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performance comparasion of pid and fuzzy control techniques in three phase induction motor control s.r.jadhav, s.v.kulkarni, t.d.dongale, t.g.kulkarni, r.r.mudholkar, m.d.uplane abstract the demand for control of electric power for electric motor drive syste m and industrial control exists since many years. variable - speed drives are designed when a motor is combined with a power electronics converter. by introducing variable speed for the driven load, it is possible to optimize the efficiency of the enti re system and this is the area where the maximum efficiency gains are possible. the closed loop control strategies employed are legion and pid is seemed to be superior amongst them. however it further needs to be improved in terms of overshoot and settling time. hence some other control strategies based on fuzzy logic , artificial neural network ( ann ) , neuro - fuz z y etc ., can be good alternatives . this paper describes the implementation of controller s based on pid and fuzzy l ogic strategies. a comparative perf ormance analysis demonstrate s the clever exploring of f uzzy l ogic control strategies circumvent ing the demerits of pid control strategies. index term : pid, f uzzy controller, three phase inverter, induction motor 1 . introduction a c motor s are getting m ore and more popular with their integration in large number of applications like pumps, conveyors, machine tools, centrifugal machines, presses, elevators, and packaging equipment etc. the major benefits of using ac motor in a system are improved reliabili ty, better performance , higher efficiency, easy scalability and feasibility of speed and torque control by different technique s . the t echniques such as r otor resistance control , s tator voltage control , v ariable f, v/f c ontrol, s lip energy recovery scheme e tc. play significant role in precisely controlling the speed of motors . many researchers have reported the work on speed control of ac machines employing different control strategies [ 1 - 3 ] . the performance comparison of various drives reported in literatur e [4 - 10] help the comprehensive understanding drive option targeted for application of interest . the ac drives are electronic devices used to control speed and torque of three - phase induction motors. an induction motor supplied by an ac drive can operate o ver a good range of frequency, typically from 10hz to 90hz. this range of frequencies yields rotor speeds from zero rpm to the rated value. the ac drive can produce the rated torque at any frequency within this range from zero to the rated frequency. in co nstant torque mode the motor operates up to base speed with constant torque. in constant power mode
the motor operates above base speed with varying torque. in constant torque mode the motor is supplied with rated voltage and frequency. some advanced tech niques are practiced in motor control applications. among these pid is most popular algorithm . some researchers have used fuzzy, fuzzy - pid and neuro fuzzy technique in many applications. the performance comparison of these methods indicates that some advan ced techniques like fuzzy achieves better performance in certain applications. in the present work the three phase motor drive is proposed, which will be implemented using pic microcontroller. the pid and fuzzy algorithms were used to control the three pha se induction motor. the performance comparison of the drive with both algorithms will be discussed subsequent sections . 2 . system block diagram fig ure 1: system b lock d iagram the system block diagram is shown in f ig . 1. it is designed around peripheral interface controller (pic 16f877a) . it includes inverter design, gate drive circuit, isolation and microcontroller for the proposed work. for the operation of variable frequency bridge inverter the required logic pulses are generated by using pi c microcontroller and are applied to gate drive circuit . the frequency for operation is read by microcontroller through hall effect speed sensor and curr ent speed is send to simulink of pid or fuzzy control technique through usart terminal of microcontroll er. the gate drive circuit is consists of opto - isolator to provide isolation for microcontroller and the other gate drive circuitry. the basic three phase voltage source inverter consists of six power mosfets with built in anti parallel diodes for freewhee ling action . the irfp C 460 n - channel mosfet is a semiconductor device operating as a switch. it operates at highest possible turn - on and turn - off rates , extremely high dv/dt capability and ensuring the accurate operation of the inverter. ac voltage from th e power grid is rectified using 16*2 lcd
the power bridge and capacitor is used as a filter, the output of filter gives pure dc to the three phase inverter as dc source. depending upon the frequency generated by microcontroller, the power supplied to the motor is v aried . the measured speed is displaying on 16* 2 lcd for the purpose of displaying the present speed of motor sensed by hall effect sensor. 2.1 . three phase inverter design three phase inverter designed using power mosfets is as shown in f ig . 2 . the invers e diode associated with the device is sufficient to operate the circuit at higher frequencies. mosfet technology promises to use much simpler and efficient drive circuits with significant cost benefits compared to bipolar devices . high voltage capacitor is connected across the rectifier out to provide low impedance path for high frequency current at switching of power devices. fig ure 3 : real t ime c ontrolling of 3 p hase i nduction m otor fig ure 2 : three phase inverter circuit mosfet irfp460 g1 fuse irfp460 q5 g4 irfp460 230 v q6 - + kbp2510 2 1 3 4 g5 irfp460 c capacitor bank irfp460 q2 irfp460 motor g6 g2 q4 g3 a q3 ac sw b q1
the conduction sequence of mosfet is 61 2 , 12 3 , 23 4 , 34 5 , 45 6 , 56 1 , and 61 2 . this gating sequence is generated so that mosfets of the same branch would not conduct at the same time. there must be some short time delay between turn off mosfet and turn on mosfet. this time delay must be greater than or equa l to turn - off time of mosfet ( ? 20 ns). each phase to phase contain120 0 phase shift. the phase to neutral output waveforms are as shown in fig . 4 . fig ure 4 : inverter o utput w aveforms (simulated in psim software ) 2.2 . gate drive using ic - irs 2110 to protect the control hardware from the high - power hex - inverter dielectric isolation is desired. a single chip, the irs2110, was found to have the desired functionality. it serve s the purpose of implement ing gate drives, including the circuitry that tak es into account the voltage biasing of the high side mosfets [8] . the ir2110 mos gate driver ic has two channels controlled by ttl or cmos compatible inputs. irs2110 have the transition threshold proportional to the supply v dd (3v - 20 v). this mgd have two gate drive channels hence independent, input commands or a single input command with complementary drive and predetermined dead time. 2.3 . microcontroller pic 16f877a for a control mechanism purpose , pic16f877a is used. the role of microcontroller is to generate pwm of desired frequency using timer/ counter module. it also monitors the sensed speed by hall effect sensor and sends it serially to simulink designed for pid and fuzzy control technique. according to speed sensed by hall effect speed sensor, t he simulink will generate control signal. this control signal is again provided to microcontroller for pwm variation. in short pwm is varied according to control signal generated by pid or fuzzy simulink. microcontroller also displays the current speed in rps (rotation per second) on 16x2 lcd display.
2.4 . hall effect speed sensor the hall - effect integrated sensor in incorporated with a hall circuit, a linear amplifier, and a cmos class a output structure. integrating the hall circuit and the amplifier on a single chip minimizes many of the problems normally associated with low voltage level analog signals. in the present work the hall effect speed sensor mh 183 is a unipolar hall effect sensor is used for speed sensing purpose has been used . it incorporates advanced chopper stabilization technology to provide accurate and stable magnetic switch points. the design, specifications and performance have been optimized for applications of solid state switches. the output transistor will be switched on (bop) in th e presence of a sufficiently strong south pole magnetic field facing the marked side of the package. similarly, the output will be switched off (brp) in the presence of a weaker south field and remain off with 0 field. [ 10 ] 3. pid and fuzzy simulink mod el development using simulink facility of matlab the models for following two types of controller have been developed for real - time motor speed control - 1. pid controller 2. fuzzy controller 3.1. pid controller simulink design in matlab fig ure 5 : pid simulink m odel pid tuner provides a fast and widely applicable single - loop pid tuning method for the simulink pid contr oller blocks. with this method the pid parameters can be easily tuned to achieve a robust design with the desired response time. the actual spee d of motor is sensed by speed sensor using pic controller and it send serially to simulink . the simulink block corresponding to constant is used to set desired speed . here auto tune pid is used for tuning plant or system. the transfer function of motor sys tem is a second order type as shown in fig. 5.
because of second order type system it exhibits ove rshoot and large settling time which forms the metric of performance in the present study. 3.2. fuzzy controller simulink design in matlab fig ure 6 : fuzzy s imulink m odel fig . 6 shows simulink design model for fuzzy controller . i t contain query instrument for accept ing the real time present speed of motor through serial port of pic . the constant is set to a reference speed . e rror block generates the output whi ch is the error between actual speed and set speed . this is error applied to one input of fuzzy controller and other to store th e error in memory to provide it to change of error block which gives error between previous error output and ac tual error at pre sent state. multiplexer combine both input and gives it to fuzzy controller . real time scope is used to observe actual behavioral of a system . to instrument block is used to send output of fuzzy controller to pic microcontroller . the fuzzy inference scheme ( fis ) for fuzzy controller is design using mamdani method. it contains structure of minimum and maximum operation [11] . direct method operates on an inference rule such as - if x is a and y is b then z is c where a, b and c are fuzzy set s . in thi s rule there are two main parts, the part following if called premise and part following then is called consequence. hence x and y are called premise variable s and z is the consequence variable. 3.3. pid simulation model the f ig .7 shows the tuning of pid contr oller. auto - tune pid controller itself tune s for exact values of k p , k i and k d .
fig ure 7 : tuning of a uto - t une pid c ontroller fig ure 8 : auto - t une pid t uning r esponse fig . 8 shows the response of auto - tune pid controller . i t depicts the t ransient response, steady state response, pick rise time, pick overshoot and most important parameter is the settling time. b y changing response time we were able to set all this parameter to desired value. auto - tune pid tuning response and all the paramet er shows a settling time of 10.8 s which is quite large. it means that system exhibits little sluggish response in tracking the set point . the various performance metric parameters are shown in below table - i .
table - i: system parameter for three phase in duction motor control parameter observed value rise time 2.09 second overshoot in % 4.91% peak time 1.05 second settling time 10.08 second fig ure 9 : real time pid response for three phase induction motor control fig . 9 shows the actual t uned pid output response and real - time speed of induction motor . d epending upon set speed and error in speed is generated which is applied to the pid controller and depending on this error pid gives the output which is pass ed over to pic microcontroller to maintain the speed . p rogram in microcontroller develops a decision signal such that if speed of motor is increas ing the pid algorithm gives large error output and depending upon error the three phase half - bridge inverter frequency is accordingly decreased to slow down the motor speed. i n the same way , if speed is found to be decreasing then frequency for inverter is increase d. t his whole program is develop ed using mplab environment with hitch c - compiler. 3.4 . fuzzy simulation model in order to control speed of induction motor using f uzzy c ontroller , it is necessary to develop fuzzy inference system (fis) in matlab environment. pid is one of the popular methods for many applications but it has certain limitations . al though , it is well suited for certain applications , fuzzy control is another simplest method for control applications. it basically closely associated with the human's decision making. also it is rule based approach providing more smooth control strategy [11 - 12] . here, we have designed the fu zzy inference system for speed control of induction motor a s is shown in fig . 1 0 .
fig ure 10 : fis e ditor for fuzzy c ontroller by mamdani m ethod for this particular application, m amdani controller is used [11] , which ha s two inputs namely error and ch ange of error ' and single output. input and output contains seven triangular membership functions . these seven membership functions are labeled as nl, nm, ns, z, ps, pm, pl which are same for input s and output variables . the ranges for these inputs are dependent on the speed of motor . the error input is nothing but difference between the speed sensed using hall effect sensor and set point speed , and change of error is nothing but the difference between current speed and previous speed. the previous speed is stored in memory block which holds the data for particular time. according to these inputs and control policy the rules are defined using decision matrix table shown in table - ii. table - ii: fuzzy rule base decision matrix for speed control e nl nm ns z ps pm pl ce u nl nl nl nl nl nm ns z nm nl nl nl nm ns z ps ns nl nl nm ns z ps pm z nl nm ns z ps pm pl ps nm ns z ps pm pl pl pm ns z ps pm pl pl pl pl z ps pm pl pl pl pl
the rules have the following format - if error is nl and ch ange of error is nl then output is nl if error is nm and change of error is ps then output is ns likewise, all forty nine rules are designed as control demand needs the action . this system is of miso (many input - single output) structure. here inputs are two and each input has seven partitions, thus there are 7x7 = 49 rules. the rules are fired according to the inputs and output condition s and decisions pertaining to output control signal are generated . this output is again sent back to the pic micro controller. it detects the output and accordingly it generates a particular pwm sequence for increasing or decreasing the speed. the fuzzy controller prov ides more smooth response and also less settling time [11, 12] . the whole system is in closed l oop. the response of fuzzy simulation is shown in fig . 1 1 . it shows the settling time required and also the settled output for given input. fig ure 1 1 : real time fuzzy response for three phase induction motor control 4 . results and discussion pid and fuzz y controllers are very efficient for speed controlling of three phase ac induction motor . they provide precise controlling action within their limits. pid controller is very much useful because it uses auto tuning. once it is tuned it tracks the output acc ording to the provided input. but it has a limitation that it has more settling time and overshoot . fuzzy controlling is another mean s for this application. its advantage is that it provides minimum settling time than pid controller and also less overshoot . the experimental results of both the controller are compared and analyzed. it is found that speed controlling of ac induction motor with fuzzy controllers is better than pid controlling method .
references 1. gade s s, shendge s b, uplane m d, performance comparison of auto tune pid controller with conventional pid controller, international journal ijcsc, v ol ume - 1, number - 1 of jan 2010, serial number 39,pp. 273 - 277, issn: 0973 - 7391. 2. r. arulmozhiyal, k baskaran, n.devarajan, j.kanagaraj, real time matlab interface for speed control of induction motor drive using dspic 30f4011, international journal of computer applications (0975 - 8887) volume 1 - n umber - 5 . 3. ashok kusagur, dr. s.f.kodad, dr.b.v.sankar ram, m odeling, design and simulation of an adaptive neuro - fuzzy inference system(anfis) for speed control of induction motor, international journal of computer ap plications (0975 - 8887) volume - 6 , n umber - 12, september 201 0 4. http://www.microchip.com/wwwproducts/devices.aspx?ddocname=en010242 (pic 16f877a datasheet). 5. g. chen, conventional and fu zz y pid controllers: an overview, 1996. 6. http://www.microchip.com/wwwproducts/devices.aspx?ddocname=en010242 7. http://www.irf.com/product - info/hexfet/ 8. http://www.irf.com/product - info/cic/fsgatedriverics.html 9. www.variablefrequencydrives.net/ 10. mh 183 cmos unipolar hal l switch .pdf. 11. gade s s, shendge s b, uplane m d,on line auto tuning of pid controller using successive approximation method, ieee xplore,international conference on 12th C 13 th march , itc - 2010 cochin . 12. bart kosko, neural network and fuzzy system - a dynamic approach to machine intelligence, university of south california, pentice hall of india, 2001. 13. chitra, assistant professor (senior), vit university, vellore, india, t.meenakshi assistant professo r, jansons institute of technology, india. j. asha professor, i.f.e.t. college of engineering, india. fuzzy logic controller for cascaded h - bridge multi level inverter, issn: 0975 - 5462 vol. 2 no. 2 feb. 2011. 14. matlab, simulink user g uide, the math works inc, 2010.

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