$3.$ The fuzzy PD rulebase is the most common form of fuzzy controller you find in the literature. The inputs are the plant state error $\backslash ($ e $\backslash )($versus the current set point of the plant$),$ and its derivative $\backslash ($ d e $\backslash ),$ and the output is the control signal $\backslash ($ u $\backslash )$ to be sent to the plant to correct the error $\backslash ($ e $\backslash ).$ For a ficeway partition of each variable, a typical fuzzy PD rulebase would look like this:

b$)$ Determine the parameters for, and plot, equal triangular membership functions for each of the linguistic values in each variable. Assume the universes of discourse are $\backslash ([-1,1]\backslash )$ for each variable.

c$)$ You probably noticed that the part of the universe of discourse where PL and NL is the strongest membership are half the size of the other membership functions. The s$-$ and z $-$ shaped membership functions let you address this problem. Redo part $($b$),$ but this time make sure that each of the five membership functions has an equal$-$sized partition of the universe of discourse where they are the strongest.

Just B and C