A vehicle dynamics control system (NCS) has been developed in this study for improving vehicle yaw rate dynamics under unreliable communication links with packet dropouts, and network-induced delay which are two typical network constraints of unreliable transmission. The NCS system consists of a fuzzy H∞ static output feedback controller. After giving the nonlinear model of the vehicle, a TakagiSugeno (T-S) fuzzy model representation is first discussed. Next, based on the Lyapunov krasovskii functional approach and a parallel distributed compensation scheme, the gains of the fuzzy controller are determined in terms of Linear Matrix Inequality (LMI). Simulations have been conducted to evaluate performance of the closed loop system under limitation of the network resources caused by data transmission.
The aim of this paper concerns the design of a process control algorithm for a class of continuous largescale systems where the measures and control functions are distributed on calculating members which can be shared with other applications and connected to digital network communications. At first, the nonlinear large-scale system is described by a Takagi-Sugeno fuzzy model (TS). After that, by using a fuzzy Lyapunov-Krasovskii functional, sufficient conditions of asymptotic stability of the behavior of the decentralized system controlled network (DNCS), are developed in terms of Linear Matrix Inequalities (LMIs). Finally, to illustrate the proposed approach, a numerical example and simulation results are presented.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.