Speed control of brushless DC motors using emotional intelligent controller

This paper presents an improved emotional controller for brushless DC motor (BLDC) drive. The proposed controller is called brain emotional learning based intelligent controller (BELBIC). The utilization of the new controller is based on the emotion processing mechanism in brain. This intelligent control is inspired by the limbic system of mammalian brain, especially amygdala. The controller is successfully implemented in simulation using MATLAB software, brushless dc drive with trapezoidal back-emf. In this work, a novel and simple implementation of BLDC motor drive system is achieved by using the intelligent controller, which controls the motor speed accurately. This emotional intelligent controller has simple structure with high auto learning feature. Simulation results show that both accurate steady state and fast transient speed responses can be achieved in wide range of speed from 20 to 300 [rpm]. Moreover, for evaluate this emotional controller and hence to assess the effectiveness and control capability of the proposed BELBIC scheme, the performances of proposed control scheme are compared with a conventional PID controller for the BLDC drive control, in simulation different conditions. This is shown proper operating than the PID controller. And also shows excellent promise for industrial scale utilization.

[1]  Caro Lucas,et al.  Introducing Belbic: Brain Emotional Learning Based Intelligent Controller , 2004, Intell. Autom. Soft Comput..

[2]  Marian P. Kazmierkowski,et al.  Direct torque control of PWM inverter-fed AC motors - a survey , 2004, IEEE Transactions on Industrial Electronics.

[3]  Z. Y. Pan,et al.  Steady state reference current determination technique for brushless DC motor drive system , 2005 .

[4]  J. Morén,et al.  A computational model of emotional learning in the amygdala. , 2000 .

[5]  Z.Q. Zhu,et al.  Direct torque control of brushless DC drives with reduced torque ripple , 2004, Conference Record of the 2004 IEEE Industry Applications Conference, 2004. 39th IAS Annual Meeting..

[6]  Dong-Choon Lee,et al.  Automatic Mode Switching of P/PI Speed Control for Industry Servo Drives Using Online Spectrum Analysis of Torque Command , 2007, IEEE Transactions on Industrial Electronics.

[7]  Magali R. G. Meireles,et al.  A comprehensive review for industrial applicability of artificial neural networks , 2003, IEEE Trans. Ind. Electron..

[8]  C. Lucas,et al.  Emotional controller (BELBIC) for electric drives — A review , 2010, IECON 2010 - 36th Annual Conference on IEEE Industrial Electronics Society.

[9]  Yen-Shin Lai,et al.  New hybrid fuzzy controller for direct torque control induction motor drives , 2003 .

[10]  Pragasen Pillay,et al.  Modeling, simulation, and analysis of permanent-magnet motor drives. II. The brushless DC motor drive , 1989 .

[11]  Leang-San Shieh,et al.  Load Disturbance Resistance Speed Controller Design for PMSM , 2006, IEEE Transactions on Industrial Electronics.

[12]  Caro Lucas,et al.  Real-time embedded emotional controller , 2010, Neural Computing and Applications.

[13]  Changliang Xia,et al.  Adaptive Speed Control for Brushless DC Motors Based On Genetic Algorithm and RBF Neural Network , 2007, 2007 IEEE International Conference on Control and Automation.

[14]  Babak Nadjar Araabi,et al.  Implementation of Emotional Controller for Interior Permanent Magnet Synchronous Motor Drive , 2006, Conference Record of the 2006 IEEE Industry Applications Conference Forty-First IAS Annual Meeting.

[15]  C. Lucas,et al.  Simultaneously, speed and flux control of a induction motor, with brain emotional learning based intelligent controller (BELBIC) , 2009, 2009 IEEE International Electric Machines and Drives Conference.

[16]  Changliang Xia,et al.  Control of Brushless DC Motor Using Fuzzy Set Based Immune Feedback PID Controller , 2007, 2007 IEEE International Symposium on Industrial Electronics.

[17]  Hong Huo,et al.  A generic neurofuzzy model-based approach for detecting faults in induction motors , 2005, IEEE Transactions on Industrial Electronics.

[18]  Caro Lucas,et al.  Sensorless speed control of switched reluctance motor using brain emotional learning based intelligent controller , 2011 .

[19]  S. Gopalakrishnan,et al.  Keeping cool while saving space and money: a semi-integrated, sensorless PM brushless drive for a 42-V automotive HVAC compressor , 2005, IEEE Industry Applications Magazine.

[20]  Bimal K. Bose,et al.  Neural Network Applications in Power Electronics and Motor Drives—An Introduction and Perspective , 2007, IEEE Transactions on Industrial Electronics.

[21]  Arash Arami,et al.  Emotion on FPGA: Model driven approach , 2009, Expert Syst. Appl..

[22]  Babak Nadjar Araabi,et al.  Brain emotional learning based intelligent controller applied to neurofuzzy model of micro-heat exchanger , 2007, Expert Syst. Appl..

[23]  The Math Works, Inc. The Math Works Inc , 1991, International Conference on Advances in System Simulation.

[24]  G.R.A. Markadeh,et al.  Position sensorless direct torque control of BLDC motor by using modifier , 2008, 2008 11th International Conference on Optimization of Electrical and Electronic Equipment.

[25]  Ching-Tsai Pan,et al.  A Phase-Locked-Loop-Assisted Internal Model Adjustable-Speed Controller for BLDC Motors , 2008, IEEE Transactions on Industrial Electronics.

[26]  G R Arab Markadeh,et al.  Speed and Flux Control of Induction Motors Using Emotional Intelligent Controller , 2011, IEEE Transactions on Industry Applications.

[27]  Jung-Pyo Hong,et al.  Reducing torque ripple of brushless DC motor by varying input voltage , 2006, IEEE Transactions on Magnetics.