Hybrid fuzzy control solutions for Brushless DC drives with Variable Moment of Inertia

This paper proposes four hybrid Takagi-Sugeno fuzzy controllers which consist of two hybrid PI Neuro-Fuzzy Controllers and two Adaptive Sliding Mode Fuzzy Controllers, for speed and position control of Brushless Direct Current motor (BLDC-m) drives. Simplified models of BLDC-m drives are derived and used in the new controller design; these models are characterized by second-order transfer functions with variable parameters and with or without an integral component. The proposed controllers and systematic design methodologies are briefly presented and some particular approaches are highlighted. The control structures exhibit important robustness properties proved by simulation results. The design methodologies guarantee the system stability and offer consistent performance under model uncertainties. Simulation-based comparisons illustrate the efficiency of the controllers.

[1]  Il-kyun Jung,et al.  Optimal tuning of PI-like fuzzy controller using variable membership function' s slope , 2009, 2009 IEEE International Symposium on Assembly and Manufacturing.

[2]  Hideki Hashimoto,et al.  Trajectory Tracking by TP Model Transformation: Case Study of a Benchmark Problem , 2007, IEEE Transactions on Industrial Electronics.

[3]  Juan Dixon,et al.  Current control strategy for brushless DC motors based on a common DC signal , 2002 .

[4]  Claudia-Adina Dragos,et al.  Low-cost fuzzy control approaches to a class of state feedback-controlled servo systems , 2011, 2011 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM).

[5]  Claudia-Adina Dragos,et al.  Speed and position control of BLDC servo systems with low inertia , 2011, 2011 2nd International Conference on Cognitive Infocommunications (CogInfoCom).

[6]  Vadim I. Utkin,et al.  Sliding mode control in electromechanical systems , 1999 .

[7]  Ladislav Madarász,et al.  Adaptation of Fuzzy Cognitive Maps - a Comparison Study , 2010 .

[8]  Asif Sabanovic,et al.  Variable structure systems : from Principles to Implementation , 2004 .

[9]  Vadim I. Utkin,et al.  Adaptive sliding mode control in discrete-time systems , 1995, Autom..

[10]  Weibing Gao,et al.  Discrete-time variable structure control systems , 1995, IEEE Trans. Ind. Electron..

[11]  K. Furuta.  Sliding mode control of a discrete system , 1990 .

[12]  Stefan Preitl,et al.  LOW COST FUZZY CONTROLLERS FOR CLASSES OF SECOND-ORDER SYSTEMS , 2002 .

[13]  Igor Škrjanc,et al.  Adaptive law with a new leakage term , 2010 .

[14]  Endre Pap,et al.  Generalized real analysis and its applications , 2008, Int. J. Approx. Reason..

[15]  Hsuan T. Chang,et al.  A Minimal Fuzzy Gain Scheduling Speed Controller and Torque Compensation for the Variable Sampling System of BLDC Motors , 2011, 2011 Fifth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing.

[16]  H. P. Ikkurti,et al.  Sliding mode scheme for speed and current control of brushless DC (BLDC) motor , 2012, IEEE-International Conference On Advances In Engineering, Science And Management (ICAESM -2012).

[17]  Sylvie Galichet,et al.  Fuzzy controllers: synthesis and equivalences , 1995, IEEE Trans. Fuzzy Syst..

[18]  Hao-Chi Chang,et al.  Sliding mode control on electro-mechanical systems , 1999 .

[19]  Claudia-Adina Dragos,et al.  Low-cost optimal state feedback fuzzy control of nonlinear second-order servo systems , 2011, 2011 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications (CIMSA) Proceedings.

[20]  R. Arulmozhiyal,et al.  Design of Fuzzy PID controller for Brushless DC motor , 2012, 2012 International Conference on Computer Communication and Informatics.

[21]  Rolf Isermann,et al.  Mechatronic Systems: Fundamentals , 2003 .

[22]  Chee-Mun. Ong,et al.  Dynamic simulation of electric machinery : using MATLAB/SIMULINK , 1997 .

[23]  Karl Johan Åström,et al.  PID Controllers: Theory, Design, and Tuning , 1995 .

[24]  Zsolt Csaba Johanyák,et al.  Survey on Five Fuzzy Inference-Based Student Evaluation Methods , 2010 .

[25]  G. Monsees,et al.  Adaptive switching gain for a discrete-time sliding mode controller , 2000, Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334).

[26]  Stefan Baldursson,et al.  BLDC Motor Modelling and Control - A Matlab®/Simulink® Implementation , 2005 .

[27]  Stephen Yurkovich,et al.  Fuzzy Control , 1997 .