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Proc. of Int. Conf. on Control, Communication and Power Engineering 2010

Speed Observer Based Load Angle Control of Induction Motor Drive 1

Gaurav N. Goyal1 and Dr. Mohan V.Aware2

Shri Ramdeobaba Kamla Nehru Engineering College /Electrical Engg. Department, Nagpur, India Email: gaurav.goyal13@gmail.com 2 Visvesvaraya National Institute of Technology/ Electrical Engg. Department, Nagpur, India Email: mva_win@yahoo.com [1]-[7]. It is possible to estimate the speed signal from machine terminal voltage and currents with the help of digital signal processor (DSP). Different methods are used for flux and speed estimation. The calculation method of state variable may be classified as models and observers. Models in comparison with observers are less complicated in the case of induction motor. The accuracy of these variables depends on the motor operating point, exactness of the parameter used, and the sensitivity of the model to drift in these parameters. The voltage model is not precise at low frequencies; however it is not sensitive to rotor resistance variations. On the other hand, the current model is sensitive to rotor resistance variations and is not accurate in calculating the rotor speed, especially at high speed. However, it is more precise, compared to voltage model, and at lower frequencies .the mixed model integrates the advantage of both models. Because of these inaccuracies in calculating the flux linkage, in many solutions an observer by introducing an additional feedback loop is used. The load angle is the angle between the flux ψr and the stator current Is. Since the flux is related to the applied voltage and is fixed, thus we cannot vary the magnitude of the vector ψr. But the speed at which it is rotating is not constant. Similarly in case of current vector the magnitude can be controlled but not ωi. ωi depends on the applied frequency.

Abstract— The performance of induction motor drives gets improved in the scalar control mode with various algorithms with speed /position feedback. In this paper load angle control of induction motor with speed observer is presented. This eliminates the physical presence of speed sensor. The basic control of rotor flux vector with stator current defines the dynamics of torque control. In this scheme, estimation of feedback variables is obtained by using algorithm with minimum number of machine parameters. The speed obtained is thus used in feedback loop to improve the machine performance. The proposed algorithm also has a capability to estimate the active and reactive power of the machine. This is further incorporated to improve the operating efficiency of the machine. The observer developed is tested for various dynamics condition to verify its operating performance in MATLAB/SIMULINK. Index Terms— Speed sensorless induction motor, Load angle control, speed observer, Energy efficiency

I. NOMENCLATURE us,is,Ψs, Ψr Rs, Rr, Ls, Lr , L m ωr ,ωΨr ,ωI x11,x12,x21,x22, Kω,Tω a3,a4,ωδ,σ

Stator voltage, current and flux, rotor flux Stator resistance, rotor resistance, stator inductance, rotor inductance, magnetizing inductance Rotor speed , rotor flux linkages speed, stator current angular frequency variables of multiscalar motor model Rotor flux speed PI controller parameters Motor coefficients

III. MATHEMATICAL MODEL OF Motor coefficients INDUCTION MOTOR A. Induction Motor Model The fundamental equation, which is used to introduce the relation ship for speed observer system, is the stator circuit equation given by

II. INTRODUCTION The speed sensor is an inconvenient device and has many drawbacks. An incremental shaft mounted speeder encoder is required for close loop speed or position control. A speed encoder is undesirable in a drive because it adds cost and reliability problems, beside the need for a shaft extension and mounting arrangement. Thus from the beginning of 1980’s there were serious research works throughout the world to control induction machine without the need for speed sensor Gaurav N Goyal is with Department of Electrical Shri Ramdeobaba Kamla Nehru College of Engineering, Asst.Professor (E-mail: gaurav.goyal13@gmail.com). M.V. Aware is with the Department of Electrical Visvesvaraya National Institute of Technology, Nagpur, INDIA(E-mail: mva_win @ yahoo.com).

us = Rs is +

+ jωaψ s

(1)

The d-and q-voltage component presented in the d-q reference frame with the rotor flux linkages oriented in the d-axis are given by

usd = Rs iˆsd +

Engineering, Nagpur as a

usq = Rs iˆsq +

Engineering, Maharashtra,

dψ s

dψˆ sd dt

dψˆ sq dt

− ωˆψ ψˆ sq

(2)

+ ωˆψ rψˆ sd

(3)

Proc. of Int. Conf. on Control, Communication and Power Engineering 2010

B. Mechanical Subsystem com 12

com 11

com

ωr

ω2 +

usα pedictive stater current controller

ωi

Load Angle Controller

ωr

atg ---

com

X12m -

δcom

atg

X22m

com

X22

X21

X22m

X21m

simulation of X21 variable

ωr

Figure 1.

INVERTER U V W

com

usβ

com

ωi

com

isα

isβ

PWM

cal of Q MM variable

X21m

cal of powers

X12m

Rotor angular speed observer

isα

isα isβ stater current measur

isβ

dψˆ sq dt

Proposed load angle control induction motor control

= usd − Rs iˆsq − ωˆψ ψˆ sd r

(4) (5)

x12 = ψ rx isy − ψ ry isx = ψ r is sin(δ )

(7)

x21 = ψ rx 2 + ψ ry 2

(8)

x22 = ψ rx isx + ψ ry isy = ψ r is cos(δ )

(9)

variables

are (12) (13)

where Ti is the time constant of the first-order delay element used for filtering stator current command, J is the inertia constant, and m0 the load torque. The new state variables are not a function of the coordinate system. Therefore, it is not necessary to transform these variables from one coordinate to another one. This is essential for the practical realization of control systems because it gives significant simplification of the drive system. The fully decoupled subsystems make it possible to use this method in the flux-weakening region and to obtain simple system structures, which are not addressed in the case of vector control methods. For control of the presented system it is essential to know the actual value of the rotor flux vector. The use of the variables “instantaneous imaginary power” and “instantaneous real power” provides a simplification of the control system [10]. They proposed these new definitions of instantaneous powers in three-phase circuits based on instantaneous voltage and current values p= usdisd + usqisq (14) q=usqisd -usdisq (15)

Equation (2) and (3) present the voltage model of induction motor in d-q reference frame. This flux simulator operates in open loop without any feed back from the rotor flux error. The flux is identified correctly when the motor parameters are exactly known .in a real system, motor parameter change with operating point and temperature ,as a result, the estimator rotor flux and the actual flux are different, and this different depends on the following: properties of the selected motor model; degree of accuracy of parameter identification; degree of accuracy of current and voltage measurement and motor operating point .the use of feedback minimizes the effect of the above factors on the identification of the rotor flux linkages. Four state variables have been proposed for describing the motor model [9]. These state variables may be interpreted as rotor angular speed, scalar and vector products of the stator current and rotor flux vectors, and the square of the rotor linkage flux, as follows: (6) x11 = ωr

Taking into account the differential equations of the stator current and rotor flux vectors in steady state and using the new state variables, the following is obtained: x 12

L m + a1 2 a 4 is + P a2 a2 = L ωi r Rr

x 22

a Q − ωi I s = 4 a 3ω i

(16)

(17)

Where 2

a1 = −

Where, δ is the angle between stator current and rotor flux vectors. By using nonlinear feedback, it is possible to obtain a new model for the induction motor with two fully decoupled subsystems: mechanical and electromagnetic. This property is not a function of the motor source [10].

a3 =

R s Lr + Rr Lm Lr ω i

Lm , a = R r Lm , L a4 = r 2 Lr ω δ ωδ

ωδ

2 ωδ = δ Lr Ls & δ = 1 − Lm

Lr Lr The use of the above relationships avoids exact measurements of the flux, resistance, and angular speed of the rotor. Increasing the accuracy of calculation of

(11)

RL dx22 1 = − x22 r m isx2 + v '2 dt Ti Lr

com

usβ

dx11 Lm 1 = x12 − m0 dt JLr J

RL dx21 R = −2 r x 21 + 2 r m x22 dt Lr Lr

com

usα

= u sd − Rs iˆsd + ωˆψ ψˆ sq

(10)

C. Electromagnetic Subsystem The basic simplified machine represented as

The estimated d-q components of stator flux linkages are as follows

dψˆ sd

dx12 1 = − x12 + v1 dt Ti

Proc. of Int. Conf. on Control, Communication and Power Engineering 2010

(

dψˆ sd com = u sd − Rs iˆsd + ωˆψ rψˆ sq + k1 ψ rd − ψˆ rd dt

the new variables is possible using an observer of the following form:

dxˆ12 1 = − x12 + v1 + k01 ( xˆ12 − x12 m ) Ti dt

(18)

dx22 1 = − x22 + is 2 + v2 + k20 ( xˆ22 − x22 m ) dt Ti

(19)

dψˆ sq dt

RL dxˆ21 R = −2 r xˆ21 + 2 r m xˆ22 dt Lr Lr

At steady state the left side of the above equation is zero, therefore, it is possible to show that the variable x21 is

ψ rq com = 0 & ψ rd com = Lmiˆsd

(21)

A. Load Angle Calculation During the control of an induction motor, the position of each vector relative to the stationary coordinate system is not important. The vectors, which have position relative to each other, have significant meaning. This relationship can be observed in the electromagnetic torque description (22) m e = k . Im (ψ r i s ) = k ψ r i s sin δ The vectors of stator current and rotor flux are presented in Fig. 2. If it is assumed that the magnitude of stator current and rotor flux vectors are kept at the same level by control system, then it is possible to control the motor torque by changing load angle δ . By using the definition of new state variables it is possible to calculate the load angle (the angle between rotor flux linkage and stator current vectors) as follows:

x12 x 22

⎛ 1 ⎞ com ωˆψ = Kω ⎜ 1 + ⎟ (ψ rq − ψˆ rq ) ⎝ Tw s ⎠ ⎛ 1 ⎞ = − Kω ⎜ 1 + ⎟ψˆ rq ⎝ Tw s ⎠

ωˆ r = ωˆ ψ − r

Where

δ = a rctg

⎞ a1 ⎞ 2 a ⎟i + 4 P ⎟ a 2 ⎟⎠ s a 2 ⎟ ⎟ a 4Q − ω ii 2 s ⎟

Θ =

(24)

Figure 2.

ωψr

ωa = 0 α

1 ωˆ ψ r s

(32)

(33) frequency and

stator current vector, respectively. Using the steady state relationships of induction motor, it is possible to modify the described estimator (31) in the following form:

Stator current and rotor flux vector

is the estimated angular speed of the rotor

− a3 x12 − ωi i 2 s + a4 q ωrm = a3 x22 Where ωi and is are the angular

ωi

(31)

Rotor speed estimation is good only at steady state, but during the transients there is an error, which increases with a decreasing speed response [8], [9]. This is relative to the delays provided by integrating the q axis component of the rotor flux vector. A decrease in this error may be achieved by providing a proper initial value for the integrator. In this case, a proper initial value might be the angular speed of rotor flux vector at steady state. From the steady state relationships, it is possible to calculate the rotor speed as follows [9], [10].

The advantage of the above solution is that it is not sensitive to any precise measurement or identification of rotor speed. s

ωˆψ

R r i sq L r i sd

(30)

currents using the measured currents and defined in the stationary reference frame and using the transformation from αβ system to dq reference frame using the estimated angle

⎟ ⎟ ⎠

(29)

flux linkage vector. And i s q & i s d are the estimated

After substituting (16) and (17) in (23) the load angle is obtained as ⎛ ⎜ Lm R r ⎜⎝

(28)

(23)

⎛ ⎜ ⎜ ⎜ a3 ⎜ ⎜ ⎜ ⎝

(27)

Based on the estimated quantities of flux components, it is possible to identify the angular speed of rotor flux linkage vector using PI controller with zero command signal

IV. LOAD ANGLE AND SPEED OBSERVER

δ = arctg

L s Lr ˆ isd Lm Ls Lr ˆ i sq Lm

x21 the (5), following model:flux quantity in feedback Inusing (4) and a command path is used instead of the actual quantity. Correction part in (29) and (30) appears with K1 gain, which needs to be tuned in the simulation. The commanded components of rotor flux linkages are as follows:

(20)

x21 = Lm x22 m

Lr ψˆ sd − δ Lm L = r ψˆ sq − δ Lm

ψˆ rq

(25)

= usq − Rs iˆsq − ωˆψ rψˆ sd + k1 (ψ rq com −ψˆ rq ) (26)

ψˆ rd =

The index denotes the calculated values using power measurement. After assuming that motor parameters are known and constant, it is possible to identify the variable

)

Proc. of Int. Conf. on Control, Communication and Power Engineering 2010 ⎛

⎛ L x 1 ⎞ 1 ⎞⎛ ⎟ψˆ rq + ⎜⎜1 + ⎟⎟⎜⎜ ω rm + Rr m 12 m Tw s ⎟⎠ T Lr x 21m w s ⎠⎝ ⎝

ωˆψ = − K ⎜⎜1 + ⎝

⎞ ⎟⎟ ⎠

(34)

Where Tw is the time constant of the first order delay filter. The first part of (34) is the equation of PI controller (30) and the second part is the filtered value of the rotor flux vector. The block diagram of a modified speed observer is presented in Fig. 3. As will be shown in the simulation results for the speed observer system from Fig. 1, the error at steady state is about 2%. This error is less than the case of using an observer without taking into account angular speed of flux linkages calculated from the steady state condition. V. PROPOSED CONTROL SCHEME

In the presented system, the vectors are stator current and rotor flux linkage. The load angle may be kept constant by changing the position of stator current vector as a result of tuning its pulsation. The current frequency ω i may be changed directly using load angle

A. Control scheme with speed feedback In fig 4, block A represents the estimator which is described and presented in fig 5.This is an open loop estimator which estimates the slip frequency ωsl as a result of which we can get rotor speed ωr in the stationery reference frame. The simulation parameters are given in Table1.

controller or frequency ω 2 .

Squrrel Cage 440V

Stator resistance Stator inductance

Rs=1.05Ω

Frequency Nominal Power Rotor resistance Rotor inductance

Lls=0.004 H 0.13H

Mutual inductance (Lm) Inertia(J)

0.2 kg.m^2

50Hz 2238W

αβ usd dq

com

usβ

usq

isα αβ

isd

Flux ψrq ψ =0 Simulator equation ψrd com

Friction Factor(f)

Llr=0.0044 H 0.005752 N.ms

Pair of Poles(P)

ψrd

isβ

) = (x

com 2 s

isq

• •

X21m

Figure 3.

(36)

com

⎛ x12 com ⎞ ⎟ com ⎟ ⎝ x 22 ⎠

ωψr +

Rotor speed calcul

ωψrm

ωrm + ω

Isd

(37)

Σ -

Lr/Lm

1/p

Rs+Ls’p +

ωr

isd isq

RrLm Lr

Σ -

Lm/Tr

ωr

Rs+Ls’p

Isq

1 S

Lr/Lm

1/p

ωsl Ψrd

Rotor angular speed observer system

Ψrq

B. Proposed Speed Sensorless Control The block B in fig.4 represents the estimator which is replaced by the estimator represented by block A. This modified speed sensor has many advantages over open loop estimator which can be better understand by performance result. The control strategy of modified speed sensor is as explained below.

Figure 5.

+Σ

- ωr

Estimator represented by Block A

Controller for state variable X12 and X21are used in this research. The controller command signals of the com

com

variables X 12 and X 22 on the basis of these quantities the square of the current amplitude is calculated as 309

)

com 2

δ com = arctg ⎜⎜

Usq

) + (x (x )

com 2

X12m

(35)

And the load angle is

---

PI controller

slip

com

Rr=0.98Ω

ωψr

com rq

the

and PWM block. The command values of load angle δ stator current amplitude Is, are adjusted by the Proportional–integral (PI) controllers. Rotor angular speed may be measured

Usd

isq

changing

The calculated stator current frequency is provided to the

com

usα

ωi = ω 2 + ω r

TABLE 1

Parameters of Induction Motor for Simulation Rotor Type Voltage (Vrms)

indirectly

Proc. of Int. Conf. on Control, Communication and Power Engineering 2010 com

com

X11

X12

com

X11

com

X21

atg com

---

X22

X21m

Î´ com B. Simulation of the Proposed Speed Sensorless control Induction Motor

Figure 6. Speed and rotor flux square controllers used to develop stator current and Load angle.

Because of the stator voltage characteristics it is essential to filter the voltage to get the fundamental harmonic. Filtering the voltage signal complicates the control system and provides undesired delay in the measurement channel. As a result, the control system performs using actual values of stator currents and delayed values of stator voltage, which leads to non precise variable identification. In the proposed control system, two different current controllers, hysteresis [7] and predictive [8], [9] are used. In the control system it is possible to use command stator current and predicted voltage, which appears at the output of the predictive controller because there is an access to first harmonics of the currents and voltages. The use of predictive current controller in the control system with load angle control simplifies the structure of the control system by eliminating the stator voltage filtering block.

Step change in Load

The performance results are shown for step change with load torque from 0 to 70 N-m at time t=0.2 sec with voltage V=440V in Fig. 12 to Fig.18. The estimated and actual speed of the motor are shown the fig.12. The stator current is observed and is shown in the fig.13. There is slight increment in the stator current because of increase in load torque at 0.2 sec.

VI. SIMULATION AND PERFORMANCE EVALUATION The Proposed scheme with its controller action is simulated in MATLAB/SIMULINK. The induction motor with load is presented in details with voltage source inverter in SVPWM mode in SIMULINK. The performance results are presented in the following sections: The state variables of the estimator are shown in fig 14 to fig 16. The estimated active power and reactive power is shown in fig.18. This shows that there is increment in the active power at t=0.2sec and also the slight increment in reactive power.

A. Open Loop Control Scheme The proposed control scheme is simulated in MATLAB/SIMULINK and performance is observed under different dynamic conditions. 1.

Step change in load

The shaft load is changed after the free running of the motor. The performance is shown in fig. 8 to 9. The dynamic performance of motor as well as estimator under load TL=70 N-m applied at time t=2000 ms, with with the terminal voltage V=440V. The estimated torque and speed are shown the fig. 8 and 9 respectively.

310 ÂŠ 2009 ACEEE

Proc. of Int. Conf. on Control, Communication and Power Engineering 2010

REFERENCES [1] Guoliang Zhang and Philip T. Krein “Torque-Angle Oriented Control of Induction Machines” [2] A. B. Plunkett, J. D. D'Atre, and T. A. Lipo, "Synchronous control of a static AC induction motor drive," IEEE Trans. Industry Applications, vol. IA-15, pp. 430-437, 1979. [3] N. R. N. Idris, A. H. M. Yatim, "An improved stator flux estimation in steady-state operation for direct torque control of induction machines," IEEE Trans. Industry Applications, vol. 38, pp. 11I0-116, 2002. [4] M. Tsuji, S. Chen, T. Ohta, K. Izumi, and E. Yamada, “A speed sensor-less vector-controlled method for induction motor using . -axis flux,” in Proc. Int. Power Electron. Motion Contr. Conf., Hangzhou, China, 1997,pp. 353– 358. [5] Z. Krzeminski and J. Guzinski, “DSP based sensorless control system of the induction motor,” in Proc.Power Electron. Intell. Motion, Nuremberg, Germany, 1998, pp. 137–146. [6] H. Abu-Rub and J. Guzinski, “Rotor angular speed, rotor resistance and state variables estimation in a nonlinear system control of induction motor,” in Proc. Fourth Int. symp. Methods Models Automation and Robotics, Miedzyzdroje, Poland, 1997, pp. 613–618. [7] H. Akagi, Y. Kanazawa, and A. Nabae, “Generalized theory of the instantaneous reactive power in three-phase circuits,” in Proc. IPEC, Tokyo, Japan, 1998, pp. 1375– 1386. [8] P.C.Krause, O. Wasynczuk, and S.D. Sudhoff, Analysis of electric machinery and drive systems, 3rd ed. New York : IEEE Press , 2002 [9] Haithem Abu-Rub, Jaroslaw Guzinski, Zbigniew Krzeminski, and Hamid A. Toliyat, “Advanced Control of Induction Motor Based on Load Angle Estimation”IEEE Transactions on Industrial Electronics ,Vol.51, No.1, Feb 2004. [10] H. Abu-Rub, Z. Krzeminski, and J. Guzinski, “Nonlinear control of induction motor—Idea and application,” in Proc. Europe. PowerElectron.—Power Electron. Motion Contr. Conf., vol. 6, Slovak Republic, 2000, pp. 213– 218.

CONCLUSION A speed observer system for sensorless control of induction is developed. The rotor peed as been calculated using steady state relationship applied to the observer system. It has high accuracy and behaves satisfactory under all the speed range. An observer system has been adopted for the nonlinear control of induction motor. The simulation results illustrated that the system operates correctly for the different motor running conditions. The proposed scheme is working in closed loop control of the induction motor control. The speed sensorless induction motor with torque angle control has better dynamic performance. The power estimate algorithm is also tested with the given induction motor model.