitoringstrategytoimproveadaptivecapacity 
and softenthecontrolsignal.Theconvergenceandstabilityoftheproposedcontrolschemeareproved 
by usingLyaponov′s method.Finally,numericalsimulationsdemonstratetheeffectivenessofthe 
proposed controlscheme. 
& 2013ISA.PublishedbyElsevierLtd.Allrightsreserved. 
1. Introduction 
Controllerfornonlinearmechanicalsystemarewidelyused 
and implementedintheindustryinordertoimprovemechanical 
systemperformance.However,thereexistexternaldisturbance, 
parametervariationsandsystemuncertaintyinharshenviron- 
ments, whichconsequentlydegradetheperformanceofthe 
control system.Therefore,aclosed-loopcontrolsystemisessential 
for improvingtheperformanceofthemechanicalsystemthrough 
effectivelycompensatingfortheuncertaintyandexternaldistur- 
bances incontrolefforts.Variousnonlinearcontrolmethodshave 
been proposedforsolvingthisproblem,includingslidingmode 
control [1–5], backsteppingcontrol [8–12], intelligentcontrol 
[13–18], etc. 
Slidingmodecontrolhaslongproveditsinterestsandithas 
gainedmuchmoreattentionforitsrobustnessagainstparameter 
variationsandexternaldisturbance.SMCisnotonlyaneffective 
methodforcontrollingnonlinearsystemsbutalsocanbeconsidered 
as asynthesisprocedure.TheconventionalSMCdesignapproach 
consistsoftwosteps.First,aslidingmodesurfaceisdesignedsuch 
thatthesystemtrajectoryalongthesurfaceobtainscertaindesired 
properties.Then,adiscontinuouscontrol(switchcontrolterm)is 
design suchthatthesystemtrajectoriesreachtheslidingmode 
surfacein finitetime [6,7].SMCasageneraldesigntoolforcontrol 
nonlinear mechanicalsystemhasbeenwellestablished,theprimary 
advantagesofSMCare:(i)Goodrobustnessandgoodtransient 
performance;(ii)fastconvergencerateandhighcontrolprecision. 
(iii)Thepossibilityofstabilizing some complexnonlinearsystems 
which aredifficulttostabilizebycontinuousstatefeedbacklaws. 
Thebacksteppingapproachisanonlineartechniquewidelyused 
incontroldesign.Themultipleadvantagesofthisapproachinclude 
itslargesetofgloballyandasymptoticallystabilizingcontrollaws 
anditscapabilitytoimproverobustnessandsolveadaptivepro- 
blems.Backsteppingslidingmodecontrolinvolvesdividinganon- 
linearsystemintomanysubsystems.Thecontrollerisdesignedto 
achieveslidingmodecontrolforeachsubsystem.TheLyapunov 
functionisusedtoguaranteetheconvergenceoftheposition 
trackingerrorforallpossibleinitialconditions.Theaddedintegrator 
withbacksteppingcontrolimprovesthesystem′s robustnessagainst 
modelinguncertaintiesandexternaldisturbances,thusimproving 
the accuracyofsteady-statecontrol [8]. In [9], anintelligentback- 
steppingslidingmodecontrolscheme usingRBFNisproposedto 
design two-axismotioncontrolsystem.Andthisstrategy,usingRBFN 
which approximatetheupperboundedofthedisturbance.In 
[10–12],anbacksteppingslidingmodetechniqueforaradialpiston 
airmotorballscrewtableisdevelopedtoaccomplishaccurate 
desiredtrackingposition.Theresultsoftheseexperimentshowthat 
backsteppingslidingmodecontrollerapparentlysuppressesover- 
shootandprovidesaccuratepositioningperformance. 
As mentionedbefore,thereareseveralbacksteppingsliding 
mode controlmethodswithapplication.However,themajorityof 
these worksarebasedontheknowledgeoftheupperboundsof 
Contents listsavailableat ScienceDirect 
journalhomepage: www.elsevier.com/locate/isatrans 
ISATransactions 
0019-0578/$-seefrontmatter & 2013ISA.PublishedbyElsevierLtd.Allrightsreserved. 
http://dx.doi.org/10.1016/j.isatra.2013.07.017 
n Corresponding author.Tel.: þ86 13644257882. 
E-mail addresses: songzhankuiwudi@163.com, 
songzhankui@mail.dlut.edu.cn (Z.Song). 
ISA Transactions53(2014)125–133
disturbance, asymptoticconvergenceoftracking-errorandthe 
usage offunctionsignwhichinvolveshighfrequenciesarepresent 
in thecontrol.Theseinconveniencesmakeverydifficult tousein 
the application.Inthispaper,anoveladaptivebackstepping 
sliding modecontrollawwithfuzzymonitoringstrategyis 
proposed forthetracking-controlofakindofnonlinearmechan- 
ical system.First,anappropriateslidingmodesurfaceiscon- 
structed, anditprovidessufficient flexibilitytoshapetheresponse 
of positiontracking-error.Then,theABSMCschemeisproposed, 
and itiscomposedofthenominalcontrolterm,robustcontrol 
term andcompensatedcontrolterm.Toobtainabetterperturba- 
tion rejectionproperty,adaptivecompensatedcontrollawis 
employedtocompensatelumpedperturbation.Thus,itrelaxthe 
requirementoftheboundoflumpedperturbation.Furthermore, 
we employthefuzzymonitoringstrategytobothimproveadap- 
tivecapacityandeliminatethehighfrequencies.Theproposed 
controlschemeensuresthattheoccurrenceoftheslidingmotion 
in finite-time andthetrajectoryoftracking-errorconvergeto 
equilibriumpoint.Therefore,itimprovestheperformancethe 
dynamic response.Themajorcontributionsofthispaperarethe 
following: 
(i) Theproposedcontrolstrategyisappliedtoensuringthe 
occurrenceoftheslidingmotionina finitetime,whichcan 
hold thecharacteroffasttransientresponseandimprovethe 
trackingaccuracy. 
(ii) Anadaptivecompensatedcontroltermisadoptedinthe 
proposedcontrolscheme,itprovidesthecompletecompen- 
sation oflumpedperturbation,anditrelaxtherequirementof 
the boundoflumpedperturbation. 
(iii) Afuzzymonitoringstrategyisintroducedtoimproveadaptive 
capacity,anditsoftensthecontrolsignal. 
The organizationofthispaperisdescribedasfollows.Inthe 
nextsection,thedynamicsofanonlinearmechanicalsystemis 
derived,andtheproblemstatementisalsogiven.In Sections 2 and 
3, thedesignoftheABSMCisdiscussed.In Section 4, simulation 
result showtheprecisecontrolisaccomplishedbasedonthe 
proposed method.Conclusionispresentedin Section 5. 
2. Problemformulation 
The generalmodelofsecond-ordermechanicalsystemsis 
described asthefollowing 
m€qþω_qþμð_qÞþbðq; _qÞþd ¼ τ ð1Þ 
where qARn is avectorofgeneralizedcoordinates; m and ω are 
parametersofthenonlinearmechanicalsystem; μð_qÞ and bðq; _qÞ arethecoulombfrictionandsystemuncertainty,respectively; 
d and τ aretheexternaldisturbanceandcontrolinput,respec- 
tively.Notethat μð_qÞ ¼ μ0ð_qÞþΔμð_qÞ, where μ0ð_qÞ and Δμð_qÞ are 
the nominalpartanduncertaintypart,respectively. 
Introducingthevariables x1 ¼ q and x2 ¼ _q, thendynamic 
system (1) can berewrittenas 
_x1 ¼ x2 
_x2 ¼ f ðx1; x2ÞþDþg  τ ð2Þ 
where g ¼m1, f ðx1; x2Þ¼g  ½ω  x2þμ0ðx2Þ and D¼g  
½Δμðx2ÞþΔbðx1; x2Þþd is calledlumpedperturbation. 
Without lossofgenerality,thetechnicalassumptionsaremade 
to posetheprobleminatractablemanner 
Assumption 1. The desiredcommandsignalandtheir first and 
second timederivativesarebounded. 
Assumption2. Thelumpedperturbation D is bounded,i.e., jDjrα, 
where α40 isunknownnumber. 
Assumption3. There existsapositivenumber αn such that 
maxfα; ^ αgrαn, where ^ α is introducedtoestimate α, and ^ α will 
be givenlater.Here,define α~ ¼ α^αn, thenwecanobtain α~ r0. 
Before themainanalysis,somelemmaswhichwillbeusedin 
stability anddesignofcontrolleraregivenasfollows. 
Lemma 1. [13]: Considerthesystem 
_x¼ f ðxÞ; f ð0Þ ¼ 0; xARn; xð0Þ ¼ x0 ð3Þ 
where f : D-Rn is continuousonanopenneighborhood D and the 
origin is0.Supposethereisacontinuousfunction VðxÞ : D-R 
defined on UDD with theorigin0suchthatthefollowing 
conditions hold: 
1. VðxÞ is positivedefiniteon DDRn; 
2.Thereexistrealnumbers k40 and νAð0; 1Þ, suchthat _V 
ðxÞþk 
Vν 
ðxÞr0,andthen,system (3) islocally finite-timestable.The 
settlingtime,dependingontheinitialstate xð0Þ ¼ x0, satisfies 
Tðx0ÞrVðx0Þ1ν 
kð1νÞ 
forall x0 in someopenneighborhoodoftheorigin.If D ¼ Rn and 
VðxÞ is alsounbounded,system (4) is globally finite-timestable. 
Lemma 2. [14,15]: Suppose a1; a2; :::an and 0onumo2 areallreal 
numbers. Thenthefollowinginequalityholds: 
ja1jnum þja2jnumþ:::þjanjnumZða21 þa22 
þ:::þa2n 
Þnum=2: 
3. Designofadaptivebacksteppingslidingmodecontrollaw 
In thissection,wewillpresenttheABSMClawdesignprocess. 
Notethattheproposedcontrolschemeiscomposedofthe 
nominal controlterms, un, adaptivecompensatedcontrolterm uc 
and robustcontrolterm ur . Thecompensatedcontrolterm uc 
providesthecompletecompensationoflumpedperturbation,and 
robustcontrolterm ur improvestheperformanceofdynamic 
response.Thecontrolobjectiveistomaketheoutputofthesystem 
totrackthedesiredcommandsignalin finite time.Thedesignof 
ABSMC isdescribedasfollowing. 
First, fortheposition-trackingobjective,define thetracking 
erroras: 
z1 ¼ e1 ¼ x1xd ð4Þ 
where xd is commandpositionsignalordesiredtrajectory.And z1 
derivativeis 
_z1 ¼ _e1 ¼ _x1_xd ¼ x2_xd: ð5Þ 
Construct aidealstatefeedbackcontrollaw ϕ, andwedesire 
that 
x2 ¼ ϕ¼k1z1þ_x1d ð6Þ 
where k1 is apositivedesignparameterand x1d is desired 
command signal.Infact,thereexistanundesired-errorbetween 
ϕ and x2. Therefore,define anerrorvariables z2 ¼ x2ϕ, the 
derivativeof z2 is expressedas: 
_z2 ¼ _x2 _ϕ 
¼ f ðx1; x2Þþg  τþD _ϕ 
ð7Þ 
where _ϕ 
¼k1 _z1þ€x1d. The first Lyapunovfunctionischosenas 
V1 ¼ z21 
=2 
then, thederivativeof V1 is: 
_V 
1 ¼ z1 _z1 ¼ z1ðx2_xdÞ ¼ z1ðz2þϕ_xdÞ¼k1z21 
þz1z2: 
Z. Song,K.Sun/ISATransactions53(2014)125–133 126
Toprovidesufficient flexibilitytoshapetheresponseofposi- 
tion tracking-error.Wedesignaslidingmodesurface 
S ¼ c1  z1þz2 ð8Þ 
where c1 is positivedesignparameter. 
Theorem 1. Forsystem (1), ifcontrollaw 
τ ¼ unþucþur ð9Þ 
is designedasfollows 
un ¼g1  ½c1 _z1þf ðx1; x2Þ_ϕ 
þk2S; ð10Þ 
ur ¼g1  
^ α 
4εSþλ2jz1j 
S þη  signðSÞ 
  
: ð11Þ 
uc ¼g1  S  ^ α2 
þ 
ε2 
4 
  
ð12Þ 
where k2, ε, λ2 and η arepositivedesignparameters.Adaptive 
update-lawisupdatedonlineas 
_^ 
α ¼ r  jSjþε  r ð13Þ 
where r is positivenumber.Andparameterrelationship 
k2ðk1þc1Þ41=4 issatisfied. Then,wheneverthetracking-error z1 
startsfromanyinitialpoint,itguaranteesthesystemtrajectoryto 
convergetoequilibriumpoint. 
Proof. Consider thefollowingLyapunovfunction 
V ¼ V1þ 
1 
2 
S2 
þ 
1 
2r 
α~ 2: 
The derivativeof V can bederivedasfollows 
_V 
¼ _V 
1þS  _S 
þ 
1 
r 
α~  _^ 
α¼k1z21 
þz1z2þS c1 _z1þ½ z_2þ 
1 
r  ~ α_^ 
α 
¼k1z21 
þz1z2þS c1 _z1þf ðx1; x2Þþg  τþD _ϕ 
h i 
þ 
1 
r 
~ α_^ 
α ð14Þ 
Substituting τ (9) and updatedlaw (13) into (14), yielding 
_V 
¼k1z21 
þz1z2þS Dk2S 
^ α 
4εSS ^ α2 
þ 
ε2 
4 
  
λ2jz1j 
S η  sgnðSÞ 
  
þ 
1 
r 
~ α_^ 
α¼k1z21 
þz1z2k2ðc1z1þz2Þ2þS D^ α2S 
ε2 
4 
S 
  
 
^ α 
4εηjSjλ2jz1jþ ~ αjSjþεðα^αnÞ¼ZTP1ZþS D^ α2S 
ε2 
4 
S 
  
 
^ α 
4εη S λ2 z1 þ ~ α S ε ^ ααnj 
 
 
 
 
 
 
 
ð15Þ 
where ZT 
¼ ½z1; z2. Ifsufficient condition k2ðk1þc1Þ41=4 issatis- 
fied, then 
P1 ¼ 
k1þk2c21 
k2c112 
k2c112 
k2 
 # 
is apositivedefinite symmetricmatrix.Therefore,wecan 
obtain ZTP1Zr0. Inaddition,thefollowingrelationshipcanbe 
established. 
S D^ α2S 
ε2 
4 
S 
  
þα~ S  
^ α 
4ε 
r S αn^ α2S2 
 
ε2 
4 
S2 
þα~ S  
^ α 
4ε 
 
 
 
 
 
 
¼ jSjUðα^α~ Þα^ 2S2 
 
ε2 
4 
S2 
þα~ S  
^ α 
4ε 
 
 
r εS2 
þ 
1 
4ε 
  
α^α~ S α^ 2S2 
 
ε2 
4 
S2 
þα~ S  
α^ 
4ε 
 
 
 
 
¼ εS2 ^ α^ α2S2 
 
ε2 
4 
S2 
¼  α^ jSj 
ε 
2jSj 
 2 
r0 
With theknowledgeabove,Eq. (15) is expressedasfollows: 
_V 
rλ2jz1jηjSjεj ^ ααnj ¼ 
ffiffiffi 
p2λ2  jz1j ffiffiffi 
p2 
ffiffiffi2 
p η  jSjffiffiffi 
p2 
ffiffiffiffiffi 
p2rε 
j ^ ααnffiffiffiffi j ffi 
p2r rmin 
ffiffiffi2 
p λ2; 
ffiffiffi2 
p η; 
ffiffiffiffiffi 
p2rε 
n o 
 jz1ffiffijffi 
p2þ jSjffiffiffi2 
p þj ^ ααnffiffiffiffi j ffi 
p2r 
  
ð16Þ 
With thehelpof Lemma 2, weobtain 
_V 
rmin 
ffiffiffi 
p2λ2; 
ffiffiffi 
p2η; 
ffiffiffiffiffi 
p2rε 
n o 
 jz1ffiffijffi2 
p 
 2 
þ jSjffiffiffi2 
p 
 2 
þ j ^ ααnffiffiffiffi j ffi 
p2r 
 2 
!1=2 
¼ϕ1  V1=2 
where ϕ1 ¼ minf 
ffiffiffi2 
p λ2; 
ffiffiffi2 
p η; 
ffiffiffiffiffi 
p2rεg. Byusing Lemma 1, itiscon- 
cluded thatthetracking-errorwillconvergetoequilibriumpoint 
in finite-timeinspiteofexternaldisturbanceandsystemuncer- 
tainty.Thiscompletestheproof □. 
Remark1. Theselectionofcontrollerparametershavedirect 
relationwiththeperformanceofdynamicresponse.Thebigger 
the λ2, ε, r and η, thebetterthedynamicresponse.However,this 
wouldresultinagreatercontroltorque,Hence,Thedesignpara- 
meterscanbeobtainedbyusingtrial-and-errormethod.Gradually 
increasethemfromzerountiltheperformanceissatisfied. 
Remark2. For exactlymeasuringorestimatingthederivativeof 
variablesansuper-twistingobserver [19,20] isavailable. 
4. DesignofABSMCwithfuzzymonitoringstrategy 
In thissection,weintroduceafuzzymonitoringfactor μnzðSÞ to 
improveadaptiveabilityofcontrolsystemandsoftencontrol 
signal. The μnzðSÞ is shownas Fig. 1. Whenthesystemmotion 
trajectoryisfarfromtheslidingmodesurface,abigweightis 
giventothecompensatedcontrolterm uc in ordertoovercomethe 
influence oftheperturbation.Whenmotiontrajectoryreachin 
sliding modesurface,thenominalcontrolterm un and robust 
controlterm ur play aleadingrole,asmallweightisgiventothe 
compensatedcontrolterm uc in ordertoreducethechatteringand 
improvetheperformanceofcontrolsystem.Themonitoringfactor 
μnzðSÞ is dynamicchangesinthewholecontrolprocess.Basedon 
the aboveanalysis,controlrulescanbewrittenas: 
Rule 1 : if S is ZOthen t is unþur 
Rule 2 : if S is NZthen t is unþurþuc 
where theZOandNZdenotezeroandnonzeroofthefuzzysets. 
The blockdiagramofcontrolsystemstructureisdepictedin Fig. 2. 
In thecontrolrules,Rule1statesthatifthevalueofSiszero 
then thecontrollawisdeterminedbythe unþur . Similarly,Rule 
2 statesthatifthevalueof S is nonzerothenthecontrollawis 
Fig. 1. Fuzzy membershipfunction. 
Z. Song,K.Sun/ISATransactions53(2014)125–133 127
determined by unþurþuc. Therefore,controllawcanbeobtained 
τ ¼ 
μZOðSÞ  ðunþurÞþμNZðSÞ  ðunþurþucÞ 
μZOðSÞþμNZðSÞ ¼ unþurþμNZðSÞ  uc 
ð17Þ 
where 0rμNZðSÞr1. 
Theorem 2. Suppose thatthesystem (1) with uncertaintiesand 
externaldisturbanceiscontrolledbytheproposedcontroller 
(17) with updatelawsin (13). Inaddition,iftherelationship 
k3ðk1þc1Þ41=4 where k3 ¼ k2ε ^ α is satisfied. Then,whenever 
the tracking-error z1 starts fromanyinitialpoint,itguaranteesthe 
states trajectorytoconvergetoequilibriumpointin finite-time. 
Proof. Consider thefollowingLyapunovfunction 
V ¼ V1þ 
1 
2 
S2 
þ 
1 
2r 
α~ 2 
Substituting τ (17) and updatedlaw (13) into (14), yielding 
_V 
¼k1z21 
þz1z2ðk2ε ^αÞS2 
ε ^αS2 
 
^α 
4ε 
þS Dα^ 2μNZðSÞS 
ε2 
4 
μNZðSÞS 
  
ðηjSjþλ2jz1jÞþjSjα~ εjα^αnj ð18Þ 
Let k3 ¼ k2ε ^ α. Ifsufficient condition k3ðk1þc1Þ41=4 issatis- 
fied, then 
P2 ¼ 
k1þk3c21 
k3c112 
k3c112 
k3 
 # 
is apositivedefinite symmetricmatrix.Andwecanobtain 
k1z21 
þz1z2k3ðc1z1þz2Þ2 ¼ZTP2Zr0. 
ThereforeEq. (18) is expressedasfollows: 
_V 
rεα^ S2 
 
^ α 
4εþS D^ α2SμNZðSÞ 
ε2 
4 
SμNZðSÞ 
  
þ S α~λ2 z1 η S ε α^αnj 
 
 
 
 
 
 
 
rε ^ αS2 
 
^ α 
4εþ S αnþ S α~λ2 z1 η S ε α^αnj 
 
 
 
 
 
 
 
 
 
¼ S ^ α 
^ α 
4εε ^ αS2 
λ2 z1 η S ε α^αnj 
 
 
 
 
 
 
r εS2 
þ 
1 
4ε 
  
^ α 
^ α 
4εε ^ αS2 
λ2 z1 η S ε ^ ααnj 
 
 
 
 
 
rmin 
ffiffiffi 
p2λ2; 
ffiffiffi 
p2η; 
ffiffiffiffiffi 
p2rε 
n o 
 jz1ffiffijffi2 
p þ jSjffiffiffi2 
p þj ^ ααnffiffiffiffi j ffi 
p2r 
 1=2 
¼φ1  V1=2 
By using Lemma 1, itisconcludedthatthetrajectoryoftracking- 
errortoconvergetoequilibriumpointin finite-time. Thiscom- 
pletestheproof □. 
5. Ballandplatesystemandsimulationresults 
5.1.Ballandplatesystem 
In thissection,westudytheballandplatesystem.Aball 
movingonaplateisatypicalnonlinearmechanicalsystem,which 
is oftenadoptedtoproof-testdiversecontrolschemes.Balland 
platesystemistheextensionofthetraditionalballandbeam 
problem,whichmovesametalballonarigidplateasshownin 
Fig. 3. In Fig. 4, ametalballstaysonarigidsquareplatewitheach 
side lengthof1m.Theslopeoftheplatecanbemanipulatedby 
twoperpendicularlyinstalledstepmotorssuchthatthetiltingof 
the plateenforcestheballtomovethedesiredpositionortotrack 
the referencetrajectory.Weassumethatspeedofslabisa 
constant whichdependsonmotorresponsespeedandtheball 
remainsincontactwiththeplateandtherollingoccurswithout 
slipping atanytime.Thedynamicsystemisdescribeasfollows 
mþ 
Ib 
r2b 
! 
€xþΔf 1þmg  u1þd1 ¼ 0 
mþ 
Ib 
r2b 
! 
€yþΔf 2þmg  u2þd2 ¼ 0 ð19Þ 
where Δf 1 ¼mðxy2þyxÞ, Δf 2 ¼mðyx2þxyÞ. The d1 and d2 are 
externaldisturbance. m¼ 0:11 isthequalityoftheball, rb ¼ 0:02 is 
Fig. 2. Control systemstructure. 
Fig. 3. Ball andplatesystem. 
Z. Song,K.Sun/ISATransactions53(2014)125–133 128
the radiusoftheball, Ib ¼ 0:176 istheballmomentofinertia, x and 
y aredisplacementoftheball.Define thestatevariableas x1 ¼ x, 
x2 ¼ _x, x3 ¼ y, x4 ¼ _y, andEq. (19) can betransformedintotwo- 
subsystem: 
subsystem1 : 
_x1 ¼ x2 
_x2 ¼ 
mg 
ðmþIb=r2b 
Þ  u1þD1 
8 
: ð20Þ 
subsystem2 : 
_x3 ¼ x4 
_x4 ¼ 
mg 
ðmþIb=r2b 
Þ  u2þD2 
8 
: ð21Þ 
where D1 ¼ð1=ðmþIb=r2b 
ÞÞðΔf 1þd1Þ, D2 ¼ð1=ðmþIb=r2b 
ÞÞ 
ðΔf 2þd2Þ. 
Remark3. Practically,in (13), the jSj cannot becomeexactlyzero 
and theadaptiveparameter ^ α may increaseboundlessly.Inorder 
toavoidtheissue,wemodifytheupdatelawas 
_^ 
α ¼ 
rjSjþε  r if jSj4δ 
0 if jSjrδ 
( 
ð22Þ 
where δ is asmallpositiveconstant. 
The proposedcontrollawsaredesignedasfollows 
u1 ¼ u1nþu1rþμnzðS1Þ  u1c ¼ ðmþIb=r2b 
Þ=ðmgÞ 

  
 c1 _z1_ϕ 
1þk2S1 
h i 
ðmþIb=r2b 
Þ=ðmgÞ 
^ α1 
4εS1þλ1jz1j 
S1 þη1sgnðS1Þ 
  
ðmþIb=r2b 
Þ  μnzðS1Þ 
mg 
S1 ^ α21 
þ 
ε2 
4 
  
ð23Þ 
u2 ¼ u2nþu2rþμnzðS2Þ  u2c ¼ ðmþIb=r2b 
Þ=ðmgÞ 

  
 c3 _z3_ϕ 
2þk4S2 
h i 
 ðmþIb=r2b 
Þ=ðmgÞ 

  ^α2 
4εS2þλ2jz3j 
S2 þη2sgnðS2Þ 
  
ðmþIb=r2b 
ÞμnzðS2Þ 
mg 
S2 ^ α22 
þ 
ε2 
4 
  
ð24Þ 
where z1 ¼ x1x1d, z2 ¼ x2ϕ1, z3 ¼ x3x3d, z4 ¼ x4ϕ2, ϕ1 ¼ 
Fig. k1z1þx_1d ϕ2 ¼ k3z3þx_3d, S1 ¼ c1z1þz2, S2 ¼ c3z3þz4. 4. Ball andplatecoordinate figure. 
0 2 4 6 8 10 12 
-2 
-1 
0 
1 
2 
time(s) 
Disturbances signal1 
0 2 4 6 8 10 12 
-2 
-1 
0 
1 
2 
time(s) 
Disturbances signal2 
0 2 4 6 8 10 12 
-4 
-2 
0 
2 
4 
time(s) Disturbances signal1 
0 2 4 6 8 10 12 
-4 
-2 
0 
2 
4 
time(s) 
Disturbances signal2 
Fig. 5. Random disturbancesignal. 
Z. Song,K.Sun/ISATransactions53(2014)125–133 129
5.2. Simulationresults 
Toshowtheeffectivenessofproposedmethodinthispaper, 
the proposedcontrolleriscomparedwiththeconventionalsliding 
mode controller.Theparametersoftheproposedcontrolscheme 
is givenasfollows k1 ¼ k3 ¼ 10, k2 ¼ k4 ¼ 6, c1 ¼ c3 ¼ 5, c2 ¼ c4 ¼ 1, 
η1 ¼ η2 ¼ 0:76, λ1 ¼ λ2 ¼ 3, δ ¼ 0:1 ε ¼ 0:03. Theinitialstatesofthe 
system x1ð0Þ ¼ 0:1, x2ð0Þ ¼ 0, x3ð0Þ ¼ 0:1, x4ð0Þ ¼ 0 and d1, d2 are 
shown in Fig. 5(a). Thecontrolobjectiveis x1-x1d ¼ sin ðπtÞ, 
x3-x3d ¼ cos ðπtÞ. Theresponsecurvesofthepositiontracking 
trajectoriesareillustratedin Fig. 6. Thetransientbehaviorof 
position tracking-errorsaregivenin Fig. 7. In Figs. 6 and 7, 
conventionalSMCcontrolstrategyneedsalongtimetoachieve 
satisfactory trackingaccuracy.Nevertheless,thepresentedcontrol 
strategycanenforcethesystemtrajectorytoreachthesliding 
surface andconvergeatsetpointin finite-time.Therefore,it 
obtains amoredesirabletrackingaccuracyinashorttime.In 
otherwords,boththefastresponseandtheabilityoftracking- 
error areimproved. Fig. 8(a andb)showsthecontrolinputofthe 
proposed controlschemeandconventionalSMC.Wecanseethat 
the controlinputofconventionalSMCisnotsmoothandcontain 
excessivechattering.Furthermore,theproposedABSMCmethod 
producesachatteringfreecontrolinput.Thus,itsoftensthe 
controlsignal Fig. 9. 
Tochecktherobustnesstheproposedmethod,weincreasethe 
externaldisturbance(in Fig. 5(b)). Thecontrolobjectiveis x1-x1d ¼ 
cos ð0:5πtÞ  ð1cos ð2πtÞÞ, x3-x3d ¼ sin ð0:5πtÞ  ð1cos ð2πtÞÞ and theothersconditionsremainunchanged.Thesimulationresults 
aregivenin Figs. 11–13. Comparing Figs.10 and 11(a andb),wecan 
find thatthepositiontrackingcontrolusingproposedmethodhas 
betterperformance.Andthetracking-errorachievesitsmaximumat 
thebeginningoftheengagement,andstaysataequilibriumpointat 
therest.Ascanbeseen,althoughthereexisttheincreaseddisturbance 
and uncertainty,thehightrackingaccuracyandfastconvergenceare 
stillhold,namelythemodeluncertaintyanddisturbancearewell 
suppressed Figs. 12 and 13. 
6. Conclusion 
In thisstudy,anoveladaptivebacksteppingslidingmodecontrol 
lawwithfuzzymonitoringstrategyisproposedforthecontrolofa 
kindofnonlinearmechanicalsystem.TheABSMChavebeendemon- 
stratedsuperiorperformanceandstill holdsrobustnessandstability 
inthepresenceuncertaintiesandexternaldisturbance,whichcan 
drivesystemtrajectorytosetpointin finite-time.Numericalsimula- 
tions areincludedtosupporttheaboveanalyses.Andtheresults 
demonstratethattheproposedcontrolstrategyeffectively. 
0 2 4 6 8 10 12 
-1.5 
-1 
-0.5 
0 
0.5 
1 
1.5 
time(s) 
X position tracking 
0 2 4 6 8 10 12 
-1.5 
-1 
-0.5 
0 
0.5 
1 
1.5 
time(s) 
Y position tracking 
Desired signal Proposed method with fuzzy monitoring strategy SMC 
Desired signal Proposed method with fuzzy monitoring strategy SMC 
0 0.2 0.4 
0 
0.5 
1 
Fig. 6. Systempositiontracking. 
0 2 4 6 8 10 12 
-0.1 
-0.05 
0 
0.05 
0.1 
time(s) 
X position error 
0 2 4 6 8 10 12 
-1 
-0.5 
0 
0.5 
time(s) 
Y position error 
The proposed control method with fuzzy monitoring strategy 
SMC 
The proposed control method with fuzzy monitoring strategy 
SMC 
0.8 0.9 1 1.1 1.2 1.3 
0 
2 
4 x 10 
2 2.2 2.4 2.6 2.8 3 3.2 3.4 
-0.04 
-0.02 
0 
Fig. 7. Tracking-error. 
Z. Song,K.Sun/ISATransactions53(2014)125–133 130
-1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1 
-1 
-0.8 
-0.6 
-0.4 
-0.2 
0 
0.2 
0.4 
0.6 
0.8 
1 
X-position 
Y-position 
-1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1 
-1 
-0.8 
-0.6 
-0.4 
-0.2 
0 
0.2 
0.4 
0.6 
0.8 
1 
X-position 
Y-position 
Fig. 9. Motion trajectory.(a)Motiontrajectoryoftheproposedmethod,(b)motiontrajectoryofSMCmethod. 
0 2 4 6 8 10 12 
-10 
-5 
0 
5 
time(s) 
0 2 4 6 8 10 12 
-10 
-5 
0 
5 
10 
time(s) 
Control signal u1 
Control signal u2 
0 2 4 6 8 10 12 
-20 
-15 
-10 
-5 
0 
5 
time(s) 
Y control signal X control signal Y control signal X control signal 
0 2 4 6 8 10 12 
-20 
-15 
-10 
-5 
0 
5 
time(s) 
Control signal u1 
Control signal u2 
Fig. 8. Control signal.(a)Controlsignaloftheproposedmethod.(b)SMCcontrolsignal. 
0 2 4 6 8 10 12 
-2 
-1 
0 
1 
2 
y position tracking x position tracking 
0 2 4 6 8 10 12 
-2 
-1 
0 
1 
2 
time(s) 
Fig. 10. Position tracking. 
Z. Song,K.Sun/ISATransactions53(2014)125–133 131
0 2 4 6 8 10 12 
-0.05 
0 
0.05 
0.1 
0.15 
time(s) 
X position tracking error 
0 2 4 6 8 10 12 
-0.05 
0 
0.05 
0.1 
0.15 
time(s) 
Y position tracking error 
Proposed method with fuzzy monitoring strategy 
SMC 
Proposed method with fuzzy monitor strategy 
SMC 
2 4 6 8 10 12 
-2 
0 
2 
x 10 
0 2 4 6 8 10 12 
-2 
0 
2 
x 10 
Fig. 11. Tracking-error. 
0 2 4 6 8 10 12 
-60 
-40 
-20 
0 
20 
40 
time(s) 
0 2 4 6 8 10 12 
-60 
-40 
-20 
0 
20 
40 
time(s) 
Control signal u1 
Control signal u2 
0 2 4 6 8 10 12 
-60 
-40 
-20 
0 
20 
40 
time(s) 
control signal u1 
0 2 4 6 8 10 12 
-60 
-40 
-20 
0 
20 
40 
time(s) 
control signal u2 control signal u2 control signal u1 
Control signal u1 
Control signal u2 
1.6 1.8 2 
-5 
0 5 
1.6 1.8 2 
-5 
0 5 Fig. 12. Controlsignal.(a)Controlsignaloftheproposedmethod.(b)SMCcontrolsignal. 
-1.5 -1 -0.5 0 0.5 1 1.5 
-1.5 
-1 
-0.5 
0 
0.5 
1 
1.5 
X-position 
Y-position 
-1.5 -1 -0.5 0 0.5 1 1.5 
-1.5 
-1 
-0.5 
0 
0.5 
1 
1.5 
X-position 
Y-position 
Fig. 13. Motion trajectory.(a)Motiontrajectoryoftheproposedmethod,(b)motiontrajectoryofSMCmethod. 
Z. Song,K.Sun/ISATransactions53(2014)125–133 132
Acknowledgements 
This paperissupportedinpartbytheNationalNaturalScience 
Foundation ofChina(Nos.11101066,61074044,61374118)andthe 
Fundamental ResearchFundsfortheCentralUniversities 
(No. DUT13LK32). 
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Adaptive backstepping sliding mode control with fuzzy monitoring strategy for a kind of mechanical system

  • 1. ResearchArticle Adaptivebacksteppingslidingmodecontrolwithfuzzymonitoring strategyforakindofmechanicalsystem Zhankui Song n, KaibiaoSun Faculty ofElectronicInformationandElectricalEngineering,DalianUniversityofTechnology,GanjingziDistrict,Dalian116024,China a rticleinfo Article history: Received2September2012 Receivedinrevisedform 26 July2013 Accepted29July2013 Availableonline21September2013 This paperwasrecommendedfor publication byDr.A.B.Rad Keywords: Backstepping Sliding modecontrol Fuzzy monitoringstrategy Finite-time a b s t r a c t A noveladaptivebacksteppingslidingmodecontrol(ABSMC)lawwithfuzzymonitoringstrategyis proposed forthetracking-controlofakindofnonlinearmechanicalsystem.TheproposedABSMC scheme combiningtheslidingmodecontrolandbacksteppingtechniqueensurethattheoccurrenceof the slidingmotionin finite-time andthetrajectoryoftracking-errorconvergetoequilibriumpoint.To obtain abetterperturbationrejectionproperty,anadaptivecontrollawisemployedtocompensatethe lumped perturbation.Furthermore,weintroducefuzzymonitoringstrategytoimproveadaptivecapacity and softenthecontrolsignal.Theconvergenceandstabilityoftheproposedcontrolschemeareproved by usingLyaponov′s method.Finally,numericalsimulationsdemonstratetheeffectivenessofthe proposed controlscheme. & 2013ISA.PublishedbyElsevierLtd.Allrightsreserved. 1. Introduction Controllerfornonlinearmechanicalsystemarewidelyused and implementedintheindustryinordertoimprovemechanical systemperformance.However,thereexistexternaldisturbance, parametervariationsandsystemuncertaintyinharshenviron- ments, whichconsequentlydegradetheperformanceofthe control system.Therefore,aclosed-loopcontrolsystemisessential for improvingtheperformanceofthemechanicalsystemthrough effectivelycompensatingfortheuncertaintyandexternaldistur- bances incontrolefforts.Variousnonlinearcontrolmethodshave been proposedforsolvingthisproblem,includingslidingmode control [1–5], backsteppingcontrol [8–12], intelligentcontrol [13–18], etc. Slidingmodecontrolhaslongproveditsinterestsandithas gainedmuchmoreattentionforitsrobustnessagainstparameter variationsandexternaldisturbance.SMCisnotonlyaneffective methodforcontrollingnonlinearsystemsbutalsocanbeconsidered as asynthesisprocedure.TheconventionalSMCdesignapproach consistsoftwosteps.First,aslidingmodesurfaceisdesignedsuch thatthesystemtrajectoryalongthesurfaceobtainscertaindesired properties.Then,adiscontinuouscontrol(switchcontrolterm)is design suchthatthesystemtrajectoriesreachtheslidingmode surfacein finitetime [6,7].SMCasageneraldesigntoolforcontrol nonlinear mechanicalsystemhasbeenwellestablished,theprimary advantagesofSMCare:(i)Goodrobustnessandgoodtransient performance;(ii)fastconvergencerateandhighcontrolprecision. (iii)Thepossibilityofstabilizing some complexnonlinearsystems which aredifficulttostabilizebycontinuousstatefeedbacklaws. Thebacksteppingapproachisanonlineartechniquewidelyused incontroldesign.Themultipleadvantagesofthisapproachinclude itslargesetofgloballyandasymptoticallystabilizingcontrollaws anditscapabilitytoimproverobustnessandsolveadaptivepro- blems.Backsteppingslidingmodecontrolinvolvesdividinganon- linearsystemintomanysubsystems.Thecontrollerisdesignedto achieveslidingmodecontrolforeachsubsystem.TheLyapunov functionisusedtoguaranteetheconvergenceoftheposition trackingerrorforallpossibleinitialconditions.Theaddedintegrator withbacksteppingcontrolimprovesthesystem′s robustnessagainst modelinguncertaintiesandexternaldisturbances,thusimproving the accuracyofsteady-statecontrol [8]. In [9], anintelligentback- steppingslidingmodecontrolscheme usingRBFNisproposedto design two-axismotioncontrolsystem.Andthisstrategy,usingRBFN which approximatetheupperboundedofthedisturbance.In [10–12],anbacksteppingslidingmodetechniqueforaradialpiston airmotorballscrewtableisdevelopedtoaccomplishaccurate desiredtrackingposition.Theresultsoftheseexperimentshowthat backsteppingslidingmodecontrollerapparentlysuppressesover- shootandprovidesaccuratepositioningperformance. As mentionedbefore,thereareseveralbacksteppingsliding mode controlmethodswithapplication.However,themajorityof these worksarebasedontheknowledgeoftheupperboundsof Contents listsavailableat ScienceDirect journalhomepage: www.elsevier.com/locate/isatrans ISATransactions 0019-0578/$-seefrontmatter & 2013ISA.PublishedbyElsevierLtd.Allrightsreserved. http://dx.doi.org/10.1016/j.isatra.2013.07.017 n Corresponding author.Tel.: þ86 13644257882. E-mail addresses: songzhankuiwudi@163.com, songzhankui@mail.dlut.edu.cn (Z.Song). ISA Transactions53(2014)125–133
  • 2. disturbance, asymptoticconvergenceoftracking-errorandthe usage offunctionsignwhichinvolveshighfrequenciesarepresent in thecontrol.Theseinconveniencesmakeverydifficult tousein the application.Inthispaper,anoveladaptivebackstepping sliding modecontrollawwithfuzzymonitoringstrategyis proposed forthetracking-controlofakindofnonlinearmechan- ical system.First,anappropriateslidingmodesurfaceiscon- structed, anditprovidessufficient flexibilitytoshapetheresponse of positiontracking-error.Then,theABSMCschemeisproposed, and itiscomposedofthenominalcontrolterm,robustcontrol term andcompensatedcontrolterm.Toobtainabetterperturba- tion rejectionproperty,adaptivecompensatedcontrollawis employedtocompensatelumpedperturbation.Thus,itrelaxthe requirementoftheboundoflumpedperturbation.Furthermore, we employthefuzzymonitoringstrategytobothimproveadap- tivecapacityandeliminatethehighfrequencies.Theproposed controlschemeensuresthattheoccurrenceoftheslidingmotion in finite-time andthetrajectoryoftracking-errorconvergeto equilibriumpoint.Therefore,itimprovestheperformancethe dynamic response.Themajorcontributionsofthispaperarethe following: (i) Theproposedcontrolstrategyisappliedtoensuringthe occurrenceoftheslidingmotionina finitetime,whichcan hold thecharacteroffasttransientresponseandimprovethe trackingaccuracy. (ii) Anadaptivecompensatedcontroltermisadoptedinthe proposedcontrolscheme,itprovidesthecompletecompen- sation oflumpedperturbation,anditrelaxtherequirementof the boundoflumpedperturbation. (iii) Afuzzymonitoringstrategyisintroducedtoimproveadaptive capacity,anditsoftensthecontrolsignal. The organizationofthispaperisdescribedasfollows.Inthe nextsection,thedynamicsofanonlinearmechanicalsystemis derived,andtheproblemstatementisalsogiven.In Sections 2 and 3, thedesignoftheABSMCisdiscussed.In Section 4, simulation result showtheprecisecontrolisaccomplishedbasedonthe proposed method.Conclusionispresentedin Section 5. 2. Problemformulation The generalmodelofsecond-ordermechanicalsystemsis described asthefollowing m€qþω_qþμð_qÞþbðq; _qÞþd ¼ τ ð1Þ where qARn is avectorofgeneralizedcoordinates; m and ω are parametersofthenonlinearmechanicalsystem; μð_qÞ and bðq; _qÞ arethecoulombfrictionandsystemuncertainty,respectively; d and τ aretheexternaldisturbanceandcontrolinput,respec- tively.Notethat μð_qÞ ¼ μ0ð_qÞþΔμð_qÞ, where μ0ð_qÞ and Δμð_qÞ are the nominalpartanduncertaintypart,respectively. Introducingthevariables x1 ¼ q and x2 ¼ _q, thendynamic system (1) can berewrittenas _x1 ¼ x2 _x2 ¼ f ðx1; x2ÞþDþg τ ð2Þ where g ¼m1, f ðx1; x2Þ¼g ½ω x2þμ0ðx2Þ and D¼g ½Δμðx2ÞþΔbðx1; x2Þþd is calledlumpedperturbation. Without lossofgenerality,thetechnicalassumptionsaremade to posetheprobleminatractablemanner Assumption 1. The desiredcommandsignalandtheir first and second timederivativesarebounded. Assumption2. Thelumpedperturbation D is bounded,i.e., jDjrα, where α40 isunknownnumber. Assumption3. There existsapositivenumber αn such that maxfα; ^ αgrαn, where ^ α is introducedtoestimate α, and ^ α will be givenlater.Here,define α~ ¼ α^αn, thenwecanobtain α~ r0. Before themainanalysis,somelemmaswhichwillbeusedin stability anddesignofcontrolleraregivenasfollows. Lemma 1. [13]: Considerthesystem _x¼ f ðxÞ; f ð0Þ ¼ 0; xARn; xð0Þ ¼ x0 ð3Þ where f : D-Rn is continuousonanopenneighborhood D and the origin is0.Supposethereisacontinuousfunction VðxÞ : D-R defined on UDD with theorigin0suchthatthefollowing conditions hold: 1. VðxÞ is positivedefiniteon DDRn; 2.Thereexistrealnumbers k40 and νAð0; 1Þ, suchthat _V ðxÞþk Vν ðxÞr0,andthen,system (3) islocally finite-timestable.The settlingtime,dependingontheinitialstate xð0Þ ¼ x0, satisfies Tðx0ÞrVðx0Þ1ν kð1νÞ forall x0 in someopenneighborhoodoftheorigin.If D ¼ Rn and VðxÞ is alsounbounded,system (4) is globally finite-timestable. Lemma 2. [14,15]: Suppose a1; a2; :::an and 0onumo2 areallreal numbers. Thenthefollowinginequalityholds: ja1jnum þja2jnumþ:::þjanjnumZða21 þa22 þ:::þa2n Þnum=2: 3. Designofadaptivebacksteppingslidingmodecontrollaw In thissection,wewillpresenttheABSMClawdesignprocess. Notethattheproposedcontrolschemeiscomposedofthe nominal controlterms, un, adaptivecompensatedcontrolterm uc and robustcontrolterm ur . Thecompensatedcontrolterm uc providesthecompletecompensationoflumpedperturbation,and robustcontrolterm ur improvestheperformanceofdynamic response.Thecontrolobjectiveistomaketheoutputofthesystem totrackthedesiredcommandsignalin finite time.Thedesignof ABSMC isdescribedasfollowing. First, fortheposition-trackingobjective,define thetracking erroras: z1 ¼ e1 ¼ x1xd ð4Þ where xd is commandpositionsignalordesiredtrajectory.And z1 derivativeis _z1 ¼ _e1 ¼ _x1_xd ¼ x2_xd: ð5Þ Construct aidealstatefeedbackcontrollaw ϕ, andwedesire that x2 ¼ ϕ¼k1z1þ_x1d ð6Þ where k1 is apositivedesignparameterand x1d is desired command signal.Infact,thereexistanundesired-errorbetween ϕ and x2. Therefore,define anerrorvariables z2 ¼ x2ϕ, the derivativeof z2 is expressedas: _z2 ¼ _x2 _ϕ ¼ f ðx1; x2Þþg τþD _ϕ ð7Þ where _ϕ ¼k1 _z1þ€x1d. The first Lyapunovfunctionischosenas V1 ¼ z21 =2 then, thederivativeof V1 is: _V 1 ¼ z1 _z1 ¼ z1ðx2_xdÞ ¼ z1ðz2þϕ_xdÞ¼k1z21 þz1z2: Z. Song,K.Sun/ISATransactions53(2014)125–133 126
  • 3. Toprovidesufficient flexibilitytoshapetheresponseofposi- tion tracking-error.Wedesignaslidingmodesurface S ¼ c1 z1þz2 ð8Þ where c1 is positivedesignparameter. Theorem 1. Forsystem (1), ifcontrollaw τ ¼ unþucþur ð9Þ is designedasfollows un ¼g1 ½c1 _z1þf ðx1; x2Þ_ϕ þk2S; ð10Þ ur ¼g1 ^ α 4εSþλ2jz1j S þη signðSÞ : ð11Þ uc ¼g1 S ^ α2 þ ε2 4 ð12Þ where k2, ε, λ2 and η arepositivedesignparameters.Adaptive update-lawisupdatedonlineas _^ α ¼ r jSjþε r ð13Þ where r is positivenumber.Andparameterrelationship k2ðk1þc1Þ41=4 issatisfied. Then,wheneverthetracking-error z1 startsfromanyinitialpoint,itguaranteesthesystemtrajectoryto convergetoequilibriumpoint. Proof. Consider thefollowingLyapunovfunction V ¼ V1þ 1 2 S2 þ 1 2r α~ 2: The derivativeof V can bederivedasfollows _V ¼ _V 1þS _S þ 1 r α~ _^ α¼k1z21 þz1z2þS c1 _z1þ½ z_2þ 1 r ~ α_^ α ¼k1z21 þz1z2þS c1 _z1þf ðx1; x2Þþg τþD _ϕ h i þ 1 r ~ α_^ α ð14Þ Substituting τ (9) and updatedlaw (13) into (14), yielding _V ¼k1z21 þz1z2þS Dk2S ^ α 4εSS ^ α2 þ ε2 4 λ2jz1j S η sgnðSÞ þ 1 r ~ α_^ α¼k1z21 þz1z2k2ðc1z1þz2Þ2þS D^ α2S ε2 4 S ^ α 4εηjSjλ2jz1jþ ~ αjSjþεðα^αnÞ¼ZTP1ZþS D^ α2S ε2 4 S ^ α 4εη S λ2 z1 þ ~ α S ε ^ ααnj ð15Þ where ZT ¼ ½z1; z2. Ifsufficient condition k2ðk1þc1Þ41=4 issatis- fied, then P1 ¼ k1þk2c21 k2c112 k2c112 k2 # is apositivedefinite symmetricmatrix.Therefore,wecan obtain ZTP1Zr0. Inaddition,thefollowingrelationshipcanbe established. S D^ α2S ε2 4 S þα~ S ^ α 4ε r S αn^ α2S2 ε2 4 S2 þα~ S ^ α 4ε ¼ jSjUðα^α~ Þα^ 2S2 ε2 4 S2 þα~ S ^ α 4ε r εS2 þ 1 4ε α^α~ S α^ 2S2 ε2 4 S2 þα~ S α^ 4ε ¼ εS2 ^ α^ α2S2 ε2 4 S2 ¼ α^ jSj ε 2jSj 2 r0 With theknowledgeabove,Eq. (15) is expressedasfollows: _V rλ2jz1jηjSjεj ^ ααnj ¼ ffiffiffi p2λ2 jz1j ffiffiffi p2 ffiffiffi2 p η jSjffiffiffi p2 ffiffiffiffiffi p2rε j ^ ααnffiffiffiffi j ffi p2r rmin ffiffiffi2 p λ2; ffiffiffi2 p η; ffiffiffiffiffi p2rε n o jz1ffiffijffi p2þ jSjffiffiffi2 p þj ^ ααnffiffiffiffi j ffi p2r ð16Þ With thehelpof Lemma 2, weobtain _V rmin ffiffiffi p2λ2; ffiffiffi p2η; ffiffiffiffiffi p2rε n o jz1ffiffijffi2 p 2 þ jSjffiffiffi2 p 2 þ j ^ ααnffiffiffiffi j ffi p2r 2 !1=2 ¼ϕ1 V1=2 where ϕ1 ¼ minf ffiffiffi2 p λ2; ffiffiffi2 p η; ffiffiffiffiffi p2rεg. Byusing Lemma 1, itiscon- cluded thatthetracking-errorwillconvergetoequilibriumpoint in finite-timeinspiteofexternaldisturbanceandsystemuncer- tainty.Thiscompletestheproof □. Remark1. Theselectionofcontrollerparametershavedirect relationwiththeperformanceofdynamicresponse.Thebigger the λ2, ε, r and η, thebetterthedynamicresponse.However,this wouldresultinagreatercontroltorque,Hence,Thedesignpara- meterscanbeobtainedbyusingtrial-and-errormethod.Gradually increasethemfromzerountiltheperformanceissatisfied. Remark2. For exactlymeasuringorestimatingthederivativeof variablesansuper-twistingobserver [19,20] isavailable. 4. DesignofABSMCwithfuzzymonitoringstrategy In thissection,weintroduceafuzzymonitoringfactor μnzðSÞ to improveadaptiveabilityofcontrolsystemandsoftencontrol signal. The μnzðSÞ is shownas Fig. 1. Whenthesystemmotion trajectoryisfarfromtheslidingmodesurface,abigweightis giventothecompensatedcontrolterm uc in ordertoovercomethe influence oftheperturbation.Whenmotiontrajectoryreachin sliding modesurface,thenominalcontrolterm un and robust controlterm ur play aleadingrole,asmallweightisgiventothe compensatedcontrolterm uc in ordertoreducethechatteringand improvetheperformanceofcontrolsystem.Themonitoringfactor μnzðSÞ is dynamicchangesinthewholecontrolprocess.Basedon the aboveanalysis,controlrulescanbewrittenas: Rule 1 : if S is ZOthen t is unþur Rule 2 : if S is NZthen t is unþurþuc where theZOandNZdenotezeroandnonzeroofthefuzzysets. The blockdiagramofcontrolsystemstructureisdepictedin Fig. 2. In thecontrolrules,Rule1statesthatifthevalueofSiszero then thecontrollawisdeterminedbythe unþur . Similarly,Rule 2 statesthatifthevalueof S is nonzerothenthecontrollawis Fig. 1. Fuzzy membershipfunction. Z. Song,K.Sun/ISATransactions53(2014)125–133 127
  • 4. determined by unþurþuc. Therefore,controllawcanbeobtained τ ¼ μZOðSÞ ðunþurÞþμNZðSÞ ðunþurþucÞ μZOðSÞþμNZðSÞ ¼ unþurþμNZðSÞ uc ð17Þ where 0rμNZðSÞr1. Theorem 2. Suppose thatthesystem (1) with uncertaintiesand externaldisturbanceiscontrolledbytheproposedcontroller (17) with updatelawsin (13). Inaddition,iftherelationship k3ðk1þc1Þ41=4 where k3 ¼ k2ε ^ α is satisfied. Then,whenever the tracking-error z1 starts fromanyinitialpoint,itguaranteesthe states trajectorytoconvergetoequilibriumpointin finite-time. Proof. Consider thefollowingLyapunovfunction V ¼ V1þ 1 2 S2 þ 1 2r α~ 2 Substituting τ (17) and updatedlaw (13) into (14), yielding _V ¼k1z21 þz1z2ðk2ε ^αÞS2 ε ^αS2 ^α 4ε þS Dα^ 2μNZðSÞS ε2 4 μNZðSÞS ðηjSjþλ2jz1jÞþjSjα~ εjα^αnj ð18Þ Let k3 ¼ k2ε ^ α. Ifsufficient condition k3ðk1þc1Þ41=4 issatis- fied, then P2 ¼ k1þk3c21 k3c112 k3c112 k3 # is apositivedefinite symmetricmatrix.Andwecanobtain k1z21 þz1z2k3ðc1z1þz2Þ2 ¼ZTP2Zr0. ThereforeEq. (18) is expressedasfollows: _V rεα^ S2 ^ α 4εþS D^ α2SμNZðSÞ ε2 4 SμNZðSÞ þ S α~λ2 z1 η S ε α^αnj rε ^ αS2 ^ α 4εþ S αnþ S α~λ2 z1 η S ε α^αnj ¼ S ^ α ^ α 4εε ^ αS2 λ2 z1 η S ε α^αnj r εS2 þ 1 4ε ^ α ^ α 4εε ^ αS2 λ2 z1 η S ε ^ ααnj rmin ffiffiffi p2λ2; ffiffiffi p2η; ffiffiffiffiffi p2rε n o jz1ffiffijffi2 p þ jSjffiffiffi2 p þj ^ ααnffiffiffiffi j ffi p2r 1=2 ¼φ1 V1=2 By using Lemma 1, itisconcludedthatthetrajectoryoftracking- errortoconvergetoequilibriumpointin finite-time. Thiscom- pletestheproof □. 5. Ballandplatesystemandsimulationresults 5.1.Ballandplatesystem In thissection,westudytheballandplatesystem.Aball movingonaplateisatypicalnonlinearmechanicalsystem,which is oftenadoptedtoproof-testdiversecontrolschemes.Balland platesystemistheextensionofthetraditionalballandbeam problem,whichmovesametalballonarigidplateasshownin Fig. 3. In Fig. 4, ametalballstaysonarigidsquareplatewitheach side lengthof1m.Theslopeoftheplatecanbemanipulatedby twoperpendicularlyinstalledstepmotorssuchthatthetiltingof the plateenforcestheballtomovethedesiredpositionortotrack the referencetrajectory.Weassumethatspeedofslabisa constant whichdependsonmotorresponsespeedandtheball remainsincontactwiththeplateandtherollingoccurswithout slipping atanytime.Thedynamicsystemisdescribeasfollows mþ Ib r2b ! €xþΔf 1þmg u1þd1 ¼ 0 mþ Ib r2b ! €yþΔf 2þmg u2þd2 ¼ 0 ð19Þ where Δf 1 ¼mðxy2þyxÞ, Δf 2 ¼mðyx2þxyÞ. The d1 and d2 are externaldisturbance. m¼ 0:11 isthequalityoftheball, rb ¼ 0:02 is Fig. 2. Control systemstructure. Fig. 3. Ball andplatesystem. Z. Song,K.Sun/ISATransactions53(2014)125–133 128
  • 5. the radiusoftheball, Ib ¼ 0:176 istheballmomentofinertia, x and y aredisplacementoftheball.Define thestatevariableas x1 ¼ x, x2 ¼ _x, x3 ¼ y, x4 ¼ _y, andEq. (19) can betransformedintotwo- subsystem: subsystem1 : _x1 ¼ x2 _x2 ¼ mg ðmþIb=r2b Þ u1þD1 8 : ð20Þ subsystem2 : _x3 ¼ x4 _x4 ¼ mg ðmþIb=r2b Þ u2þD2 8 : ð21Þ where D1 ¼ð1=ðmþIb=r2b ÞÞðΔf 1þd1Þ, D2 ¼ð1=ðmþIb=r2b ÞÞ ðΔf 2þd2Þ. Remark3. Practically,in (13), the jSj cannot becomeexactlyzero and theadaptiveparameter ^ α may increaseboundlessly.Inorder toavoidtheissue,wemodifytheupdatelawas _^ α ¼ rjSjþε r if jSj4δ 0 if jSjrδ ( ð22Þ where δ is asmallpositiveconstant. The proposedcontrollawsaredesignedasfollows u1 ¼ u1nþu1rþμnzðS1Þ u1c ¼ ðmþIb=r2b Þ=ðmgÞ c1 _z1_ϕ 1þk2S1 h i ðmþIb=r2b Þ=ðmgÞ ^ α1 4εS1þλ1jz1j S1 þη1sgnðS1Þ ðmþIb=r2b Þ μnzðS1Þ mg S1 ^ α21 þ ε2 4 ð23Þ u2 ¼ u2nþu2rþμnzðS2Þ u2c ¼ ðmþIb=r2b Þ=ðmgÞ c3 _z3_ϕ 2þk4S2 h i ðmþIb=r2b Þ=ðmgÞ ^α2 4εS2þλ2jz3j S2 þη2sgnðS2Þ ðmþIb=r2b ÞμnzðS2Þ mg S2 ^ α22 þ ε2 4 ð24Þ where z1 ¼ x1x1d, z2 ¼ x2ϕ1, z3 ¼ x3x3d, z4 ¼ x4ϕ2, ϕ1 ¼ Fig. k1z1þx_1d ϕ2 ¼ k3z3þx_3d, S1 ¼ c1z1þz2, S2 ¼ c3z3þz4. 4. Ball andplatecoordinate figure. 0 2 4 6 8 10 12 -2 -1 0 1 2 time(s) Disturbances signal1 0 2 4 6 8 10 12 -2 -1 0 1 2 time(s) Disturbances signal2 0 2 4 6 8 10 12 -4 -2 0 2 4 time(s) Disturbances signal1 0 2 4 6 8 10 12 -4 -2 0 2 4 time(s) Disturbances signal2 Fig. 5. Random disturbancesignal. Z. Song,K.Sun/ISATransactions53(2014)125–133 129
  • 6. 5.2. Simulationresults Toshowtheeffectivenessofproposedmethodinthispaper, the proposedcontrolleriscomparedwiththeconventionalsliding mode controller.Theparametersoftheproposedcontrolscheme is givenasfollows k1 ¼ k3 ¼ 10, k2 ¼ k4 ¼ 6, c1 ¼ c3 ¼ 5, c2 ¼ c4 ¼ 1, η1 ¼ η2 ¼ 0:76, λ1 ¼ λ2 ¼ 3, δ ¼ 0:1 ε ¼ 0:03. Theinitialstatesofthe system x1ð0Þ ¼ 0:1, x2ð0Þ ¼ 0, x3ð0Þ ¼ 0:1, x4ð0Þ ¼ 0 and d1, d2 are shown in Fig. 5(a). Thecontrolobjectiveis x1-x1d ¼ sin ðπtÞ, x3-x3d ¼ cos ðπtÞ. Theresponsecurvesofthepositiontracking trajectoriesareillustratedin Fig. 6. Thetransientbehaviorof position tracking-errorsaregivenin Fig. 7. In Figs. 6 and 7, conventionalSMCcontrolstrategyneedsalongtimetoachieve satisfactory trackingaccuracy.Nevertheless,thepresentedcontrol strategycanenforcethesystemtrajectorytoreachthesliding surface andconvergeatsetpointin finite-time.Therefore,it obtains amoredesirabletrackingaccuracyinashorttime.In otherwords,boththefastresponseandtheabilityoftracking- error areimproved. Fig. 8(a andb)showsthecontrolinputofthe proposed controlschemeandconventionalSMC.Wecanseethat the controlinputofconventionalSMCisnotsmoothandcontain excessivechattering.Furthermore,theproposedABSMCmethod producesachatteringfreecontrolinput.Thus,itsoftensthe controlsignal Fig. 9. Tochecktherobustnesstheproposedmethod,weincreasethe externaldisturbance(in Fig. 5(b)). Thecontrolobjectiveis x1-x1d ¼ cos ð0:5πtÞ ð1cos ð2πtÞÞ, x3-x3d ¼ sin ð0:5πtÞ ð1cos ð2πtÞÞ and theothersconditionsremainunchanged.Thesimulationresults aregivenin Figs. 11–13. Comparing Figs.10 and 11(a andb),wecan find thatthepositiontrackingcontrolusingproposedmethodhas betterperformance.Andthetracking-errorachievesitsmaximumat thebeginningoftheengagement,andstaysataequilibriumpointat therest.Ascanbeseen,althoughthereexisttheincreaseddisturbance and uncertainty,thehightrackingaccuracyandfastconvergenceare stillhold,namelythemodeluncertaintyanddisturbancearewell suppressed Figs. 12 and 13. 6. Conclusion In thisstudy,anoveladaptivebacksteppingslidingmodecontrol lawwithfuzzymonitoringstrategyisproposedforthecontrolofa kindofnonlinearmechanicalsystem.TheABSMChavebeendemon- stratedsuperiorperformanceandstill holdsrobustnessandstability inthepresenceuncertaintiesandexternaldisturbance,whichcan drivesystemtrajectorytosetpointin finite-time.Numericalsimula- tions areincludedtosupporttheaboveanalyses.Andtheresults demonstratethattheproposedcontrolstrategyeffectively. 0 2 4 6 8 10 12 -1.5 -1 -0.5 0 0.5 1 1.5 time(s) X position tracking 0 2 4 6 8 10 12 -1.5 -1 -0.5 0 0.5 1 1.5 time(s) Y position tracking Desired signal Proposed method with fuzzy monitoring strategy SMC Desired signal Proposed method with fuzzy monitoring strategy SMC 0 0.2 0.4 0 0.5 1 Fig. 6. Systempositiontracking. 0 2 4 6 8 10 12 -0.1 -0.05 0 0.05 0.1 time(s) X position error 0 2 4 6 8 10 12 -1 -0.5 0 0.5 time(s) Y position error The proposed control method with fuzzy monitoring strategy SMC The proposed control method with fuzzy monitoring strategy SMC 0.8 0.9 1 1.1 1.2 1.3 0 2 4 x 10 2 2.2 2.4 2.6 2.8 3 3.2 3.4 -0.04 -0.02 0 Fig. 7. Tracking-error. Z. Song,K.Sun/ISATransactions53(2014)125–133 130
  • 7. -1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1 -1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1 X-position Y-position -1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1 -1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1 X-position Y-position Fig. 9. Motion trajectory.(a)Motiontrajectoryoftheproposedmethod,(b)motiontrajectoryofSMCmethod. 0 2 4 6 8 10 12 -10 -5 0 5 time(s) 0 2 4 6 8 10 12 -10 -5 0 5 10 time(s) Control signal u1 Control signal u2 0 2 4 6 8 10 12 -20 -15 -10 -5 0 5 time(s) Y control signal X control signal Y control signal X control signal 0 2 4 6 8 10 12 -20 -15 -10 -5 0 5 time(s) Control signal u1 Control signal u2 Fig. 8. Control signal.(a)Controlsignaloftheproposedmethod.(b)SMCcontrolsignal. 0 2 4 6 8 10 12 -2 -1 0 1 2 y position tracking x position tracking 0 2 4 6 8 10 12 -2 -1 0 1 2 time(s) Fig. 10. Position tracking. Z. Song,K.Sun/ISATransactions53(2014)125–133 131
  • 8. 0 2 4 6 8 10 12 -0.05 0 0.05 0.1 0.15 time(s) X position tracking error 0 2 4 6 8 10 12 -0.05 0 0.05 0.1 0.15 time(s) Y position tracking error Proposed method with fuzzy monitoring strategy SMC Proposed method with fuzzy monitor strategy SMC 2 4 6 8 10 12 -2 0 2 x 10 0 2 4 6 8 10 12 -2 0 2 x 10 Fig. 11. Tracking-error. 0 2 4 6 8 10 12 -60 -40 -20 0 20 40 time(s) 0 2 4 6 8 10 12 -60 -40 -20 0 20 40 time(s) Control signal u1 Control signal u2 0 2 4 6 8 10 12 -60 -40 -20 0 20 40 time(s) control signal u1 0 2 4 6 8 10 12 -60 -40 -20 0 20 40 time(s) control signal u2 control signal u2 control signal u1 Control signal u1 Control signal u2 1.6 1.8 2 -5 0 5 1.6 1.8 2 -5 0 5 Fig. 12. Controlsignal.(a)Controlsignaloftheproposedmethod.(b)SMCcontrolsignal. -1.5 -1 -0.5 0 0.5 1 1.5 -1.5 -1 -0.5 0 0.5 1 1.5 X-position Y-position -1.5 -1 -0.5 0 0.5 1 1.5 -1.5 -1 -0.5 0 0.5 1 1.5 X-position Y-position Fig. 13. Motion trajectory.(a)Motiontrajectoryoftheproposedmethod,(b)motiontrajectoryofSMCmethod. Z. Song,K.Sun/ISATransactions53(2014)125–133 132
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