Variable-speed drive (VSD) motors provide hope for greatly reducing energy consumption and reliance on foreign fuels. In one approach, digital signal processors (DSPs) are being used to create a new generation of VSD-based controllers for motors such as brushless direct current (BLDC) motors.
However, these motors present challenges. Controlling motor speed on a BLDC motor is complicated when using traditional proportional, integral, and differential (PID) controllers because they rely on a complex mathematical model and are computationally intensive. An alternative approach is to use fuzzy logic (FL) algorithms to eliminate the need for complex math formulas and provide an easy-to-understand solution. FL motor control also has a shorter development cycle compared to PID controllers, and thus a faster time-to-market. This article discusses the process of using FL algorithms to control BLDC motors using a Texas Instruments c28xx fixed-point family of DSPs.
BLDC control model development
Before constructing the FL engine, we must first develop a model to base the design on. FL controllers use heuristic knowledge and express the design using a linguistic description of the model. Rather than develop a model from scratch, we'll use the PID controller model as a starting point. Once developed and implemented, the FL controller is improved by adjusting its parameters.
In general, there are three design steps for developing a FL BLDC controller:
1. Define inputs, outputs, and the controller's range of operation.
2. Define fuzzy membership set functions and rules.
3. Tune the engine.
Figure 1 shows the block diagram of the BLDC controller model.
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