A linear approximation requires handling each input separately which multiplies design effort. Similarly, a piecewise linear approach requires the design of several controllers and is costly to implement. A lookup table seems more appropriate for this problem but it takes time to develop, debug and tune. This relationship can also be represented in a table form illustrated in Figure 8 . The fuzzy approach requires significantly less entries than a lookup table depending upon the number of labels for each input variable.
Rules are much easier to develop, and simpler to debug and tune compared to a lookup table.
Another example of simplicity is the classical control problem of the double stage inverted pendulum. Using conventional programming, this problem is extremely difficult, or impossible to implement. Aptronix has demonstrated a physical model of the 2-stage inverted pendulum which was accomplished using only 30 rules. The software portion of the project took only two days to develop. Fuzzy Logic reduces hardware costs Using a lookup table the two-input temperature controller requires 64Kb of memory, while the fuzzy approach is accomplished with less than 0.5Kb of memory for labels and object code combined.