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 DOI: 10.1177/0959651812456498

1335 originally published online 7 September 2012 2012 226:Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering

Jakub E Takosoglu, Pawel A Laski and Slawomir BlasiakA fuzzy logic controller for the positioning control of an electro-pneumatic servo-drive

  

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Original Article

Proc IMechE Part I:J Systems and Control Engineering226(10) 1335–1343� IMechE 2012Reprints and permissions:sagepub.co.uk/journalsPermissions.navDOI: 10.1177/0959651812456498pii.sagepub.com

A fuzzy logic controller for thepositioning control of an electro-pneumatic servo-drive

Jakub E Takosoglu, Pawel A Laski and Slawomir Blasiak

AbstractThe main objective of our research project was to design an electro-pneumatic servo-drive positioning control system,which involved applying a fuzzy logic controller. A proportional–derivative fuzzy logic controller was selected to performposition changeover, follow-up, and teach/playback control. These methods of control are essential in automation equip-ment, such as pick-and-place machines, manipulators, and robots. Compared to the smart positioning controllerSPC200, the proportional–derivative fuzzy logic controller demonstrated superior accuracy required for industrial pneu-matic manipulators.

KeywordsFuzzy logic controller, positioning system, electro-pneumatic servo-drive, state-space controller

Date received: 24 March 2012; accepted: 3 July 2012

Introduction

The development of automation and robotics has con-tributed to an increased interest in electro-pneumaticservo-drives, which are highly dynamic, reliable, andcheap to manufacture. However, their application toindustrial robots and manipulators is limited due tounsatisfactory positioning accuracy,1 with this problembeing difficult to solve in the case of pneumatic sys-tems. One reason is that there is insufficient informa-tion on the conversion of compressed gas energy2 intomechanical energy of a pneumatic cylinder. Electro-pneumatic servo-drives with a teach/playback fuzzycontrol system have considerable practical significance,especially in the control of manipulating machines,industrial robots and manipulators, pneumatic arms,3,4

and physiotherapeutic manipulators.5 The methods ofcontrol based on artificial intelligence, including fuzzylogic, are described in Situm et al.,1 Carneiro and DeAlmeida,6 and Schulte and Hahn.7

Traditional systems of control of electro-pneumaticservo-drives use mainly positioners or proportional–integral–derivative (PID) controllers. In fuzzy logiccontrol, control algorithms are designed intuitively, onthe basis of an operator’s knowledge and experience.The knowledge coded in database rules is also the resultof the theoretical and practical understanding of thedynamics of a control system. As fuzzy logic controllers

enable a shift from qualitative to quantitative control,8,9

they can be applied in multiaxial electro-pneumaticservo-drives of various—series, parallel, or hybridseries/parallel—kinematic structures of manipulatorsand robots. Advancements in the software for real-timerapid prototyping and hardware-in-the-loop simulationhave enabled us to construct a positioning control sys-tem of an electro-pneumatic servo-drive using a fuzzylogic controller and test it under laboratory condi-tions.10 Such an approach minimizes the design costs.The analyzed system improves the dynamics and posi-tioning accuracy of an electro-pneumatic servo-driveand eliminates the disturbances in its control system.

Test stand

The control system discussed here is illustrated inFigure 1. Figure 2 shows a general view of the test stand

Faculty of Mechatronics and Machine Building, Kielce University of

Technology, Poland

Corresponding author:

Jakub E Takosoglu, Faculty of Mechatronics and Machine Building, Kielce

University of Technology, Aleja Tysiaclecia Panstwa Polskiego 7, Kielce

25-314, Poland.

Email: qba@tu.kielce.pl

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for the positioning control of an electro-pneumaticservo-drive with a fuzzy logic controller.

The test stand consists of the following.

� A DGPL-25-224 pneumatic rodless cylinder (pistondiameter of 25mm and stroke length of 224mm).

� AnMPYE-5-1/8-HF-010-B 5/3 way proportional flowcontrol valve (voltage of 0–10V, nominal flow rate of700L/min, and switching frequency of ca. 75Hz).

� A BTL5-A11-M0600-P-S32 noncontact micropulsedisplacement transducer (analog output signal vol-tage of 0–10V).

Figure 1. A schematic diagram of the control system of an electro-pneumatic servo-drive.

Figure 2. A general view of the test stand for the positioning control of an electro-pneumatic servo-drive (single-axis positioningsystem): 1: a potentiometric displacement transducer (motion trajectory adjuster); 2: a noncontact micropulse displacementtransducer; 3: a rodless pneumatic cylinder; 4: an xPC Target computer screen; 5: a pneumatic F.R. unit; 6: power supply; 7: anSCP200 state-space controller; 8: pressure transducers; 9: a servo-valve.

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� An MLO-POT-225-TLF potentiometric displace-ment transducer acting as a motion trajectoryadjuster (analog output signal voltage of 0–10V).

� PXW pressure transducers.� An AD/DA PCI-DAS1602/16 16-bit measurement

card with eight analog inputs and two analogoutputs.

� A smart positioning controller SPC200.� A mass load.� Two PC computers, the Host PC and the Target

PC, the latter with an xPC Target real-time system.

The control system is fitted with a potentiometricdisplacement transducer, which acts as a motion trajec-tory adjuster11 (teleoperator). As shown in Figure 4,the MATLAB/Simulink on the Host PC combinedwith the xPC Target on the target PC constitutes areal-time system for rapid prototyping and hardware-in-the-loop simulation. The target computer isequipped with an input/output (I/O) card and a real-time xPC Target system, with the latter activatingdata acquisition and controlling the electro-pneumaticservo-drive. The host and target computers communi-cate and share information by means of the transmis-sion control protocol/internet protocol (TCP/IP).Working with the package for rapid prototypingrequires developing and compiling a Simulink model

and then sending it to the target computer, whichfunctions as a real controller. The xPC Target systemenables you to measure, diagnose, tune, and visualizethe analyzed control process.

Fuzzy logic controller

The proportional–derivative (PD) fuzzy logic controllerwith two inputs, that is, e(t) (position error) and De(t)(change in the position error), and one output, that is,u(t) (voltage in the coil servo-valve), which was used tocontrol the electro-pneumatic servo-drive shown inFigure 3,9 operates on the knowledge base containingIF-THEN rules,12–14 using undefined predicates and afuzzy control mechanism.

The input and output signals of the fuzzy logic con-troller were fuzzified with triangular, trapezoidal, andGaussian membership functions represented as fuzzysets. Twenty-five fuzzy rules in the rule base (Table 1)constituted the fuzzy control surface.

In the fuzzification process, the firing degree wascalculated as a MIN function, the fuzzy implicationwas determined as a MIN function, and the aggrega-tion of the particular outputs of the rule was estimatedas a MAX function. The center of gravity method wasused to obtain a crisp value.

Figure 3. A schematic diagram of an electro-pneumatic servo-drive with a fuzzy logic controller.

Table 1. Fuzzy rule base.

De\e NB NS Z PS PB

NB NB NB NB NM PBNS NB NS NS PS PBZ NB NS Z PS PBPS NB NS PS PS PBPB NB PM PB PB PB

NB: negative big; NS: negative small; PB: positive big; PS: positive small; Z: zero; NM: negative medium; PM: positive medium.

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SPC200 controller

The smart positioning controller SPC200 used in thecomparative analysis is a commercially available con-troller of a serial manipulator able to connect up to fouraxes. This universal axis controller includes a position-ing controller for servo-pneumatic axes and a sequencecontroller for positioning systems. The SPC200 cancontrol both electromechanical drives and servo-pneumatic axes using a stepper motor. Local inputs andoutputs as well as fieldbus interfaces help us to auto-mate tasks ranging from the straightforward to thecomplex ones.15,16 The manufacturer does not specifythe control type. The literature on the subject describesthe SPC200 controller as a state-space controller, capa-ble of controlling linear motion parameters (position,velocity, and acceleration), a schematic diagram ofwhich is shown in Figure 4.

The calculation of a new value of the command sig-nal by the controller requires the following.

� Measurement of the current displacement of theactuator piston x(t).

� Reproduction of the unmeasured variables regard-ing velocity v(t) and acceleration a(t) based on thedisplacement x(t).

� Prediction of the system state variables xp(t), vp(t),and ap(t) in H steps based on the determined valuesof the linear model of the state variables as well ason the control vector u determined in the previoussteps.

� Determination of the control sequence u in L stepsin the set value of the follow-up or braking phase.

� Limitation of the command signals.

� Transfer of the current value of the command signalto the proportional servo-valve.

The producer declares the control accuracy to be60.2O 0.8mm, and the 0.01mm position measure-ment resolution \ 1%.

In the developed system, the SPC200 controllercommunicates with the PC via the RS232 port, whichis equipped with 32kB operational memory, where themotion and control parameter data can be stored. Thedata are then used to generate plots using the PC andthe WinPISA software. Measurements can be per-formed in the debug mode, which implies that the pro-gram instructions are followed at 1-s intervals. Theuser sets the instruction initializing data saving in thecontroller. However, only 13 s of the data can be saved.The data are transferred to the PC after the measure-ment is completed. The interval between the measure-ments determined from the plots generated by theWinPISA software is 1.5ms, which corresponds to theworking frequency of the SPC200 controller of 665Hz.

The system analyzed here can be used to register var-ious dynamic quantities, that is, a(t), v(t), x(t), and u(t),simultaneously. Due to low capacity, the SPC systemfirst writes the data and then transfers them to the PC(ca. 27 s at 9600 kbit/s). The SPC is also limited withrespect to the amount of data to be stored. The maxi-mum is 13 s. The greater the number of dynamic quanti-ties to be registered by the controller, the shorter themeasuring time. Figure 5 shows a diagram of a com-mercially available control system. A general view ofthe test stand for the positioning control of an electro-pneumatic servo-drive with an SPC200 controller is pre-sented in Figure 6.

Figure 4. A schematic diagram of the state-space controller.

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The fuzzy control system developed by the authorsprocesses data at 0.5-ms intervals, which correspondsto a working frequency of 2000Hz. There are no limita-tions with respect to the measuring time or the numberof measurements taken. Moreover, the measurementand the data transfer take place in real time.

Results of experimental tests

The tests were conducted to analyze the changeover,follow-up, and teach/playback control of the motion ofan electro-pneumatic servo-drive.5,9 Examples of the

test results concerning the positioning control of theelectro-pneumatic servo-drive are presented in Figure7. The quality of the control of the electro-pneumaticservo-drive with the fuzzy logic controller was checkedby means of standard performance indices including5,9

the following.

� Settling time tR� Overshoot dp

dp = ym � y0 tð Þ ð1Þ

� Steady-state error e(t)j j

Figure 5. A schematic diagram of an industrial electro-pneumatic servo-drive with an SPC200 controller.SPC: smart positioning controller; I/O: input/output; AIF: axis interface; MTS: manufacturer’s name of displacement encoder.

Figure 6. A general view of the test stand for the positioning control of an electro-pneumatic servo-drive with an SPC200controller: 1: an SPC200 controller; 2: an SPC-AIF-MTS communication interface; 3: a proportional servo-valve; 4: a pneumatic FR(filter and regulator of pressure) unit; 5: power supply; 6: an operator panel; 7: a rodless cylinder.

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� Integral of absolute error (IAE)

IAE=

ð‘

0

e tð Þj jdt ð2Þ

� Integral of squared error (ISE)

ISE=

ð‘

0

e2 tð Þdt ð3Þ

� Integral of the time-weighted absolute error (ITAE)

ITAE=

ð‘

0

t e tð Þj jdt ð4Þ

� Integral of the time-weighted squared error (ITSE)

ITSE=

ð‘

0

te2 tð Þdt ð5Þ

� Integral of control (ISC)

ISC=

ð‘

0

u2 tð Þdt ð6Þ

where ym is maximum value of the control signal, y0(t)is input signal, e(t) is position error, and u(t) is controlsignal.

The additional performance criteria were5,9 asfollows.

� Absolute position error

Dx=

PNi=1

x0 ið Þ � x ið Þj j

Nð7Þ

� Absolute velocity error

Figure 7. Positioning control of an electro-pneumatic servo-drive: (a) position changeover control (step input) with a mass load,(b) follow-up control (ramp input) with a mass load, (c) follow-up control (sin input), and (d) teach/playback control.

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Dv=

PNi=1

v0 ið Þ � v ið Þj j

Nð8Þ

where x(t) is position, v(t) is velocity, and N is num-ber of the measuring points.

Figures 8 to 10 show the positioning control of thedeveloped electro-pneumatic servo-drive with the fuzzylogic controller. In Figure 8, we can see the position chan-geover control (step input) without a mass load. Figure 9illustrates the follow-up control (ramp input) without amass load, and Figure 10 presents the follow-up control(ramp input) with a mass load. All these figures includethe performance indices of the control process.

Conclusion

This project was undertaken to design an electro-pneu-matic servo-drive positioning control system using a PDfuzzy logic controller. The controller was found to bewell-suited for performing the following tasks: positionchangeover control, follow-up control, and teach/play-back control. The PD fuzzy logic controller enabledpositioning of the electro-pneumatic servo-drive withan accuracy specified for industrial manipulators.Simulations and experimental tests were conducted onthe electro-pneumatic servo-drive with the fuzzy control-ler performing position changeover control and follow-up control. The designed fuzzy system is reported to beefficient, stable, resistant to disturbances and able tocooperate with any electro-pneumatic servo-drive. There

Figure 9. Positioning control of an electro-pneumatic servo-drive: (a) follow-up control (ramp input) without a mass load and (b)performance indices.

Figure 8. Positioning control of an electro-pneumatic servo-drive: (a) position changeover control (step input) without a mass loadand (b) performance indices.

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is no need for controller tuning, signal filtration, or otheradditional operations along the control track. There isalso no limitation on the number of measurements.

The developed fuzzy logic system was practicallyused for teach/playback control in various servo-pneumatic systems. The system can process measure-ment data every 0.5ms, which is equivalent to 2000Hz.In contrast to the SPC controller, the fuzzy logic con-troller does not have limitations with respect to themeasuring time or the amount of measurement data tobe stored. Measurement is performed in real time.Electro-pneumatic servo-drives with this teach/play-back control system have considerable practical signifi-cance, especially in the control of manipulatingmachines, industrial manipulators, and robots as wellas physiotherapeutic manipulators. The suggested posi-tioning system can also be used for educational pur-poses, for example, to facilitate the understanding ofthe operation of actuators, sensors, and fuzzy logiccontrollers.

The primary objective of the study was to demon-strate the superiority of the designed fuzzy logic con-troller over the commercially available smartpositioning controller SPC200 to be used for the con-trol of an electro-pneumatic servo-drive. The analysiscovered standard and integral performance indices.Additionally, we determined the absolute position andvelocity errors and other performance criteria forfollow-up control. Some of the time characteristics ofthe electro-pneumatic servo-drive positioning controlsystem obtained for the two controllers were repre-sented graphically. The performance indices were com-pared using bar charts displayed in logarithmic format.The data indicate that the designed fuzzy logic control-ler can also be applied to teach/playback control, whichmay be necessary in manually guided manipulators androbot end-effectors when the motion trajectories are

nonlinear or difficult to describe mathematically. Themanual motion trajectory adjuster was used to deter-mine the motion trajectory, which can be recorded inthe controller memory as a reference signal and thenplayed back.

Funding

This research received no specific grant from any fundingagency in the public, commercial, or not-for-profit sectors.

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Figure 10. Positioning control of an electro-pneumatic servo-drive: (a) follow-up control (ramp input) with a mass load and (b)performance indices.

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Appendix 1

Notation

e(t) position errorN number of the measuring pointstR settling timeu(t) voltage in the coil servo-valve (control

signal)xp(t), vp(t),ap(t)

state-space variables

ym maximum value of the control signaly0(t) input signal

De(t) change in the position errorDv absolute velocity errorDx absolute position errordp overshoote(t)j j steady-state error

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