Simulation Approach for Sliding Mode Control of Induction Servo Motor

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International Journal of Electrical, Electronics and Computer Systems (IJEECS)

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ISSN (Online): 2347-2820, Volume -3, Issue-11 2015 104

Simulation Approach for Sliding Mode Control of Induction Servo Motor

1M Lakshmi Swarupa, ²C.H.Naveen Kumar, ³K.Chetaswi

Department of Electrical and Electronics Engineering, MREC (A), Hyderabad, Telangana, India Abstract—The main objectives of this paper is aimed to

control the position of a field oriented Induction Servo motor drive for a given reference input signal in a very efficient way and to compare the two control schemes using Matlab/Simulink. To determine a PI control system which is insensitive to uncertainties, including parameter variations and external disturbances in the whole control process. To determine an adaptive sliding-mode control system which adjusts the bound of uncertainties in real time and also reduces the chattering phenomena in the control effort using a simple adaptive algorithm. The simulation result of the control schemes for a given Induction Motor.

Index Terms— Field oriented induction servo motor, PWM inverter and sliding mode control system

I. INTRODUCTION

With the well known merits of reliability, simple construction and low weight, Induction Motors have been gradually utilized in place of DC Motors ^[5] which suffer from the draw backs of spark, corrosion and necessity of maintenance. Induction Motor due to their ruggedness, ease of maintenance and low cost are widely used in domestic applications and industrial sectors with wide range in rating from a few hundred watts to few mega watts. The torque control in an Induction Motor is a basic problem due to its non linear characteristics. In order to achieve both high dynamic performance and high power efficiency, squared rotor flux has to be precisely controlled with the motor speed and torque because the power efficiency in Induction Motors in steady state operation is related to the squared rotor flux. Due to the advances in power electronics and microprocessors, Induction Motor drives used in variable speed and position Control have become more attractive in industrial Processes such as robot manipulates factory automations and transportation applications.

A proportional-integral-derivative controller (PID controller) is shown in figure 1, it is a common feedback loop component in industrial control systems.

The controller takes a measured value from a process or other apparatus and compares it with a reference set

point value. The difference (or "error" signal) is then used to adjust some input to the process in order to bring the process' measured value to its desired set point. Unlike simpler controllers, the PID ^[3] can adjust process outputs based on the history and rate of change of the error signal, which gives more accurate and stable control. In contrast to more complex algorithms such as optimal control theory, PID controllers can often be adjusted without advanced mathematics.

However, pushing robustness and performance to the limits requires a good understanding of the theory and controlled process.

Fig 1: Block diagram of PID Controller

II. NEED FOR SLIDING MODE CONTROL SCHEME

Computed torque or inverse dynamics technique ^[2] is a special application of feedback linearization of nonlinear systems. The computed torque controller is utilized to linearize the nonlinear equation of robot motion by cancellation of some, or all, nonlinear terms.

Then, a linear feedback controller is designed to achieve the desired closed-loop performance.

Consequently, large control gains are often required to achieve robustness and ensure local stability.

Thus, it is natural to explore other nonlinear controls that can circumvent the problem of uncertainties in the computed torque approach and to achieve better compensation and global stability.

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Fig 2: Block diagram of SMC for Second order system Variable Structure Control (VSC)^[1] with sliding mode, or sliding mode control (SMC), is one of the effective nonlinear robust control approaches since it provides system dynamics with an invariance property to uncertainties once the system dynamics are controlled in the sliding mode. The first step of SMC design is to select a sliding surface that models the desired closed- loop performance in state variable space. Then the control should be designed such that system state trajectories are forced toward the sliding surface and stay on it. The system state trajectory in the period of time before reaching the sliding surface is called the reaching phase. Once the system trajectory reaches the sliding surface, it stays on it and slides along it to the origin.

The system trajectory sliding along the sliding surface to the origin is the sliding mode. The insensitivity of the control system to the uncertainties exists in the sliding mode, but not during the reaching phase. In variable structure control with Sliding mode, the system structure is switched and the system state crosses the predetermined hyper-plane, so that the system slides along the reference trajectory.

The resultant characteristic of the system may become far different from those of the original system and it has been known that the system becomes to be immune to the parameter variations and disturbances. In an ideal system, the switching frequency can be very high and the state slides smoothly on the reference trajectory. In real systems however, such as digital control systems the switching rate should be limited.

Accordingly the system state chatters around the sliding line and the limit cycle occurs even in the steady state. SMC is robust with respect to matched internal and external disturbances.

SMC techniques are applicable to any minimum phase systems with relative degree less than the system order.

The control algorithm is based on the model of the motor in a frame rotating with stator current vector, which is rarely used in the field oriented control.

III. DESIGNING OF TOTAL SLIDING MODE CONTROLLER

Sliding mode controller is suitable for a specific class of nonlinear systems. This is applied in the presence of modeling inaccuracies, parameter variation and disturbances, provided that the upper bounds of their absolute values are known. Modeling inaccuracies may come from certain uncertainty about the plant (e.g.

unknown plant parameters), or from the choice of a simplified representation of the system dynamic.

Sliding mode controller design provides a systematic approach to the problem of maintaining stability and satisfactory performance in presence of modeling imperfections.

A sufficient condition for this behavior is to choose the control law, so that

((3.1)

In the presence of modeling imperfection and disturbance

Let e=ωr-ω^* (3.2)

IV. SIMULATION

To evaluate the proposed algorithm for the rotor flux and speed estimation, computer simulations have been conducted using MATLAB.

PWM Inverter -K-

rad/sec Continuous powergui

iqd (A) iabc (A), RPM , Nm, Wr Yr*

flux controller Te*

Yr is*

wsl

Vector control In2Out2

SMC Controller is*

theta irabc

Ref. iabc 1500

Ref. Speed (rpm)

Iabc

Ir_abc Va Vb Vc Load

1 s

Tm Va Vb Vc We

iabc Wr Te iqs id Induction machine model

-K-

Fig 3: Vector control of Induction Motor with PI controller

Fig 4: Simulation result for PI controller

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PWM Inverter -K-

rad/sec Continuous pow ergui

iqd (A) iabc (A), RPM , Nm, Wr Yr*

flux controller Te*

Yr is*

wsl

Vector control In2Out2

SMC Controller is*

theta irabc

Ref. iabc 1500

Ref. Speed (rpm)

Iabc

Ir_abc Va Vb Vc Load

1 s

Tm Va Vb Vc We

iabc Wr Te iqs id Induction machine model

-K-

Fig 5: Vector control of Induction Motor with SMC controller

Fig 6: Simulation results for SMC controller

V. CONCLUSIONS

The position of a field oriented Induction Servo motor drive for a given reference input signal in a very efficient way is simulated in Matlab/Simulink and comparison with different control schemes like PI control system, adaptive sliding-mode control system which adjusts the bound of uncertainties in real time and also reduces the chattering phenomena in the control effort using a simple adaptive algorithm. The simulation result of the control schemes for a given Induction Motor.

VI. REFERENCES

[1] Bose B.K.,”Modern Power Electronics and AC Drives”, Pearson Education, 4th Edition, 2004.

[2] Atkinson D. J., P. P. Acarnley and J. W. Finch,

“Application of estimation technique in vector

controlled inductin motor drives,” IEE Conference Proceeding, London, July 1990, pp.

358-363.

[3] Baader U., M. Depenbrock, and G. Gierse, “ Direct self control of inverter- fed induction machines: A basis for speed control without a speed measurement,” IEEE Trans. Ind. Appl., vol. 28, no. 3, May 1992, pp. 581-588.

[4] Chan, C. C., and H. Q. Wang, “New scheme of sliding mode control for high performance induction motor drives,” IEE Proc. on Electric Power Applications, vol. 143, no. 3, May 1996, pp 177- 185.

[5] Hasse K., “ On the dynamic behavior of induction machines driven by variable frequency and voltage sources,” ETZ Arch. Bd.

89, H. 4, 1968, pp. 77-81.

[6] Krause P. C., Analysis of Electric Machinary, McGrow-Hill, New York, 1986.

[7] Krause P. C and C. S. Thomas, “Simulation of symmetrical induction machinery,” IEEE Trans.

on Power Apparatus & Systems, vol. 84, no. 11, 1965, pp. 1038- 1053.

[8] Soto, R., and K. S. Yeung, “ Sliding mode control of induction motor without flux measurement,” IEEE Transaction on Industrial Application, vol. 31, no. 4, 1995, pp.744- 751.

[9] Benchaib, A., A. Rachid, and E. Audrezet, “ Sliding made input-output linearization and field orientation for real time control of induction motors,” IEEE Trans. on Power Electronics, vol. 14, no.1, Jan 1999, pp.128- 138.

[10] Mohanty K.B., “Sensorless sliding mode control of induction motor drives,” TENCON -2008, IEEE Region 10 Conference, Hyderabad.

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