While the KKL-based interval observer approach offers a generic and systematic method for designing interval observers for nonlinear systems, there are potential limitations and drawbacks compared to other interval observer design methods. One limitation is the computational complexity involved in determining the transformation function T and its inverse T∗, especially for high-dimensional systems. The nonlinearity and complexity of the transformation can make it challenging to compute the observer bounds efficiently. Additionally, the conservativeness of the observer bounds may lead to wider intervals, reducing the accuracy of state estimation. Furthermore, the requirement for Lipschitz injectivity of the transformation may impose restrictions on the observability properties of the system, limiting the applicability of the KKL-based interval observer to certain classes of systems.