high performance pmlsm drives using tms320f2812 dsp controller

8/7/2019 High Performance PMLSM Drives Using TMS320F2812 DSP Controller

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Thc 2004 IEEE .4sia-PncilicConicrcncc onCircuits and Systems, Deccmbcr 6-9.2004

HIGH PERFORMANCE PMLSM DRIVES USING TMS320F2812DSP CONTROLLERYing-ShiehKung,member IEEE

Department of Electrical EngineeringSouthem T aiwan U niversity of TechnologyYung-K ang City, Tainan Hsien, 710, [email protected]

ABSTRACTA high performance position control for PML SM drivesusing TMS320F2812 DSP controller is presented. Due tothe DSP has the characteristics of fast computation andthe complete integrations of motor peripheral circuit, afully digital controller of PMLSM drives system can beintegrated and realized by s o h a r e in single chip. Toincrease the perf ona nce of PMLS M drives, an adaptivefuzzy controller is applied to cope with the systemuncertainty and load variations. Some experimentalresults have been validated the theo retical ones.

1. INTRODUCTIONW i g to the advantages of high power density, highperformance motion control in fast speed and betteraccuracy, permanent magnet linear synchronous motors(PMLSM) have been gradually used in many automationcontrol fields as an actuators [l-21, such ascomputer-controlled machining tools and semiconductormanufacturing equipments. But in industrial applications,there are many uncertainties, such as system parameteruncertainty, external load disturbance, kiction force,model uncertainty, always diminish the performancequality of the pre-design of the motor driving system. Tocope with those problems, in recent years, manyintelligent control techniques [3-41, such as fuzzy control,neural networks control, adaptive fuzzy control etc., havebeen developed and applied to the position control ofservo motor drives to obtain high operating performance.A high performance motor control system should have afast dynamic response in adjusting its control parametersso that the motor outputs affected by the disturbances canrecover to their original status as soon as po ssible [5].With the rapid development in microprocessor, the highperformance digital signal processor @SP) becomes apopular research on digital control [6-71 for ac drives du eto their high-speed performance, simple circuitry, on-chipperipherals of a micro-controller into a single chip

solution. Especially the new generation DSP controllerTMS320F28x [8] produced hy Texas Instrument, whichhas the advantages of high speed (150MIPS) performance,up to 128Kx16 flash, 2 set (12 channels) of PW M output,2 se t (4 channels) of QEP input, 12 channels 12-hit A Dconverter (20011s conv ersion time), 56 hits GP IO, is verysuitable to develop a fully digital controller and acomplicated intelligent control algorithm in servo m otordrives. Therefore, in this paper, a TMS320F2812 DSPembedded with the function of current vector control,SWWM scheme and adaptive fuzzy position control hasbeen developed a high performance drives for PMLSM.With the exceilent characteristics of proposed system, itwill make drives of PM LSM mo re programmable, robustand easy implementation.

2. THEORETICAL ANALYSISThe architecture of the proposed intelligent controlsystem for a PMLSM is shown in Fig. 1, in which thecurrent vector control and the intelligent position controlare all implemented in a TMS 320F2812 DSP chip. Thedetailed are introduced in the following section:2.1Mnthematical model of PMLSM:The dynamic model of a typical PMLSM can berepresented with synchronou s rotating reference6 asfollows [I ]

! % = - R - ; , + l T L , x ; 1dt L, T Ld I L,

where vd, vq are d- and q-axis voltages; id, is, are the d-and q-axis currents, R, is the phase winding resistance;L d ,L,are the d- and q-axis inductance; f is the translatorspeed; 1, is the permanent magnet flux linkage; T is thepole pitch. The developed electromagnetic thrust force isgiven by

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The current control of a PMLSM drive is based on avector control, that is, if we control idto 0 in Fig.1, thePMLSM will be decoupled and control a PMLSMbecome easy as to control a DC motor. Aftersimplification and considering the mechanical load, themodel of a PMLSM can be expressed in the followingequation,

where

an d the mechanical dynamic equation of PMLSM isd 2 x , dxE -FL= J , -t B,dt2 dt

(4)

where Fe ,K , ,J , ,B , and FL are represented withthe motor thrust force, force constant, inertial value,damping ratio and external force, respectively. In Fig.1,the configuration of the current loop using vector controlfor PMLSM drives includes PI controller, coordinatetransformation for Clarke, Clarke-' , Park , Park-'and SVPWM, A/D conversion, pulse signal detection ofthe encoder etc. which are not to discuss here.2.2Adaptive fuzzy controller in position control loop:The structure of an adaptive fuzzy controller forPMLSM drives is depicted in the dotted line of Fig. 1,which consists of a fuzzy controller, a reference modeland an adjusting mechanism. In Fig.1, the tracking errorand the change o f the error, e , Ae are defmed as

e ( k )= x , ( k ) - x , ( k ) , (7)&(k) = e (k )- e( k - I ) , (8)

and e, de and q a s input and output variable of fuzzycontroller, respectively. The design procedure of thefuzzy controller is as follows:0 Defme the linguist value are { A , ,A 2 , E )with the

symmetrical triangular membership function:I n

where X, is input value, L(.) is output value,x," and W ; are mean value and width of th etriangularmembership function.

0 Derive M fuzzy control rules as initial condition, suchas,IF e isAy and AeisA; THENu, isEm,m=1,2,..,M(10)

0 Construct the fuzzy system with u , ( z l e) kom thoseM rules using the singleton fuzzifier,product-inference rule, and central averagedefuzzifier method. Therefore, (IO) is replaced withthe following expression:

M M

C cm[n := , 5, (x, 3 2: 9 W:)I c m p mC[rI:=,s,(.,.Y,m C P mA"='u,(x18)= "2 = M,=I m=l

those cI,c 2,.., c y are adjustable parameters.The gradient descent method is adopted to derive thefuzzy control law in Fig. 1. The main purpose ofadjusting the parameters of the fuzzy controller is tom i n i u m the square error (instantaneous cost function)between the position of moving part of the linear motor

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and the output of the reference model. The instantaneouscost function is defined as follows:1 12 2 (12)J(k+l)=- g(k+ly =- [xJk+I)-xp(k+$

and the parameters of c, is adjusted with,aJ(k +1)Ac , ( k ) oc - ~ a q k )

To derive the formulation of adjusting the parametersc, ,at first, we assume FL to be zero, and take Laplacetransformation with (4)-(6), and then

(14)The bilinear transformation is applied and the differenceequation of PMLS M drive system can be derived as

(15)( ~ - e - w J " ) z - ~(1 -e -B-r"-z - ' ) ( l- 2.') 'where z- ' is a back-shift operator, and T is the samplingperiod. In Fig.1, the current command ii and the outputof fuzzy controlleruJ can be obtained by the followingexpression

i~(k)=~(u,(k-l)+(K,+Kp)u,(k)-xp(k)+xp(R-l)) (16)From(15)and(16), wehave

(17)x , ( k ) = ( A + I - B k v ) x p ( k - l ) - ( l - BK,)x,(k-2)+ Bk,u,(k - 2 ) + Bk , ( K , + K, )u , ( k - 1)with A = exp(-B,T/ J.). B =K,(1 -A)/B,.Furthermore, according to the chain rule, the partialdifferential equation of J(k +1) in (12) can berewritten a s

where a is learning rate. From (1 I), (13), (17) and (18),it is straightforward that the parameters c, of fuzzycontroller in ( 1 I ) can be derived by the followingexpression.

= aS ign(B )K , (K ,+K , ) e, (k)Because the motor parameter B is not easy to know, thesign(B) is employed to calculate in (19) and it is alwaysone due to B be positive. The sign(.) denoted the signoperator.

c pm

3. EXPERIMENTAL SYSTEM AND RESULTSThe overall experimental system is depicted in Fig. I ,and it includes a TMS320F2812 DSP controller. a

voltage source IGBT inverter and a PMLSM. ThePMLSM is single-axis stage with cog-free linear motorand its stroke length is 600mm. The maximum speed andacceleration are 4m/s and 4 g's, respectively. Themoving mass is 2.5kg, the maximum payload is 22.5kgand the maximum thrust force is 73N at continuouscondition. A linear encoder with 5pm resolution ismounted on the PMLSM as position sensor, and the polepitch is 30.5mm (about 6100 pulses). TheTMS320F2812 DSP controller in Fig.1 is used todevelop a fully digital controller for PMLSM drives,which the current vector control scheme and intelligentadaptive position control strategy are all realized bysoftware in this DSP chip. In the implementation, thePWM switching frequency of inverter is designed with16k Hz, dead-band is l p , and the control samplingfrequency of current and position loop are chosen asBkHz, and ZkHz, respectively. The flay chart of mainprogram and the intermpt service routine for digitalmotor control algorithm are designed and show n in Fig.2. The programs are coded by C language and thecomputation time of DSP for executing current loop is3 . 6 ~and executing the adaptive fuzzy control algorithmof position loop is 16 p.In experiment, for testing the learning effect of theproposed controller and choosing an adequate learningrate a, a square wave position com mand with amplitudeof 5mm with no external load is applied and the trackingresults between the output of reference model and themeasured position of the moving part of PMLSM underdifferent learning rate of 0.05, 0.1, and 0.15 is shown inFig. 3. All cases in Fig. 3, at initial, the moving part ofPMSLM tracks the output of reference model withoscillation, meanwhile the parameters of fuzzy controllercontinuous tuning toward reducing the error between theoutput of the reference model and the position of themoving part at each control sampling interval. After onesquare wave position comm and tracking, the parametersof fuzzy controller are almost tuned to the adequatevalue. It has also shown that a choose 0.15 is betterlearning performance than a choose 0.05. Furthermore,in order to compare the advantages between theproposed adaptive fuzzy controller and conventional PIcontroller, the same square wave with am plitude of 5mmbut 1 Hz frequency position command is used, and thestep response error between them are shown in Figs.4(a)-4(b). It shows that after one command periodlearning, in steady state, both of them all have z ero error,but in transient state, the peak of the tracking errors forthe proposed adaptive fuzzy controller is only the half ofthose of the PI controller. At last, to demonstrate theperformance of the frequency response, a tested inputsignal of sinusoid wave with Y2.5 mm amplitude and 5Hz frequency value is provided. In this design, themoving part of the PMLSM tracking the tested signal isshown in Fig. 5(a) and the tracking errors is plotted inFig. 5(b). The results reveal that they have good positiontracking. Therefore, from Figs. 3-5, they demonstratethat the use of a TM S320F2812 D SP chip to construct avector control and an adaptive fuzzyposition controllerfor PMLSM drives is effectiveness, high performanceand robustness.

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4. CONCLUSIONSA high per formance of PMLSM dr ives us ing a newgenerat ion TMS320F2812 DS P chip has been presentedin this paper. In order to reach this high perform ancegoals, those key techniques, such as the current vectorcont ro l le r , the SV PWM scheme and the adaptive fuzzyspeed controller of the P M L S M d r i v e s are al limplemented in this DSP chip. Emulation result showsthat even in the compl ica ted opera t ion of the proposedcontrol algorithm, i t only spends about Z O pcomputation time of DSP for executing an overallcontrol loop. Experimental results al so demonstrate thatin s tep command response and f iequency commandresponse, the posit ion of the moving par t of PMLSMadopting the proposed system can fast t rack theprescribed dynamic resp onse well .

5. REFERENCES[ I ] J.F.Gieras and Z.J. Piech, Linear Synchronous Motors -

TranrportotionandAutomation System, CRC Press, 2000.[2] P. K. Budig, "The application of linear motors,"Proceedings, PIEMC 2000, the third international, vol. 3,pp. 1336-1340.[3] C.M. Liaw, R.Y. Shue, H.C. Chen and S.C. Chen,"Development of a linear brushless DC motor drive withrobust position control," IEE Proc. Electr. Power Appl.,2001,vol. 148,No.2, pp. 11l- l18 .[4] F.I. Lin and C.H. Lin, "On-line gain tuning using RFNNfor linear synchronous motor," PESC, 2001 IEEE 3ZndAnnual, vol. 2, pp. 766-771.[ 5 ] T.S.Radwan, MA . Rahman, A.M. Osheiba and A.E.Lashine, "Dynamic Analysis of a High PerformancePermanent Magnet Synchronous Mot or Drive," Electricaland Computer Engineering, 1996,Canadian Conference onvol. 2, pp. 611-614.[6] B; Zhang, Y. Li and Y. Zuo, "A DSP-based fully digital

PMSM servo drive using on-line self-tuning PI controller"Proc. PIEMC 2000, v01.2, pp. 1012-1017.[7]A.M. Trzynadlowski, M.P. Kazmierkowski, P.Z.Grabowski, M.M. Bech, "Three examples of DS Papplications in advanced induction motor drives,"American Control Conference, 1999, vol. 3, pp.2139-2140.[8] TMS32OF2810 and TMS320F2812 Digital SignalProcessors, Handbook of Texas Instruments, 2002.

M Ti=O)Fig.3. Step response tracking results between the output of rcfcrcnccmodel and the actual position of moving part at different learningrate(a)a=0.05(b)a=0.10(c)a=0.15

0 0.25 0.5 0.75 I 1.25 1.5 1.75 2 22 5 2.5(8) Tim@,)

._o 0.25 0.5 a75 i 1.25 1.5 1 . i ~ 2 z.25 2s(b) The@)Fig. 4. Tracking error for a squarc wave position command withamplitude 5 mm under (a) proposed adaptive fuzzy control (b)PI control.

iy ast: aM5 4.5e+ -I0 0.15 0.5 0.75 I 1.25 1.5 1.75 I 1.25 2.5Fig. 5 . (a) Tracking a 5H z sinusoid input signal (b) Tracking em r.UFig. 2. Flow chan of main and ISR program in DSP chip

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high performance pmlsm drives using tms320f2812 dsp controller

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