Embedded Systems Design - March 2008 - (Page 25)

0308esd.p16to25 2/14/08 3:51 PM Page 25 cover feature to the defuzziﬁcation module to convert the fuzzy value back to a crisp value. The resulting crisp value is a PWM offset that is added to the current PWM duty cycle; creating a closed loop system. The updated PWM value is checked to see if the new value is within bounds, and appropriate action is taken if it is not. Finally the fuzzy controller returns the updated PWM duty cycle count to the calling routine. Figure 8 shows a debug session of the demo application. Channels 1 &2 (the display window in the upper-right hand corner) displays the PWM counter, and the capture of the hall-effect sensors respectively. Channels 3 & 4 (the display window beneath channels 1 & 2) show the edge-triggered versions of the PWM counter and the hall-effect sensors. The watch window displays important variables. Most important are SetSpeed, and CurrentSpeed. These values are close enough so that the output of the fuzzy controller has a zero value. Also note the other values used in the controller process. This session shows the motor under no-load conditions. The behavior may be slightly different with a load. Moreover, if a ﬁner granularity is desired it may be necessary to tune the controller. ■ Byron Miller is an independent ﬁrmware engineer specializing in the design of microprocessors, DSPs, hardware debug, porting, as well as the development of ﬁrmware for control, data acquisition, fuzzy logic, and Internet appliances. He has a BA in computer science and a masters in software engineering. You can reach him at bmiller2@isd.net. Demonstration application motor control block diagram. 3.3V 6 - PWMs TMS320F/C2812 X1 CAP1 - 3 Hall effect sensors 12Vdc 3-Phase inverter 3-Phase BLDC motor X2 Figure 7 Motor debug session. Figure 8 Brubaker, David. “Fuzzy-logic system solves control problem,” EDN June 18, 1992, p. 121. Brubaker, David. “Design and simulate your own fuzzy setpoint controller,” EDN January 5, 1995, p. 167. V. Donescu, D.O. Ncacsu, G. Griva, “Design of a Fuzzy Logic Speed Controller for Brushless DC Motor Drives,” IEEE Spectrum September 1996, p. 404. M. Chow, Y. Tipsuwan, “Fuzzy Logic Microcontroller Implementation for DC Motor Speed Control,” IEEE Spectrum March 1999, p. 1271. J. Lee, T. Im, H. Sung, Y. Kim, “A Low Cost Speed Control System of Brushless DC Motor Using Fuzzy Logic,” IEEE Spectrum April 1999, p. 433. Miller, Byron. “A Top-Down Approach to Fuzzy Logic Design,” Embedded Systems Programming, July 1998, p. 52. Simon, Dan. “Fuzzy Control,” ESP July, 2003, p. 55. Miller, Byron. “Fuzzy Logic Does Real Time on the DSP,” Dr. Dobbs Journal, July 2004, p. 25. Fuzzy Logic: An Overview of the Latest Control Methodology. (TI doc – SPRA028). Fuzzy Logic Motor Control with MSP430x14x. (TI doc- SLAA235). TMS320F/C28xx Data Manual. (TI doc – SPRS174M). FURTHER READING: Von Altrock, Constantin. Fuzzy Logic and NeuroFuzzy Applications Explained. Englewood Cliffs, NJ: Prentice Hall, 1995. Miller, Byron. The Design and Development of Fuzzy Logic Controllers. Minneapolis, MN: Impatiens Publications, 1997 G. Klir, D. Schwartz, “Fuzzy logic ﬂowers in Japan, IEEE Spectrum JULY 1992, p. 32. Brubaker, David. “Fuzzy-logic basics: intuitive rules replace complex math,” EDN June 18, 1992, p. 111. www.embedded.com | embedded systems design | MARCH 2008 25 http://www.embedded.com

Table of Contents Feed for the Digital Edition of Embedded Systems Design - March 2008

Embedded Systems Design - March 2008 Contents #Include Programming Pointers Designing DSP-based Motor Control Using Fuzzy Logic Hardware/Software Verification Enters the Atomic Age Efficient CRC Calculation with Minimal Memory Footprint Programming Your Own Microcontroller Advertising Index Break Points Marketplace

Embedded Systems Design - March 2008

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