Time discretization issues in induction machine model solving for real-time applications

The Euler numerical integration method is used very commonly to solve the dynamic equations of the induction machine in real-time on digital processors. The need to solve the machine model also arises in real-time hardware-in-loop simulations, and in electric load emulation. The Euler method is often preferred in such applications due to its fast, simple single-step, explicit nature. However, Euler integration can result in large errors in transient and steady state response calculations, even with practical integration time steps. This paper aims at providing an analytical approach to studying the steady state errors caused by the Euler method in solving the induction machine model. It is shown analytically that the least error occurs when the machine model is solved in the synchronous reference frame. The effect of these errors on the closed loop decoupled control of induction machines is analysed in detail. The paper also gives a new formulation of Feedback Linearization Control (FLC) in the synchronous reference frame to reduce the effect of the discretization error. Analyses and simulations are validated through experiments.

[1]  T.G. Habetler,et al.  High-performance induction motor speed control using exact feedback linearization with state and state derivative feedback , 2003, IEEE Transactions on Power Electronics.

[2]  S. Peresada,et al.  Adaptive partial feedback linearization of induction motors , 1990, 29th IEEE Conference on Decision and Control.

[3]  Yerramreddy Srinivasa Rao,et al.  Real-Time Electrical Load Emulator Using Optimal Feedback Control Technique , 2010, IEEE Transactions on Industrial Electronics.

[4]  Hung-Ching Lu,et al.  Sensorless Decoupling Control of Induction Motors Based on Feedback Linearization , 2006, 2006 International Conference on Intelligent Engineering Systems.

[5]  In-Joong Ha,et al.  Control of induction motors for both high dynamic performance and high power efficiency , 1992, IEEE Trans. Ind. Electron..

[6]  M.P. Kazmierkowski,et al.  High performance induction motor control via feedback linearization , 1995, 1995 Proceedings of the IEEE International Symposium on Industrial Electronics.

[7]  Peter Vas,et al.  Sensorless vector and direct torque control , 1998 .

[8]  Mahesh B. Patil,et al.  Real time simulation of power electronic systems on multi-core processors , 2009, 2009 International Conference on Power Electronics and Drive Systems (PEDS).

[9]  A. Isidori Nonlinear Control Systems , 1985 .

[10]  Pablo J. Alsina,et al.  A discrete model of induction motors for real-time control applications , 1993, IEEE Trans. Ind. Electron..

[11]  Ahmed Rachid On induction motors control , 1997, IEEE Trans. Control. Syst. Technol..

[12]  D. L. Sobczuk Feedback linearization control of inverter fed induction motor-DSP implementation , 2002, Industrial Electronics, 2002. ISIE 2002. Proceedings of the 2002 IEEE International Symposium on.

[13]  F. Giri,et al.  Discrete-time modelling of induction motors with consideration of magnetic saturation , 2006, IECON 2006 - 32nd Annual Conference on IEEE Industrial Electronics.

[14]  Jafar Soltani,et al.  Nonlinear torque and stator flux controller for induction motor drive based on adaptive input–output feedback linearization and sliding mode control , 2008 .

[15]  M. Malinowski,et al.  Feedback Linearization Control of Inverter Fed Induction Motor - with Sliding Mode Speed and Flux Observers , 2006, IECON 2006 - 32nd Annual Conference on IEEE Industrial Electronics.

[16]  Scott D. Sudhoff,et al.  Analysis of Electric Machinery and Drive Systems , 1995 .

[17]  T. G. Habetler,et al.  High-performance induction motor speed control using exact feedback linearization with state and state derivative feedback , 2004 .