Recently, the local stability and local stabilization problems have been investigated by several authors for nonlinear systems described by Takagi Sugeno (T S) fuzzy systems.
The effect of delay on several properties of nonlinear systems such as harmonic generation, gain compression/expansion and desensitisation is studied by considering the example of a Duffing oscillator with retarded damping.
This paper proposes a distributed model predictive control (MPC) strategy for a large-scale system that consists of several dynamically coupled nonlinear systems with decoupled control constraints and disturbances.
Many publications have reported effective schemes to apply fuzzy sliding mode control (FSMC) method for the controller design of several high-order nonlinear systems [18, 19, 20, 21].
In addition, the modified Prelle-Singer procedure [17, 18] is used to apply it to a class of second-order nonlinear ordinary differential equations, to solve several physically interesting nonlinear systems, and to identify a number of important linearization procedures.
Based on this study, a methodology to estimate several nonlinear functions in dynamics systems is proposed.
Results of the studies convincingly demonstrate that the system delay has a significant effect on several important properties of nonlinear systems.
Based on the finite-time stability theorem of stochastic nonlinear systems, several sufficient conditions are proposed for guaranteeing the finite-time stability of the controlled neural networks in probability.
Several time integration methods for nonlinear systems are compared.
