Techno-Economic Evaluation of 5G Technology for Automated Guided Vehicles in Production

The fifth generation of mobile communication (5G) is expected to bring immense benefits to automated guided vehicles by improving existing respectively enabling 5G-distinctive network control systems, leading to higher productivity and safety. However, only 1% of production companies have fully deployed 5G yet. Most companies currently lack an understanding of return on investment and of technical use-case benefits. Therefore, this paper analyses the influence of 5G on an automated guided vehicle use case based on a five-step evaluation model. The analysis is conducted with a use case in the Digital Experience Factory in Aachen. It shows a difference of net present value between 4G and 5G of 1.3 M€ after 10 years and a difference of return of investment of 66%. Furthermore, analysis shows an increase of mobility (13%), productivity (20%) and safety (136%). This indicates a noticeable improvement of a 5G-controlled automated guided vehicle compared to a 4G-controlled automated guided vehicle.

Criticality Aware Scheduler Prioritization in Virtual Orthogonal Multichannel Parallelism for 5G Cellular Network

To fulfill various enhanced requirements of next generation wireless access, 5 G cellular network will drive towards higher energy efficiency, lower latency and higher reliable wireless networks. The key contributions can summarize as follows: (1) proposes frame-based max-weight scheduling (FMWS) with reconfiguration delay in combination of round–robin algorithm can dynamically control throughput and delay. The frame-based dynamic control (FBDC) policy is applicable to 5 G cellular network control systems in data link layer, provides a new framework for developing throughput-optimal network control policies using state-action frequencies. (2) proposes a novel approach in MAC layer--Virtual multichannels Parallelism Carrier Sense Multiple Access (VMCP-CSMA) which can compute a set of TDDM schedules for multiple channels at once rather than computing one schedule at a time and constantly switching or recomputing schedules. (3) proposes a novel criticality aware scheduler prioritization in VMCP-CSMA policy can reorder a set of TDDM schedules based on max-weight scheduling with reconfiguration delay according to different application requirements. It can achieve high throughput and low delay with low complexity compared with other schedulings.

Asymptotical Synchronization of Drive-Response Networks by Sample-Data-Based Event-Triggered Control with Quantization and Cyber-Attacks

This paper addresses the asymptotic synchronization problem for a kind of drive-response complex networks (DRCNs) under cyber-attacks by using network control systems (NCSs). In order to reduce the pressure of communication and save the communication bandwidth on NCSs, some sampled-data-based event-triggered synchronization feedback controllers and logarithmic quantizers are designed by taking into account the effect of the NCSs’ transmission delays. Using Lyapunov stability theories, several sufficient conditions are obtained to guarantee the existence of sampleddata- based event-triggered synchronization controllers for the DRCNs with distributed-delay. Then, the state feedback gains are obtained by solving certain linear matrix inequalities (LMIs). Finally, a numerical example is provided to illustrate the effectiveness of the sampled-data-based eventtriggered control scheme.

Influence of working conditions in agricultural enterprises on fatigue and labor productivity

The article summarizes the results of studying the influence of harmful production factors on the fatigue of agricultural workers and labor productivity. The purpose of the study: to determine the possibilities of improving work efficiency and productivity by improving the sanitary and hygienic conditions in the workplace. The relevance of the work is determined by the fact that in the coming years, we can expect an increase in labor productivity of no more than 3% at a given 5-6%, which requires a search for options for changing the trend. The research methodology is based on the study of published works and the identification of the degree of influence of harmful factors in the workplace on human performance and labor productivity. In conclusion, we offer options for solving the problem. The first is to bring jobs to regulatory requirements by known methods, which in most cases does not require significant financial costs, but will significantly affect the growth of labor productivity, bringing this figure to 7%. The second is the exclusion of a person from the zone of harmful factors due to remote control systems with instrument control and video surveillance of technological processes, full automation of production processes and the transition to neural network control systems, robotics.

ARCH-COMP20 Category Report: Artificial Intelligence and Neural Network Control Systems (AINNCS) for Continuous and Hybrid Systems Plants

This report presents the results of a friendly competition for formal verification of continuous and hybrid systems with artificial intelligence (AI) components. Specifically, machine learning (ML) components in cyber-physical systems (CPS), such as feedforward neural networks used as feedback controllers in closed-loop systems are considered, which is a class of systems classically known as intelligent control systems, or in more modern and specific terms, neural network control systems (NNCS). We more broadly refer to this category as AI and NNCS (AINNCS). The friendly competition took place as part of the workshop Applied Verification for Continuous and Hybrid Systems (ARCH) in 2020. In the second edition of this AINNCS category at ARCH-COMP, four tools have been applied to solve seven different benchmark problems, (in alphabetical order): NNV, OVERT, ReachNN*, and VenMAS. This report is a snapshot of the current landscape of tools and the types of benchmarks for which these tools are suited. Due to the diversity of problems, lack of a shared hardware platform, and the early stage of the competition, we are not ranking tools in terms of performance, yet the presented results probably provide the most complete assessment of current tools for safety verification of NNCS.