Ieee transactions on control systems technology

Condition monitoring can reduce machine breakdown losses, increase productivity and operation safety, and therefore deliver significant benefits to many industries. The emergence of wireless sensor networks (WSNs) with smart processing ability play an ever-growing role in online condition monitoring of machines. WSNs are cost-effective networking systems for machine condition monitoring. It avoids cable usage and eases system deployment in industry, which leads to significant savings. Powering the nodes is one of the major challenges for a true WSN system, especially when positioned at inaccessible or dangerous locations and in harsh environments. Promising energy harvesting technologies have attracted the attention of engineers because they convert microwatt or milliwatt level power from the environment to implement maintenance-free machine condition monitoring systems with WSNs. The motivation of this review is to investigate the energy sources, stimulate the application of energy harvesting based WSNs, and evaluate the improvement of energy harvesting systems for mechanical condition monitoring. This paper overviews the principles of a number of energy harvesting technologies applicable to industrial machines by investigating the power consumption of WSNs and the potential energy sources in mechanical systems. Many models or prototypes with different features are reviewed, especially in the mechanical field. Energy harvesting technologies are evaluated for further development according to the comparison of their advantages and disadvantages. Finally, a discussion of the challenges and potential future research of energy harvesting systems powering WSNs for machine condition monitoring is made.

Energy Harvesting Technologies for Achieving Self-Powered Wireless Sensor Networks in Machine Condition Monitoring: A Review.

Explicit formula and graphs of few special functions are derived in the paper on the basis of various definitions of various fractional derivatives and various fractional integrals. Their applications are also reviewed in the paper.

/pdf/applications-of-fractional-calculus-1c2m93jo56.pdf

Applications of Fractional Calculus

Variable-order fractional operators were conceived and mathematically formalized only in recent years. The possibility of formulating evolutionary governing equations has led to the successful application of these operators to the modelling of complex real-world problems ranging from mechanics, to transport processes, to control theory, to biology. Variable-order fractional calculus (VO-FC) is a relatively less known branch of calculus that offers remarkable opportunities to simulate interdisciplinary processes. Recognizing this untapped potential, the scientific community has been intensively exploring applications of VO-FC to the modelling of engineering and physical systems. This review is intended to serve as a starting point for the reader interested in approaching this fascinating field. We provide a concise and comprehensive summary of the progress made in the development of VO-FC analytical and computational methods with application to the simulation of complex physical systems. More specifically, following a short introduction of the fundamental mathematical concepts, we present the topic of VO-FC from the point of view of practical applications in the context of scientific modelling.

https://royalsocietypublishing.org/doi/pdf/10.1098/rspa.2019.0498

Applications of variable-order fractional operators: a review

Internet of Things (IoT) constitutes the next step in the field of technology, bringing enormous changes in industry, medicine, environmental care, and urban development. Various challenges are to be met in forming this vision, such as technology interoperability issues, security and data confidentiality requirements, and, last but not least, the development of energy efficient management systems. In this paper, we explore existing networking communication technologies for the IoT, with emphasis on encapsulation and routing protocols. The relation between the IoT network protocols and the emerging IoT applications is also examined. A thorough layer-based protocol taxonomy is provided, while how the network protocols fit and operate for addressing the recent IoT requirements and applications is also illustrated. What is the most special feature of this paper, compared to other survey and tutorial works, is the thorough presentation of the inner schemes and mechanisms of the network protocols subject to IPv6. Compatibility, interoperability, and configuration issues of the existing and the emerging protocols and schemes are discussed based on the recent advanced of IPv6. Moreover, open networking challenges such as security, scalability, mobility, and energy management are presented in relation to their corresponding features. Lastly, the trends of the networking mechanisms in the IoT domain are discussed in detail, highlighting future challenges.

/pdf/network-protocols-schemes-and-mechanisms-for-internet-of-4bsu7d7ieu.pdf

Network Protocols, Schemes, and Mechanisms for Internet of Things (IoT): Features, Open Challenges, and Trends

Hybrid PID Based Predictive Control Strategies for WirelessHART Networked Control Systems

https://sciendo.com/pdf/10.34768/amcs-2021-0026

Forecasting Models for Chaotic Fractional–Order Oscillators Using Neural Networks

In this chapter, a toolbox for fractional-order systems and PI/PID controllers using Scilab will be developed. According to our knowledge, the proposed toolbox is the first Scilab based toolbox for fractional-order systems and controllers. The toolbox will be developed in three stages. Initially, the definitions of fractional-order operators, approximation algorithms and fractional-order differentiator and integrator will be implemented. Using these definitions in the second stage, fractional-order systems, controllers, and filters will be developed. The final stage includes the time and frequency domain analysis as well as numerical and stability analysis of the systems.

Scilab Based Toolbox for Fractional-order Systems and PID Controllers

This book presents the study to design, develop, and implement improved PI control techniques, and comparison with the well known PI controllers. 

Optimal Fractional-order Predictive PI Controllers

In industrial applications of wireless technologies, very common, wireless sensor and actuator nodes are installed at fields. Therefore, it is critical to extend battery’s lifetime for ensuring continuous servicing period of field instruments over years. Apart from periodic battery status update during operations of the nodes, at planning stage, plant management team can estimate batteries’ lifetime at field wireless instruments for operational budget estimation and preventive maintenance planning. This work proposes a framework to estimate the battery’s lifetime taken into consideration of periodic update periods and devices’ operational frequencies. The framework is based on the knowledge of wireless node, microcontroller’s power consumption, and battery specifications. Based on the analysis, at particular operational conditions (i.e., update period of 512 s, low-power mode with voltage of 1.8 V), the estimated battery’s lifetime of a wireless node can reach up to 9 years.

Kishore Bingi

Papers

Hybrid PID Based Predictive Control Strategies for WirelessHART Networked Control Systems

Forecasting Models for Chaotic Fractional–Order Oscillators Using Neural Networks

Scilab Based Toolbox for Fractional-order Systems and PID Controllers

Optimal Fractional-order Predictive PI Controllers

Battery’s Life-Time Estimation of Industrial WirelessHART Sensor Actuator Node