## 3 Development of NCS between 2001 to 2010
The performance analysis of the event-triggered control for the detector sampling in a NCS was carried out by Reference [53]. The analytical formula for analyzing the mean and, therefore, the rate of event-driven traffic versus the sampling resolution was obtained. The simulation results in support of the obtained formula were additionally discussed. A fault detection technique for NCSs supporting the parity relation and Principal Component Analysis (PCA) was projected in Reference [54]. The projected methodology noticed an honest decoupling from the unknown and random network-induced delay. In Reference [55] a fault bearing control methodology for the nonlinear NCSs with communication constraints was given. In Reference [56], the Tagaki-Sugeno (T-S) model was utilized to design a networked system with completely different delays induced by the network. When analyzed with the existing system modeling methods, this approach does not need the data of the actual delays induced by the network. The work in Reference [57] focused on the networked system with random time delays and, additionally, bestowed a brand new modeling methodology for the linear and nonlinear NCS with time delays that are random in nature and named those models as similar T-S fuzzy models. A system supported bionic principles was introduced by Reference [58] to demonstrate the information obtained from an oversized range of numerous sensors. By means of that structure symbolization, the quantity of data to be processed was considerably reduced. In Reference [59] the event-triggered control was revisited, from an input-to-output perspective. Review of many modern results on evaluation, investigation, and controller synthesis for networked systems were administered in Reference [60]. Another paper, by Reference [10], surveyed appropriate work from the areas of systems and process control, detection, and estimation. Input delay approach, during which the sample-and-hold circuit can be implanted into an analog system with an input delay which is time-varying, was revised in Reference [61]. The loss of data-packets in the NCSs was mentioned in Reference [62]. In Reference [63], a mathematical model of a small rotorcraft was presented. The identification methodology and state estimation using Extended Kalman Filter were discussed. Control algorithms, based on PI, LQG and SDRE approaches, focused on rotorcraft were also proposed. In Reference [64], the impact of a network within the electrical circuit of a system was discussed. They used an unsystematic loss of data-packet model for the network, and showed the results for discrete-time period systems with stochastic process jumping constraints. In Reference [65] the exponential stability of Nonlinear Time Varying (NLTV) impulsive systems was established with the help of Lyapunov functions separated at the impulse times. In Reference [66], it was observed that for NCSs with delays and output feedback stabilization, there was a deviation in the mean-square stability due to the random communication situations. In Reference [67], a state feedback controller was proposed for the stabilization of an uncertain linear networked control systems with random communication time delays, which differs from the Lyapunov-Razumikh methodology. In Reference [68], a sufficient condition was obtained for the exponential stability of the networked systems, and they also the mentioned relationship between the dropout rate of the data-packets. An occurrence-based discrete-time model (an exponential unsure system with delay) was proposed by Reference [69] that showed that the stability of the projected system can be achieved by finding an effect for a switched stochastic system with an additive norm delimited uncertainty. In Reference [70], the state feedback controllers were considered for a closed-loop NCS that is represented as a delay in switched systems. A technical note involved with the stabilization drawback of NCS was revealed by Reference [71].