JCD 2024年第3期新鲜出炉！

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B. Balaji, S. Ganesan, P. Pugazhendiran & S. Subramanian

Renewable energy sources are being incorporated into power networks to guarantee dependable and inexpensive electricity for the urban and industrial sectors. Recent research approximates microgrids powered by renewable energy and controlled by smart grids may provide more reliable and efficient energy systems economically. Its natural interaction among renewable energy sources, electric demands, and energy storage devices makes DC microgrid a contemporary electrical grid technology. In this paper, a nonlinear control approach with outstanding precision, robustness, and simplicity of tuning and implementation, is made to deal with the control of the DC microgrid system to bring out the efficacy of the system at higher points. A closed-loop continuous time sliding mode controller is proposed for a boost converter with a cascade filter. DC microgrid system with sliding mode controller is simulated and the analysis has been carried outs with motor load to check the adequacy of the proposed system.

Guduru Naga Divya & Sanagapallea Koteswara Rao

Surveillance of underwater for maritime warfare is traditionally being carried out by bearings-only tracking from many decades. The measurements used for state estimation here are nonlinear. Also the noise in the measurements and the process cannot be always Gaussian. The traditional nonlinear filtering algorithms like extended Kalman filter and modified gain extended Kalman filter use the linearisation of the system. The unscented Kalman filter (UKF) uses the sigma point approach based on Gaussian distribution to deal with nonlinearity. The particle filter (PF) uses the randomly generated particles based on the pdf of the state. PF is highly complex to implement and it also suffers from sample impoverishment. Hence, ensemble Kalman filter (EnKF) which is a simplified form of PF will be tried out for bearings-only tracking in this research work. The performance of EnKF is compared with PF and UKF and the results obtained using these filters in Matlab are presented.

Athanasios Siouras, Konstantinos Stergiou, Patrik Karlsson & Serafeim Moustakidis

ABSTRACT

Due to their detection capabilities and low cost, unmanned aerial vehicles (UAVs) are commonly used in search and rescue (SAR) operations. In a SAR mission, the UAV's height may change, causing objects to shrink or increase thus affecting generalization. This paper proposes a hybrid object detection (OD) technique that combines altitude-dependent local deep learning (DL) models, each one designed for a given flight altitude range. Seven cutting-edge OD models, including YOLOv4 and v5, EfficientDet, Detectron2, MobileNet, and Faster R-CNN, were trained locally with YOLOv5 and Scaled YOLOv4 being the best performers in low and high-altitude images, respectively. The suggested hybrid strategy, which uses the best OD performers, outperformed well-known DL algorithms with 86.2% mAP on a public dataset. Computing efficiency and accuracy with images of varying resolutions were also explored. Dividing the fundamental detection issue into local subproblems that are treated separately by powerful OD networks might increase SAR capabilities.

Joshua Ojo Nehinbe

ABSTRACT

The advancements in digital circuits have led to the development of very complex and large assemblies of logic gates that are electronically integrated together to synthesize highly effective electronics, microprocessors and computer systems. However, the complexity of these devices must be succinctly simplified to achieve simplest circuits. The functions of some logic gates in the circuits must be inverted to minimize the existence of noise and other sources of interference that can distort the performance of the circuits. Besides, most circuit designers and programmers often oversight thorough diagnosis of the Boolean expressions for designing digital circuits. This paper proposes 26 new theorems of digital logic. The proven theorems demonstrate that logic gates are prominently embedded within the elements of hexadecimal notations and the Boolean expressions that are used for designing digital circuits, synthesizing and inverting the functions of six different logic gates during the simplification of complex digital circuits.

Shanshan Zheng, Guofeng Chen & Yaojun Zhang

ABSTRACT

The comprehensive trade-off among reliability, maintainability, availability and life cycle cost should be solved in the overall design of warship equipment. Maintainability analysis and comprehensive trade-off of naval ships equipment based on the PROMETHEE method are proposed. In the method, the evaluation model of alternatives set is formed through the analysis of maintainability-related factors, the determination of target attribute and related attribute weight of alternatives, the selection of attribute priority function and threshold. And carry out calculation and analysis, form the ranking of alternatives. Combined with the calculation and analysis of specific examples, the evaluation results of six groups of alternatives are obtained, and the optimal scheme is determined. The research provides an effective theoretical basis for maintainability analysis and comprehensive trade-off of system overall design. It guides the implementation and decision of the project. It’s suitable for the comprehensive trade-off problem of multi-objective relationships to find the optimal solution.

K. Naresh, P. Umapathi Reddy & P. Sujatha

ABSTRACT

Due to their numerous advantages, wind turbines with changeable speed power production systems are increasingly being used. This study proposes the architecture and specifications of an induction turbine-generating wind system, as well as a PI controller-based DC voltage link regulator and optimal torque control system. The suggested control technique as stated in this paper allows the system to function in grid-linked mode as well as the islanded mode and also in parallel with other power generation units, loads, FACTS devices, etc. This paper involves the analysis of different test cases in grid-connected mode as well as an islanded mode with a PV generation unit, passive loads, induction motor loads, and other wind energy generation systems. The paper also includes an analysis of the response of the system with the switching on and off of the other units. MATLAB 2013a thereby validates the system findings and analysis.

Huchang Liao, Yue Xiao, Zheng Wu & Zhi Wen

ABSTRACT

Multiple criteria sorting (MCS) refers to assigning alternatives to ordered classes based on the evaluation values of alternatives on multiple criteria. Researchers have developed various methods to solve MCS problems. There is a need to sort out the research in this area to enable researchers to understand the current state of research and the challenges in terms of methods and applications. Different from existing review papers on MCS methods, this paper explores the research progress of MCS methods and summarises characteristics and limitations of existing MCS methods. The research status, key areas of focus, and emerging trends in this field are outlined through bibliometric analysis. Characteristics of different MCS methods from the perspectives of value/utility functions, outranking relations, and decision rules are analysed and then the applications of MCS methods are summarised. Finally, lessons learned from the review and future research directions are discussed.

Tao Ren, Shixiang Sun, Yanjie Xu & Georgi Marko Dimirovski

ABSTRACT

Identification of key nodes in complex networks can effectively speed up the spread of favourable information or prevent the spread of rumours and diseases. An algorithm based on local gravity model is proposed to mine the key spreaders in complex networks. The existing algorithms based on gravity model consider the shortest distance between nodes. However, nodes not only influence each other through the shortest path, which will lead the loss of information between nodes. Different from the existing gravity model, the distance considered in this model is not the shortest distance between nodes, but the reciprocal of the number of feasible paths between nodes. Conveniently, the model is called FPLGM (Local Gravity Model Based on Feasible Paths). Ten different networks are utilised to verify the effectiveness of FPLGM. Results show that the FPLGM performs best in comparison with the well-known state-of-the-art methods.

Hongmei Wang, Jingkun Wang, Shuiqing Xu, Chao Cheng, Qiang Liu & Hongtian Chen

ABSTRACT

The operating data of high-speed train electric drive systems contain unknown disturbances and noise, which makes it challenging to identify incipient faults. In order to improve the incipient fault detection capability of the electric drive system, a fault detection algorithm based on dynamic inner independent component analysis is proposed. In this paper, a mathematical proof of the dynamic inner independent component analysis algorithm is first given, and then the method is validated by means of an electric drive system simulation platform. The simulation results show that the dynamic fault detection method proposed in this paper can effectively monitor the operating status of the electric drive system without the need to establish a mathematical model of the system and expertise. Compared with the fault detection methods based on independent component analysis and principal component analysis, the proposed method decreases the fault detection time and reduces the false alarm rate and missing alarm rate.

Jyoti Kumari & Prabhat Kumar

ABSTRACT

Localisation is an important task and is complex in 3D WSNs in comparison to 2D. The presence of obstacles or irregular terrain makes the localisation task more challenging due to the lack of network connectivity. Few approaches proposed have considered irregular topology but for limited structures like C, H, valley, mountainous areas, etc. This paper investigates the localisation error of sensor nodes deployed in four different 3D real terrains. The network area is divided into grids and a mobile anchor node broadcasts a signal from each grid. This network division provides sufficient anchor signal to each sensor node and found that more than 95% of sensor nodes have been localised with an average localisation error of 19 m. The use of a mobile anchor node eliminates the requirement for many fixed-grounded anchor nodes. The results obtained demonstrate that the localisation error is dependent on terrain topography, grid size and UAV height.

Jun Ye, Shigui Du & Rui Yong

ABSTRACT

A Z-number (ZN) presented by Zadeh is a new framework of fuzzy sets that combines a restriction value with a reliability measure. Based on this motivation of the concept of ZN, this study first proposes a cubic Z-number (CZN) set and operational relations of CZNs, and then defines two expected functions of CZNs to rank CZNs. Next, we present a CZN hybrid weighted arithmetic and geometric averaging (CZNHWAGA) operator and its properties. Then, a multicriteria DM model with unknown criterion weights is established based on the proposed CZNHWAGA operator, the expected functions, and the standard deviation of the expected values in the setting of CZNs. Lastly, the established DM model is applied to the selection of solar cells to illustrate its practicability and effectiveness in the setting of CZNs. However, the established DM model can solve the problem of unknown criterion weights and strengthen the DM reliability and flexibility.

Umesh Kumar Yadav, Praveen Mande & V. P. Singh

ABSTRACT

In this proposal, systematic learning-based approximation of higher-order (HO) system is performed utilising rank-exponent (RE) assisted weight determination method incorporating greywolf-optimisation (GWO) algorithm. The time-moments (TMs) along with Markov-parameters (MPs) of HO system and desired approximant are ascertained in order to utilise in the approximation process. The errors between TMs as well as MPs of HO system and desired approximant are used to frame weighted objective-function. The weights associated with objectivefunction are derived systematically using RE method. Once, weights are derived using RE method, GWO algorithm is used for minimising the resultant objective-function. The sixthorder system of hydro-power-station is utilised as real-test scenario in this study to demonstrate efficacy and effectiveness of proposed RE-based methodology. The considered sixthorder fixed-coefficient HO system is approximated to reduced-order-model of order three. For better examination and analysis of proposed methodology, responses along with quantitative analysis in tabular form for time-domain-specifications and performance-error-indices are presented.

L. Faramondi, G. Oliva, R. Setola & S. Bozóki

ABSTRACT

Relative pairwise comparisons represent the cornerstone for several decision-making methods. Such approaches aim to support complex decision-making situations with multiple alternatives and are essential in order to provide an overall absolute evaluation of the alternatives despite the presence of experts and/or decision-makers with conflicting opinions. Moreover, when decisionmaker’s opinions are affected by uncertainty, there is the need to analyse the effect of such uncertain measures on the result of the decision-making process. We propose an approach based on a multi-objective optimisation problem, able to identify the presence of rank reversal issues in order to evaluate the stability of the final outcome of the decision-making process and a metric able to support experts in evaluating the effects of their uncertainty. We characterise the robustness of the ranking with respect to rank reversal by identifying a perturbation that is as small as possible, while causing the maximum number of ordinal swaps.

Firas H. Almukhtar

ABSTRACT

Lung cancer has been a leading cause of cancer-related mortality in recent years, and early detection can increase patients’ chances of recovery. Machine learning and image processing may be used to analyze Computed Tomography (CT) scans for signs of lung cancer; by integrating several machine learning models, the accuracy of lung cancer diagnoses can be increased. In this paper, we propose a method that introduces a segmentation algorithm based on Social Spider Optimization (SSO) to detect suspicious regions in the CT image. The proposed method uses a combination of Error Correcting Output Codes (ECOC) and Support Vector Machine (SVM) to classify suspicious regions and diagnose lung cancer. The efficiency has been evaluated and compared with previous works. The results show that the proposed method can diagnose lung cancer with an average accuracy of 96.67% and can be used as an efficient tool for assisting specialists in diagnosing lung cancer.

Qiang Yu & Na Wei

ABSTRACT

This paper proposes a new concept of binary F-dependent average dwell time, which describes different types of switching signals by the different grouping function BF for switched systems. Then, combing with the improved multiple Lyapunov function approach, the issues of stability and stabilisation for switched linear systems under the proposed strategy are investigated for the first time, which unify the classical average dwell time (ADT), mode dependent ADT, edge dependent ADT, and Φ dependent ADT, and are more flexible and practical than other existing criteria. Finally, a numerical example is given to illustrate the effectiveness of the obtained results.

Lamia Ouhib & Redouane Kara

ABSTRACT

This paper deals with the observer design for a class of Interconnected Takagi–Sugeno (TS) systems with Immeasurable Premise Variables (IPV). We first investigate the D-stability of Luenberger-like interconnected multiple observers. However, the resulting constraints can be somewhat conservative due to the use of a common Lyapunov matrix. Then, the so-called Finsler’s lemma is used to relax the D-stability conditions through the introduction of additional slack variables providing more flexibility and extra degrees of freedom. The designed conditions are expressed as Linear Matrix Inequalities (LMIs). The proposed approaches are applied in simulation to a Proton Exchange Membrane Fuel Cell (PEMFC) system and a four-tank system.

Zynab Masomi, Mahdi Yaghoobi & Hamid R. Kobravi

ABSTRACT

Chaos is an unpredictable phenomenon that has received attention in nonlinear dynamic systems. Empirical investigations of the gear’s dynamic response demonstrate the existence of chaos and bifurcation in this system. Chaotic behaviour is an unfavourable phenomenon in the vibrations of gear systems. Thus, designing a smooth and optimal gear system, controlling or eliminating this chaotic behaviour is of great importance. Therefore, this paper presents an improved fuzzy control using the extended grey wolf optimiser to control the chaotic behaviour of a gear transmission system. To evaluate this method, the results are studied in the presence and absence of white noise. Finally, the proposed method is compared with adaptive sliding mode control, indicating the superiority of the proposed method in minimising the square error and increasing the speed of eliminating chaotic behaviour.

Chun Wei, Haiyan Shi, Baoliang Liu, Zhiqiang Zhang & Yanqing Wen

ABSTRACT

A dependent competitive failure model of Caputo uncertain fractional differential equation (UFDE) degradation with uncertain threshold is proposed. There are two main reasons for the failure of an equipment or system, long-term natural wear and the impact of external loads. Each shock will cause a sharp increase in wear. In the absence of fault data, the natural wear process is driven by a Caputo type of UFDE, and the external load is an uncertain renewal reward process. Three different shock models are considered and calculated the belief reliability of device according to uncertainty theory, taking the jet pipe servo control valve as an example, the proposed model is simulated, and the results show that the proposed model is effective.