Formation Control of Automated Guided Vehicles in the Presence of Packet Loss.

This paper presents the formation tracking problem for non-holonomic automated guided vehicles. Specifically, we focus on a decentralized leader-follower approach using linear quadratic regulator control. We study the impact of communication packet loss-containing the position of the leader-on the performance of the presented formation control scheme. The simulation results indicate that packet loss degrades the formation control performance. In order to improve the control performance under packet loss, we propose the use of a long short-term memory neural network to predict the position of the leader by the followers in the event of packet loss. The proposed scheme is compared with two other prediction methods, namely, memory consensus protocol and gated recurrent unit. The simulation results demonstrate the efficiency of the long short-term memory in packet loss compensation in comparison with memory consensus protocol and gated recurrent unit.

Wireless Communications for Smart Manufacturing and Industrial IoT: Existing Technologies, 5G and Beyond.

Smart manufacturing is a vision and major driver for change in today's industry. The goal of smart manufacturing is to optimize manufacturing processes through constantly monitoring, controlling, and adapting processes towards more efficient and personalised manufacturing. This requires and relies on technologies for connected machines incorporating a variety of computation, sensing, actuation, and machine to machine communications modalities. As such, understanding the change towards smart manufacturing requires knowledge of the enabling technologies, their applications in real world scenarios and the communication protocols and their performance to meet application requirements. Particularly, wireless communication is becoming an integral part of modern smart manufacturing and is expected to play an important role in achieving the goals of smart manufacturing. This paper presents an extensive review of wireless communication protocols currently applied in manufacturing environments and provides a comprehensive review of the associated use cases whilst defining their expected impact on the future of smart manufacturing. Based on the review, we point out a number of open challenges and directions for future research in wireless communication technologies for smart manufacturing.

Sensor Fusion and State Estimation of IoT Enabled Wind Energy Conversion System.

The use of renewable energy has increased dramatically over the past couple of decades. Wind farms, consisting of wind turbines, play a vital role in the generation of renewable energy. For monitoring and maintenance purposes, a wind turbine has a variety of sensors to measure the state of the turbine. Sensor measurements are transmitted to a control center, which is located away from the wind farm, for monitoring and maintenance purposes. It is therefore desirable to ensure reliable wireless communication between the wind turbines and the control center while integrating the observations from different sensors. In this paper, we propose an IoT based communication framework for the purpose of reliable communication between wind turbines and control center. The communication framework is based on repeat-accumulate coded communication to enhance reliability. A fusion algorithm is proposed to exploit the observations from multiple sensors while taking into consideration the unpredictable nature of the wireless channel. The numerical results show that the proposed scheme can closely predict the state of a wind turbine. We also show that the proposed scheme significantly outperforms traditional estimation schemes.

Modelling, Characterization of Data-Dependent and Process-Dependent Errors in DNA Data Storage.

Using DNA as the medium to store information has recently been recognized as a promising solution for long-term data storage. While several system prototypes have been demonstrated, the error characteristics in DNA data storage are discussed with limited content. Due to the data and process variations from experiment to experiment, the error variation and its effect on data recovery remain to be uncovered. To close the gap, we systematically investigate the storage channel, i.e., error characteristics in the storage process. In this work, we first propose a new concept named sequence corruption to unify the error characteristics into the sequence level, easing the channel analysis. Then we derived the formulations of the data imperfection at the decoder including both sequence loss and sequence corruption, revealing the decoding demand and monitoring the data recovery. Furthermore, we extensively explored several data-dependent unevenness observed in the base error patterns and studied a few potential factors and their impacts on the data imperfection at the decoder both theoretically and experimentally. The results presented here introduce a more comprehensive channel model and offer a new angle towards the data recovery issue in DNA data storage by further elucidating the error characteristics of the storage process.

Oligo Design with Single Primer Binding Site for High Capacity DNA-Based Data Storage.

DNA has become an attractive medium for long-term data archiving due to its extremely high storage density and longevity. Short single-stranded DNAs, called oligonucleotides (oligos), have been designed and synthesized to store digital data. Previous works designed the oligos with a pair of primer binding sites (PBSs) (each with a length of around 200) attached at the two ends of each basic readable data block. The addition of PBSs decreases the data density significantly because in the current DNA synthesis, the maximum length of a synthesized oligo in good quality is around 200. Furthermore, the maximum homopolymer run allowed by the existing experiments has been reported to be three nucleotides. In this work, to increase the data density, we have devised and tested an oligo design for DNA-based storage with the basic readable data block appended by a single PBS at one end only, while allowing the maximum homopolymer run to be increased to 4. We also present an oligo assembly algorithm that can reconstruct oligos with a single PBS from the error-prone raw readouts obtained from the sequencing process. We have conducted a wet lab experiment to validate the proposed design, where we tested with 398KB of data stored into 10,750 oligos. The experimental results show that it is possible to recover over 99 percent of the oligo sequences without error, which proves that one PBS is sufficient for implementing a DNA-based data storage system with maximum homopolymer run relaxed to 4. The use of single PBS leads to a significant data density gain from 14.3 to 140.2 percent over the existing short-strand DNA data storage schemes by reserving more nucleotides for storing information bits.

High capacity DNA data storage with variable-length Oligonucleotides using repeat accumulate code and hybrid mapping.

BACKGROUND: With the inherent high density and durable preservation, DNA has been recently recognized as a distinguished medium to store enormous data over millennia. To overcome the limitations existing in a recently reported high-capacity DNA data storage while achieving a competitive information capacity, we are inspired to explore a new coding system that facilitates the practical implementation of DNA data storage with high capacity. RESULT: In this work, we devised and implemented a DNA data storage scheme with variable-length oligonucleotides (oligos), where a hybrid DNA mapping scheme that converts digital data to DNA records is introduced. The encoded DNA oligos stores 1.98 bits per nucleotide (bits/nt) on average (approaching the upper bound of 2 bits/nt), while conforming to the biochemical constraints. Beyond that, an oligo-level repeat-accumulate coding scheme is employed for addressing data loss and corruption in the biochemical processes. With a wet-lab experiment, an error-free retrieval of 379.1 KB data with a minimum coverage of 10x is achieved, validating the error resilience of the proposed coding scheme. Along with that, the theoretical analysis shows that the proposed scheme exhibits a net information density (user bits per nucleotide) of 1.67 bits/nt while achieving 91% of the information capacity. CONCLUSION: To advance towards practical implementations of DNA storage, we proposed and tested a DNA data storage system enabling high potential mapping (bits to nucleotide conversion) scheme and low redundancy but highly efficient error correction code design. The advancement reported would move us closer to achieving a practical high-capacity DNA data storage system.