A Survey on Model-Based Distributed Control and Filtering for Industrial Cyber-Physical Systems <s> D. Hardware Platform <s> This paper evaluates the performance of a distributed Kalman filter applied to an ultrasound based positioning application with seven sensor nodes. By distributed we mean that all nodes in the network desires an estimate of the full state of the observed system and there is no centralized computation center after deployment. Communication only takes place between neighbors and only once each sampling interval. The problem is solved by communicating estimates between neighbors and then forming a weighted average as the new estimate. The weights are optimized to yield a small estimation error covariance in stationarity. The minimization can be done off line thus allowing only estimates to be communicated. In the experimental setup the distributed solution performs almost as good as a centralized solution. The proposed algorithm also proved very robust against packet loss. <s> BIB001 </s> A Survey on Model-Based Distributed Control and Filtering for Industrial Cyber-Physical Systems <s> D. Hardware Platform <s> Wireless sensor networks (WSN) are becoming increasingly popular, due to the benefits they bring to many applications as well as the increasing availability and maturity of the underlying technology. The fundamental building blocks of these networks are the sensor nodes themselves, the sensors attached to these nodes, and the software running on the nodes. A basic sensor node platform consists of a CPU, a radio and a power supply. For the last 10 years a number of research institutions and companies have been designing and producing nodes with these three components as a minimum. We review how these sensor nodes have evolved over this time and we also categorize the features of various platforms so as to enable an application developer to quickly determine which node is appropriate for their particular network or which features are desirable for inclusion on a custom built sensor platform. <s> BIB002 </s> A Survey on Model-Based Distributed Control and Filtering for Industrial Cyber-Physical Systems <s> D. Hardware Platform <s> This paper demonstrates the feasibility of implementing Real-Time State Estimators (RTSEs) for Active Distribution Networks (ADNs) in Field-Programmable Gate Arrays (FPGAs) by presenting an operational prototype. The prototype is based on a Linear State Estimator (LSE) that uses synchrophasor measurements from Phasor Measurement Units (PMUs). The underlying algorithm is the Sequential Discrete Kalman Filter (SDKF), an equivalent formulation of the Discrete Kalman Filter (DKF) for the case of uncorrelated measurement noise. In this regard, this work formally proves the equivalence the SDKF and the DKF, and highlights the suitability of the SDKF for an FPGA implementation by means of a computational complexity analysis. The developed prototype is validated using a case study adapted from the IEEE 34-node distribution test feeder. <s> BIB003
Sensor network platforms are likewise undergoing a revolution along with improving processors and memories to enhance the capabilities of local processing and computing, and various platforms with different CPUs and operating systems are designed to satisfy the commercial application (see BIB002 for more details). For example, as one of the most popular microsensor platforms, the Mica platform, which is designed by UC Berkeley, is with an Atmel ATmega processor running the TinyOS operating system (see Fig. 2 for its node  ). In  , three typical platforms of sensor networks, i.e., Particle, μNode and Sindrion, are systematically designed by using a serviceoriented approach and the first two ones are confirmed by a BP petrochemical plant in the U.K., where PIC18f6720 and MSP430 microcontrollers are integrated into sensor nodes (see Fig. 3  for more details). In BIB001 , a distributed Kalman filtering algorithm is implemented in the Tmote Sky sensor network together with a small ultrasound receiver in order to realize the localization, where the desired weights are optimized offline to yield a small estimation error covariance in stationarity. Recently, various hardware used for sensor networks and robot platforms are thoroughly surveyed and the scope of services with different facilities are also discussed in  . Finally, the sequential discrete KF algorithm is performed in a field programmable gata array (FPGA) to obtain the real-time state estimate of active distribution networks BIB003 .