Intelligent Tuning of Fuzzy Controllers by Learning and Optimization - Fuzzy Modeling and Control: Theory and Applications - page 145

Fig. 7.8 a Real system response (drilling force) and b control signal (feed rate) in operation with

17-4PH

Table 7.2 Performance indices for the force drilling control experiments using 17-4PH material
Controller ITAE ITSE IT2SE Ovt (%)

ANFIS 3.78 0.45 2.28 3.47

TNFIS 1.42 0.18 0.33 8.21

From the analysis, the reader can figure out how the TNFIS system is capable
of generating local models with satisfactory accuracy and good dynamic behaviour.
Control strategies based on the transductive neuro-fuzzy) paradigm were applied
to drilling force regulation in an industrial environment. A comparative study of