Robust RBFN Control for Linear InductionMotor Drive Using FPGA

A field-programmable gate array (FPGA) based robust radial basis function network (RBFN) control system is proposed to control the mover position of a linear induction motor (LIM). First, the indirect field-oriented mechanism is adopted for the control of LIM. Next, an equivalent control law bases on sliding-mode control is designed, in which the uncertainties are lumped by a conservative constant. However, the lumped uncertainty is unknown and difficult to obtain in advance in practical applications. Therefore, a RBFN is derived to approximate the equivalent control law in real-time, and a robust RBFN control system with online training ability is resulted. Then, a FPGA chip is adopted to implement the indirect field-oriented mechanism and the developed control algorithms for possible low-cost and high-performance industrial applications. The effectiveness of the proposed control scheme is verified by some simulated and experimental results. With the robust RBFN control system, the mover position of the FPGA-based LIM drive possesses the advantages of good transient control performance and robustness to uncertainties in the tracking of periodic reference trajectories.

[1]  Francesc Guinjoan,et al.  A fixed-frequency quasi-sliding control algorithm: application to power inverters design by means of FPGA implementation , 2003 .

[2]  P.J.C. Branco,et al.  Theoretical modeling and experimental tests of an electromagnetic fluid transportation system driven by a linear induction motor , 2006, IEEE Transactions on Magnetics.

[3]  Faa-Jeng Lin,et al.  Adaptive backstepping control for linear induction motor drive to track periodic references , 2000 .

[4]  Volnei A. Pedroni.  Circuit Design with VHDL , 2004 .

[5]  Faa-Jeng Lin,et al.  FPGA-based fuzzy sliding-mode control for a linear induction motor drive , 2005 .

[6]  Hassan K. Khalil,et al.  Output feedback control of nonlinear systems using RBF neural networks , 2000, IEEE Trans. Neural Networks Learn. Syst..

[7]  Douglas L. Perry,et al.  VHDL: Programming by Example , 2002 .

[8]  Faa-Jeng Lin,et al.  Recurrent-Fuzzy-Neural-Network-Controlled Linear Induction Motor Servo Drive Using Genetic Algorithms , 2007, IEEE Transactions on Industrial Electronics.

[9]  Chuen-Tsai Sun,et al.  Functional equivalence between radial basis function networks and fuzzy inference systems , 1993, IEEE Trans. Neural Networks.

[10]  Hualin Tan,et al.  Adaptive backstepping control and friction compensation for AC servo with inertia and load uncertainties , 2003, IEEE Trans. Ind. Electron..

[11]  Young-Kiu Choi,et al.  An adaptive neurocontroller using RBFN for robot manipulators , 2004, IEEE Trans. Ind. Electron..

[12]  Chia-Feng Juang,et al.  Water bath temperature control by a recurrent fuzzy controller and its FPGA implementation , 2006, IEEE Transactions on Industrial Electronics.

[13]  Paolo Rocco,et al.  Single and multistate integral friction models , 2004, IEEE Transactions on Automatic Control.

[14]  A. Shoulaie,et al.  Online control of thrust and flux in linear induction motors , 2003 .

[15]  Ion Boldea,et al.  Linear electric actuators and generators , 1997, 1997 IEEE International Electric Machines and Drives Conference Record.

[16]  I. Boldea,et al.  Linear Electric Actuators and Generators: Linear Electric Actuators and Generators , 1997 .

[17]  Hui Li,et al.  A Stochastic Digital Implementation of a Neural Network Controller for Small Wind Turbine Systems , 2006, IEEE Transactions on Power Electronics.

[18]  E. Mizutani,et al.  Neuro-Fuzzy and Soft Computing-A Computational Approach to Learning and Machine Intelligence [Book Review] , 1997, IEEE Transactions on Automatic Control.

[19]  Karl Johan Åström,et al.  Adaptive Control , 1989, Embedded Digital Control with Microcontrollers.

[20]  K. Nam,et al.  Field-oriented control scheme for linear induction motor with the end effect , 2005 .

[21]  Tzuu-Hseng S. Li,et al.  Implementation of human-like driving skills by autonomous fuzzy behavior control on an FPGA-based car-like mobile robot , 2003, IEEE Trans. Ind. Electron..

[22]  Weiping Li,et al.  Applied Nonlinear Control , 1991 .

[23]  Daijin Kim,et al.  An implementation of fuzzy logic controller on the reconfigurable FPGA system , 2000, IEEE Trans. Ind. Electron..

[24]  Hui Li,et al.  Digital Anti-Windup PI Controllers for Variable-Speed Motor Drives Using FPGA and Stochastic Theory , 2006, IEEE Transactions on Power Electronics.