Rapid developments in wireless sensor networks have extended many applications, hence, many studies have developed wireless sensor network positioning systems for indoor environments. Among those systems, the Global Position System (GPS) is unsuitable for indoor environments due to Line-Of-Sight (LOS) limitations, while the wireless sensor network is more suitable, given its advantages of low cost, easy installation, and low energy consumption. Due to the complex settings of indoor environments and the high demands for precision, the implementation of an indoor positioning system is difficult to construct. This study adopts a low-cost positioning method that does not require additional hardware, and uses the received signal strength (RSS) values from the receiver node to estimate the distance between the test objects. Since many objects in indoor environments would attenuate the radio signals and cause errors in estimation distances, knowing the path loss exponent (PLE) in an environment is crucial. However, most studies preset a fixed PLE, and then substitute it into a radio propagation loss model to estimate the distance between the test points; such method would lead to serious errors. To address this problem, this study proposes a Path Loss Exponent Estimation Algorithm, which uses only four beacon nodes to construct a radio propagation loss model for an indoor environment, and is able to provide enhanced positioning precision, accurate positioning services, low cost, and high efficiency.
Boundary feedback control of networks of freeway traffic is considered in this paper by means of Partial Differential Equations (PDEs) based techniques. The control and measurements are all located at the boundaries of each link. We have established the boundary control model for the system, a linear hyperbolic system of balance laws, which includes not only the traffic flow dynamics of the network described by combining the linearized Aw-Rascle-Zhang (ARZ) traffic flow model of each link, but also the integrated on-ramping metering and variable speed limit control modeled as the boundary condition. As the traffic demand of the network is fluctuated, the boundary Inputto-State Stability (ISS) controller is designed to suppress the disturbance and regulate the traffic flow into the boundedness regions of the desired states. Based on a novel Lyapunov function, some sufficient conditions in terms of the matrix inequalities are derived for the ISS boundary stabilization in the L 2 norm. The numerical simulation is given to illustrate the effectiveness of the developed boundary feedback control. Moreover, an interesting traffic experiment is carried out by using the traffic simulation software, AIMSUN, and some specific traffic data are collected and analyzed to verify the feasibility and effectiveness of the boundary control.
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