In this article we review several intelligent and robotic algorithm approaches and then propose a novel neural-network (NN)-based approach for nonlinear systems. The nonlinear systems can be represented by the nonlinear Takagi-Sugeno and NN models. Linear differential inclusion (LDI) state-space representation is utilized to deal with stability analysis and control problems on oceanic structures. The stability conditions for the neural-fuzzy logic criteria are derived utilizing the LDI representation. The stability analysis via Lyapunov theory can guarantee the stability of a time-delay tension leg platform (TLP) system.