GUILLEMIN INTRODUCTION Today home appliance applications require
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Approach Motor Control With fuzzy LOGIC
GUILLEMIN
INTRODUCTION Today home appliance applications require more more features such motor speed control, motor speed adaptation accessories, efficient easy human interface security features. These requirements achieved using electronic controls. This paper describes universal motor speed control implemented standard micro-controller running software using fuzzy LOGIC concept. different stages development this motor speed control using fuzzy LOGIC described with SGS-THOMSON micro-controller (MCU) fuzzy logic development tool: "fuzzyTECH Explorer Edition", from basic knowledge system first results. CONTROL MOTOR SPEED? Most motors used food-processors universal motors (brush motors with serial excitation) supplied mode. stator windings such motor connected series with rotor. flux proportional motor current motor torque proportional square current. Therefore motor speed largely sensitive torque variations shown Figure Universal Motor Basic Characteristics
Imotor
keep motor speed stable upon load variations, bringing more comfortable food-processor improved cooking mixture, motor speed control implemented generations food-processors. This speed control achieved adjustment motor voltage "phase angle" techniques "Pulse Width Modulation" (PWM) techniques.
fuzzyTECH Explorer Edition trademark Inform Software Corporation
1993 rights reserved.
AN419 01,94
APPROACH MOTOR CONTROL WITH fuzzy LOGIC
PRACTICAL APPLICATION Figure describes fuzzy logic motor speed control application. 400W universal motor supplied mode. This voltage adjusted P.W.M. through chopper stage composed Insulated Gate Bipolar Transistor (IBGT) STGP10N50 freewheeling diode STTA806DI. standard micro-controller, ST6265 with on-board timer, directly manages IGBT through 5/15V interface. Fig. Measures Tacho Voltage Updates Duty Cycle Control
TIMER
motor speed measured means tachogenerator frequency timer, tachogenerator voltage Analog Digital (A/D) converter. simplest solution consists using converter (the maximum speed motor corresponding full scale converter i.e. 5V). tachogenerator signal amplified, filtered then converted voltage means simple frequency/voltage converter. This solution avoids timer prescaler programming changes motor speed calculation large amplitude speed variations. speed measurement done periodically synchronized on-chip timer acting time base. This time base defined taking into account duration execution fuzzy rules (12, 15ms), duration motor speed change routine duration other functions exemple data byte transmission (explained later). This synchronization time base equal 30ms. manages tasks such minimum mains voltage detection, tachogenerator voltage measurement, fuzzy logic speed control, duty cycle generation, motor speed selection.
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APPROACH MOTOR CONTROL WITH fuzzy LOGIC
Description food-processor motor universal motor used this application speed ranging 22000 (i.e. Hz). gear ratio between motor speed tool speed equal 7.5. ratio between tachogenerator frequency motor frequency equal advantages using fuzzy logic such application overcome need precise mathematical model system. Nevertheless, system behaviour known this knowledge acquired with some simple experimental graphs. Open loop motor speed versus duty cycle tachogenerator voltage versus motor speed shown following Figures Fig. Motor Speed Versus Duty Cycle. Fig. Tacho Voltage Versus Motor
Speed
Unloaded motor
Utacho
Loaded motor
Speed
slopes these curves give system resolution: duty cycle variation gives speed variation unloaded motor speed, rotations second loaded motor, speed measurement resolution given converter resolution. Input/output variables definition input variables fuzzy logic controller, estimating motor speed variations, speed error speed error variations speed error equals measured speed minus targeted speed Vtacho Vtgt range variation defined maximum speed motor, i.e. [-300Hz, +300Hz]. speed error variation estimating motor speed evolution, equals, sampling time (30ms), measured speed minus previously measured speed Vtacho(n) Vtgt(n-1). output variable duty cycle variation, calculated fuzzy inference kernel. duty cycle then calculated MCU: %(n) %(n-1) applied IGBT gate each 30ms. This output signal, automatically generated micro-controller timer, ranges from 100% with resolution 0.4% (full range duty cycle coded from 255).
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APPROACH MOTOR CONTROL WITH fuzzy LOGIC
fuzzy LOGIC APPROACH WITH DEVELOPMENT TOOL program flow chart given Figure shows that fuzzy logic development divided into main parts: fuzzy logic application itself micro-controller environment program. Fig. fuzzy Logic Application Flow Chart. fuzzy logic part consists executable code generated development tool. This part made fuzzification input variables, execution activated rules defuzzification producing output variable. environment program consists micro-controller initialization, motor speed acquisition, speed error speed error variation calculation, input variable adaptation fuzzy logic kernel code values, calling fuzzy logic kernel, duty cycle update, motor speed command acquisition waiting synchronization time base "fuzzyTECH Explorer Edition" used develop this application covers steps fuzzy logic design from project, linguistic variables rules definitions executable code generation.
environment program
initialization Mains voltage monitoring 220V
Fuzzy routines generated development tool
Fuzzy logic data array initialization Start time base motor speed acquisition Adaptation fuzzy kernel inputs Input variable fuzzification Rules execution output defuzzi fication
duty cycle update read speed command Time base
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APPROACH MOTOR CONTROL WITH fuzzy LOGIC
Project definition development tool first step when using fuzzyTECH ST62 Explorer Edition define project means project editor window. project editor displays controller structure allows designer directly access linguistic variables rule definitions. Figure shows project window motor speed control. Fig. Motor Speed Control Project.
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APPROACH MOTOR CONTROL WITH fuzzy LOGIC
Linguistic variables definition next step controller design definition linguistic variables. graphic interface development tool allows designer easily create most suitable linguistic variables membership functions application. During definition linguistic variables, development tool allows user define representations variables: "shell value" "code value". shell value representation variables only used display actual data with tool. code values used micro-controller executable code generation range from (8-bit representation). Having same scale code value shell value gives better understanding control behaviour directly comparing real fuzzy inputs/output linguistic variables. input membership functions shown Figure defined taking into account speed acceleration motor system resolution. motor speed range well covered with five membership functions. According sensibility speed measurement line speed sampling rate (3Hz each 30ms corresponds acceleration 100Hz/s), motor speed variation range described with three membership functions. triangular shaped ("Pi-Type") membership functions "Zero" "Nul" make duty cycle variations less sensitive converter resolution. Fig. Membership Functions Fig. Membership Functions Speederr Speederrvar
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APPROACH MOTOR CONTROL WITH fuzzy LOGIC
duty cycle variation computed using Center Maximum method, output linguistic variable represented with lines instead triangular shape shown Figure PWMVar code value been reduced range producing each 30ms maximum duty cycle variation with resolution 0.4% directly compatible with resolution generated ST6. This avoids additional calculation when adding duty cycle variation current duty cycle (%). Fig. Membership Functions Duty Cycle
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APPROACH MOTOR CONTROL WITH fuzzy LOGIC
Rule definition Fig. Spreadsheet Rule Editor. Figure shows fuzzy controller rules. They have been defined understanding behaviour system find rules maintaining speed error near zero (steady state rules), rules avoiding motor speed overshoot (small variation rules) rules providing rapid response large error command change (big variation rules). fuzzy development tool with Spreadsheet rule editor (fig. provides easy rule acquisition also permits definition rule aggregation (MIN operators available) rule composition (PROD operator with degree support Here, rules aggregation done using operator degree support
Adaptation real variables fuzzy kernel input Working with variations input variables, which have negative values, translation done code whole range input variables within range 255]. motor speed representation (given converter) vary from 255, speed error speed error variation range from -255 +255. This variation coded within range 255] dividing input variables adding (07fh) normalize value. Open loop testing optimization fuzzy development tool offers ways test optimize rules membership function definition: interactive debug mode provides designer with graphical verification every design step even while design being performed. batch mode associated with pattern generator records output variables versus each input variables.
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APPROACH MOTOR CONTROL WITH fuzzy LOGIC
Real time test real time test application done using emulator EPROM version device. both cases, real time recording application variables measuring motor behaviour (tachogenerator voltage, variation, linguistic variables) helpful. This achieved 9600 Baud serial link between computer recording data. This data file then used spreadsheet editor capable displaying curves. This method, replacing oscilloscope, been used record following results (e.g. Figure 10). PRACTICAL RESULTS Recordings tachogenerator voltage (corresponding motor speed) duty cycle while motor running given following figures. motor reaches steady state speed 1.3s corresponding execution about fuzzy logic loops. overshoot motor speed been observed. steady state, notice motor speed fluctuations 3Hz. These fast fluctuations (30ms) resolution limit speed measurement line (tachogenerator converter) remain inaudible. Figure shows speed step response when motor loaded. Fig. Speed Step Response Versus Time Unloaded Motor.
Unloaded motor speed step response
Time
Time
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APPROACH MOTOR CONTROL WITH fuzzy LOGIC
Figure shows load step response motor. motor permanently loaded with 200W; 110W load variations applied. Upon these load variations, motor recovered targeted speed within less than without speed overshoot. Fig. Load Step Response Versus Time 200W Loaded Motor.
Load step reponse
Time
Time
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APPROACH MOTOR CONTROL WITH fuzzy LOGIC
CONCLUSION This note presents speed control with fuzzy logic universal motor. This motor control, implemented using standard ST6265 micro-controller running fuzzy logic kernel, gives acceptable results home appliances, such drills, washing machines, food processors, which require high precision level control. Improvements achieved increasing sensitivity speed error variation adding parameter giving image motor load order adapt variation motor load. Using fuzzy logic this application avoided needing knowledge precise mathematical model system regulation loop, permits first results within some days. Furthermore, fuzzy logic program flexible easily adapted other motor characteristics. Optimizing results (response time overoscillations) achieved making several trials; precise method fuzzy logic variables rule definitions available. These optimization trials reduced number effect Fuzzy logic variable modifications system behaviour well understood.
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APPROACH MOTOR CONTROL WITH fuzzy LOGIC
REFERENCES Adaptative fuzzy logic control motor speed loop Kosc, Profumo Electrical Drives Power Electronics September 1992. Twenty years fuzzy control: Experiences gained lessons learnt E.H. Mamdani IEEE 1993. fuzzyTech Explorer Edition User Manual SGS-THOMSON Microelectronics ST6260-6265 data sheet SGS-THOMSON Microelectronics Sensorless speed control universal motor Thierry Castagnet, Corporate Application Laboratory, SGS-THOMSON Microelectronics.
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APPROACH MOTOR CONTROL WITH fuzzy LOGIC
Appendix Practical schematic universal motor speed control with fuzzy logic. fuzzy logic regulation loop achieved standard MCU. motor supplied mode through chopper stage composed IGBT STGP10N50 freew heeling diode STTA806DI. board directly connected mains.
100uF 0.47/2W +18V 5.1V 200uF NRES 2.2K BC327 47nF 12K/2W 0.1uF 3A-600V 12K/2W 100uF 380V
27pF
270K
6.8K
ST6265
XTAL EXTAL
8MHz
27pF
TIM2out
10nF 100K 74HC123 10nF +18V 4148 TS272
BC337 4148 2222
4.7K
8.2K 4148
2.2K
STGW10N50 STTA806DI
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APPROACH MOTOR CONTROL WITH fuzzy LOGIC
NOTES
Information furnished believed accurate reliable. However, SGS-THOMSON Microelectronics assumes responsability consequences such information infringement patents other rights third parties which result from use. license granted implication otherwise under patent patent rights SGS-THOMSON Microelectronics. Specifications mentioned this publication subject change without notice. This publication supersedes replaces information previously supplied. SGS-THOMSON Microelectronics products authorized critical components life support devices systems without express written approval SGS-THOMSON Microelectronics.
1994 SGS-THOMSON Microelectronics Rights Reserved
Purchase Components SGS-THOMSON Microelectronics, conveys license under Philips Patent. Rights these components system, granted provided that system conforms Standard Specifications defined Philips. SGS-THOMSON Microelectronics GROUP COMPANIES Australia Brazil France Germany Hong Kong Italy Japan Korea Malaysia Malta Morocco Netherlands Singapore Spain Sweden Switzerland Taiwan Thailand United Kingdom U.S.A.
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