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This paper investigates interference mitigation and read rate improvement by using novel power control and graph‐based scheduling schemes for radio frequency identification (RFID) systems.

The first method is a distributed power control (DPC) scheme proposed as an alternative to listen‐before‐talk (LBT) for RFID systems specified under CEPT regulations. The DPC algorithm employs reader transmission power as the system control variable to achieve a desired read range and read rate without causing unwanted interference. The second approach is graph‐based scheduling, which uses a graph coloring‐based approach to temporally separate readers with overlapping interrogation zones. The scheduling of the timeslots is carried out so as to offer better efficiency for each reader.

This paper shows that power control, graph theory, collision probability analysis along with timeslot scheduling schemes can be widely adapted to solve general RFID problems. The study shows that selection of timeslot allocation schemes should be carried out after carefully analysing the process/workflow in the application domain. While fair scheduling schemes can be applicable to stable manufacturing environments, event‐triggered scheduling schemes are more effective in fairly chaotic environments.

The study shows that the proposed interference mitigation and read rate improvement techniques can be generalized to assist in design, development, and implementation of a variety of RFID‐based systems, ranging from supply chain level operations to shop floor control. The proposed techniques improve not only the reliability of RFID systems but, more importantly, improve business processes that rely on RFID data.

This paper presents an overview on the Auto‐ID (Automatic Identification) technologies testbed that has been established at the University of Missouri‐Rolla (UMR) with the objective of supporting research, development, and implementation of Auto‐ID technologies in network‐centric manufacturing environments.

UMR's Auto‐ID testbed uses a unique hardware‐in‐the‐loop simulation methodology, which integrates decision‐making model development with the design of networking topology and data routing/scheduling schemes, in order to develop, test, and implement viable Auto‐ID solutions. The methodology is founded on a 3‐level integrated model: controller simulation, distributed controller simulation, and distributed controller simulation with hardware‐in‐the‐loop.

This paper discusses two case studies that highlight the effective use of RFID technology, its potential advantages, challenges, and deficiencies stemming from particular applications. These applications include dock doors, automated guided vehicles, conveyor and automated storage/retrieval systems, integration of RFID middleware with programmable logic controllers, and inventory management of time‐sensitive materials.

The paper presents an innovative idea: hardware‐in‐the‐loop simulation methodology to design automation systems. The approach has been implemented on a variety of applications, which are presented in the paper as case studies.

The purpose of this paper is to present a new way for identification of products/parts and their tracking during the whole life cycle, from the manufacture and assembly phase to the disassembly phase.

Radio frequency identification (RFID) technology is applied on a chosen product, an in‐mould labelling (IML) robot.

This paper discusses a case study that highlights the use of RFID as automatic identification technology, especially in the processes of assembly/disassembly of the IML robot. The application can be expanded onto any kind of product, with the exception of some life cycle phases that are specific for a particular product.

The paper gives an example of how RFID technology can actually be realized in the case of the IML robot to improve the quality of tracking its main components.

The users have the possibilities to access and analyze information about the products/parts during their cycle.

There are high expectations for reliability, safety and fault tolerance are high in chemical plants. Control systems are capable of potential faults in the plant processing systems. This paper proposes is a new Fault Tolerant Control (FTC) system to identify the probable fault occurrences in the plant.

A Fault Diagnosis and Isolation (FDI) module has been devised based on the estimated state of system. An Unscented Kalman Filter (UKF) is the main innovation of the FDI module to identify the faults. A Multi-Sensor Data Fusion algorithm is utilized to integrate the UKF output data to enhance fault identification. The UKF employs an augmented state vector to estimate system states and faults simultaneously. A control mechanism is designed to compensate for the undesirable effects of the detected faults.

The performance of the Nonlinear Model Predictive Controller (NMPC) without any fault compensation is compared with the proposed FTC scheme under different fault scenarios. Analysis of the simulation results indicates that the FDI method is able to identify the faults accurately. The proposed FTC approach facilitates recovery of the closed loop performance after the faults have been isolated.

A significant contribution of the paper is the design of an FTC system by using UKF to estimate faults and enhance the accuracy of data. This is done by applying a data fusion algorithm and controlling the system by the NMPC after eliminating the effects of faults.