Fault Detection Based On T-S Fuzzy Model For Nonlinear Networked Control Systems

With the continued development and successful application of electronic technology,network technology and control science, networked control systems with the advantages ofresource sharing and distribution of remote control have attracted a lot of attentions.Networked control system can bring many benefits, but there are some basic problems whichwill affect the system security and reliability. As an effective method, fault detection ofnetworked control system is applied to improve the system security and reliability, and thismethod has also been widely used in industry.At present, fault detection of networked control system's research is mostly based onlinear systems, but in real life networked control systems are often based on nonlinearsystems. In this paper, fault detection of nonlinear networked control systems is discussed asfollows:Firstly, the fault detection for a class of time-varying delay and uncertain nonlinearnetworked control systems is discussed. Based on T-S fuzzy modeling method, a newnonlinear networked control system is constructed. Moreover, an observer is designed todetect faults. Stability conditions in terms of linear matrix inequality are also provided.Secondly, Based on H∞filter and T-S fuzzy modeling method, the robust faultdetection of a class of nonlinear networked control systems with modeling uncertainties isstudied. By using the inputting delay approach, the nonlinear networked systems withnetwork transmission delays are equivalently transformed into a class of continuous-timesystems with communication delays in probability distribution and propose sufficientconditions for asymptotical stability of the observer-based closed-loop systems.Finally, the fault detection for nonlinear networked control systems with random packetloss and the fault detection for nonlinear networked control systems with delay and randompacket loss are discussed. Random packet losses from the sensor to the controller and fromthe controller to the actuator are described by a binary switching sequence satisfying aBernoulli distribution. Meanwhile, the fuzzy observer is designed by using the fuzzydominant subsystem rule and we propose sufficient conditions for asymptotical stability of theobserver-based closed-loop systems, through the simulation, one numerical example is givento illustrate the effectiveness and reliability of the proposed results.