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

Real-time pressure process control is quite challenging due to high nonlinearity and sensitivity. For the control of such processes, PI/PID controllers are most widely used due to the advantages of simple structure, ease of tuning and implementation. However, the performance of such controllers degrades during set-point change and high external disturbances. Therefore, this paper proposes the application of fractional order PI (FOPI) controllers for real-time control of pressure process. Experimental results of the performance comparison of the three major variants of FOPI controllers (i.e., (PI)n, [PI] and PI) shows that the standard form PI outperformed the other controllers in terms of overshoot while (PI)n produced better results in terms of settling and rise times. Hence, the later has better disturbance ability to recover from effect of disturbance.

Fractional Order PI Controllers for Real-time Control of Pressure Plant

This paper focuses on developing a prediction model to predict heart stroke using the parameters, namely, age, hypertension, previous heart disease status, average body glucose level, BMI, and smoking status. The prediction model is developed using a support vector machine (SVM) algorithm. Further, the SVM algorithm with various decision boundaries like linear, quadratic, and cubic are also produced. The performance prediction results show that the linear and quadratic SVM has performed better in predicting the heart stoke with greater accuracy values. This is true for both the male and female databases during training and testing.

Prediction of Heart Stroke Using Support Vector Machine Algorithm

pH control plays an important role in a wide range of industrial applications for waste management. The high non-linearity in pH neutralization processes and the uncertainty of the plant dynamics are key challenges that cannot be effectively addressed using PID controllers tuned with conventional methods. Some of the available and quite often tuning methods used for designing PID controllers are Cohen-Coon, Ziegler-Nichols (ZN), and Tyreus-Luyben. To address these problems, particle swarm optimization (PSO) is employed to tune the PID controller for a pH neutralization plant. The PSO algorithm is one of the most powerful methods for resolving non-smooth global optimization problems. In this paper, the mathematical model of pH process is developed taking into consideration of the overall plant's dynamics. The PSO based PID controller is then implemented and evaluated by comparing its performance with that of ZN-PID.

Optimal PID control of pH neutralization plant

In networked control system, such as WirelessHART that is characterized by stochastic delay, the use of proportional integral and differential (PID) controllers is inadequate. This is because PID performs poorly in handling time-delay processes. The main reason for this poor performance is the limitation in the range of stable gain of the controller. Time delay causes oscillatory response of the PID with large gain. Likewise, sluggish response is experienced with small gain of the PID. Also, dead time compensators like smith predictor and internal model controller are difficult to be implemented practically since they require exact model of the process to be controlled. Therefore, this paper proposes the application of setpoint weighting strategy to be used alongside PID controller in a WirelessHART network. This method extends significantly the range of the PID gain, while providing good set point tracking and load regulation. From the simulation and experimental results obtained, the capability of the approach to load regulation and tracking can be seen in its fast recovery from effect of disturbance with minimal overshoot. Thus, a two degree of freedom control is achieved. Results also showed that the method is robust to real-time random variable network delay and model mismatches.

Adopting Setpoint Weighting Strategy for WirelessHART Networked Control Systems Characterised by Stochastic Delay

Control of CSTR process has been challenging due to highly nonlinear and dynamic behavior. Furthermore, the CSTR processes are unstable. The use of PID controllers for such processes has been attempted. However, poor performance is obtained due to limitations of the PID controllers. On the other hand, using heuristic algorithms to tune the controllers only gives optimal performance for a restricted range of parameter variations. This paper proposes the use of fuzzy gain scheduling (FGS) adaptation mechanism to tune set-point weighted PID controller for the CSTR process. The result of comparison from the simulation performed showed that proposed method achieved better set-point tracking and disturbance rejection compared to the FGS-PID controller.

Kishore Bingi

Papers

Fractional Order PI Controllers for Real-time Control of Pressure Plant

Prediction of Heart Stroke Using Support Vector Machine Algorithm

Optimal PID control of pH neutralization plant

Adopting Setpoint Weighting Strategy for WirelessHART Networked Control Systems Characterised by Stochastic Delay

Fuzzy gain scheduled set-point weighted PID controller for unstable CSTR systems