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Comparison of different DC motor positioning control algorithms

Comparison of different DC motor positioning control algorithms

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Comparison of different DC motor positioning control algorithms

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  1. Comparison of different DC motor positioning control algorithms N. Baćac*, V. Slukić*, M. Puškarić*, B. Štih*, E. Kamenar**, S. Zelenika** * University of Rijeka, Faculty of Engineering, Rijeka, Croatia ** University of Rijeka, Faculty of Engineering and Centre for Micro and Nano Sciences and Technologies, Rijeka, Croatia

  2. About us… • Faculty of Engineering ( and Centre for Micro and Nano Sciences and Technologies (, • Precision Engineering Laboratory ( • People: Saša Zelenika, David Blažević, Ervin Kamenar • Main activities: • Ultra-high precision positioning systems and laser interferometric measurements • Energy harvesting/scavenging systems • Stereomicroscope measurements • Laser Doppler vibrometer measurements

  3. Ourprojects… • On-going: • GOLDFISH - DetectionofWatercourseContaminationusingSensorNetworksinDevelopingcountries (EU FP7 project) • Ultra-highprecisioncompliantdevices for microandnanotechnologyapplications (FundedbyMinistryofScienceEducationandSportsoftheRepublicof Croatia) • Center for microand nano sciencesand technologies (CMNST) • Finished: • WirelessAutonomous Tire PressureSensor(WATPS) (The Business Innovation Agency of the Republic of Croatia - BICRO) • System for automatic pressure regulation with a self-regulating autonomous valve (SAV) (From Ip To Business - FIDES)

  4. Content • Introduction • Experimental Set-up • DC motor positioningcontrolalgorithms • PID • Cascade • State-Space • Experimental resultsanddiscussion • Conclusions

  5. Introduction • DC motor finds application in many of today’s mechatronics systems: • precision positioning machines, • robotic arms, • pick-and-place machine for production of Printed Circuit Boards (PCB), • … • When DC motors are used, a feedback sensor is needed in order to establish velocity/position control.

  6. Actuator and feedback sensor (1/2) • Experimental system employed in this work is composed of a DC actuator with an embedded planetary gearbox and an incremental rotational (quadrature) encoder Gearbox Encoder

  7. Actuator and feedback sensor (2/2)

  8. Control system • National Instruments PXI-1050 chassis, PXI-8196 embedded controllerandPXI-6221 Data AcquisitionCard (DAQ) are used as a controlsystem. • Control alghoritms are programmed intheLabVIEWprograming environment. • LM675T based Power operationalamplifier is used to drivethe DC actuator.

  9. Experimental Set-Up blockscheme 64:1

  10. Control algorithms – PID (1/2) • Predefined LabVIEWPID block is used to implementthe PID alghoritm. • The tuning of the PID controller parameters isconducted intwosteps; byusingZiegler-Nicholsmethod (rough estimate of the gains) andbyanexperimental method (fine-tuning).

  11. Control algorithms – PID (2/2) • PID parameters are verifiedbyusingcustomdevelopedMaltab model.

  12. Control algorithms – Cascade (1/2) • Cascade control is composed of two loops: the velocity and the position loop. • Velocity(PI) loop is constituted by a proportional gain (KP), which scales the velocity error, and an integral time constant (TI), which defines the integration time. • A velocity loop itself cannot ensure that the actuator stops in a certain position, hence a positioning loop in cascade (series) with the PI velocity controller is employed.

  13. Control algorithms – Cascade (2/2) • The cascadecontrolerparameters are tuned by using a custom developed MatlabSimulink model. • The resulting parameters are implemented in the LabVIEW environment where additional online fine tuning is performed in order to match better real system response.

  14. Control algorithms – State Space (1/2) • State-space (SS) control derives from the state-variable method of representing differential equations. • Thebasicprincipleofthesynthesisofthe SS controller is to achievedesiredclosed-loop dynamics withpropervaluesoftheLvector. • GainvectorL is calculatedbyusingAckerman’s formula.

  15. Control algorithms – State Space (2/2) • SS Matlab model

  16. Experimentalresults (1/2) Parameters for the PID control method Parameters for the Cascade control method Dynamic results for the state-space control method

  17. Experimentalresults (2/2) comparison of dynamics for different control methods (experiments)

  18. Conclusions (1/2) • An overview of different DC motor control approaches is given in this work. • A Matlab model of the used actuator is established in order to simulate different control approaches. • Threedifferent controllersare implemented in the LabVIEW environment and experiments are conducted.

  19. Conclusions (2/2) • It is concluded that positioning control via the state-space controller has the fastest response and the lowest settling time. • Cascade control can be efficiently used, although the tuning of its parameters can often be cumbersome and computationally more intensive due to the presence of two PI blocks and the needed velocity calculation. • PID control results in negligible steady-state errors and acceptable rise and settling times.

  20. Thank you for your attention! Questions