➤A new MF has been introduced by combining trapezoidal and triangular MFs, and the results obtained confirm that the combined one, TTMF, yield better results compared to TrMF and TMF. ➤ Computation in IT2FLS using COS TR and "Wu-Mendel" uncertainty bounds has a different strategy, whereas the uncertainty bounds formulation has given the advantage of reduction of time delay in computation of IT2FLS. ➤ The MF having lesser parameters like GMF and SEMF has a higher accuracy rate than TrMF, TMF, and TTMF. ➤ Formulation of IT2FLS using uncertainty bounds can be replaced in place of type reductions, which proved as an equal substitution in place of type reduction. ➤ The results confirmed that the IT2FLS with GMF in both COS TR and "Wu-Mendel" uncertainty bounds has improved by 1% average error rate than the T1FLS [1]. ➤ In addition, the GMF, along with the "WuMendel" uncertainty bound and COS-TR method, is the best option compared to all others. ➤ The formulation of IT2FLS can be performed in two ways by using COS TR and "Wu-Mendel" uncertainty bounds. IT2FLS with "Wu-Mendel" uncertainty bounds has shown little better performance than COS TR. The future research directions are: ◆ The MFs can also be defined in terms of parameters associated with variable-gain nonlinear controller, which remains unexplored for SEMF and TTMF. ◆ The performance can be further studied based on the combination of MF, like trapezoidal with Gaussian, trapezoidal with semi-elliptic, and so on. Such a kind of membership may perform well in the prediction of uncertainties.