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A fundamental aspect of society is the exchange and discussion of opinions between individuals, occurring in situations as varied as company boardrooms, elementary school classrooms and online social media. After a very brief introduction to the established results of the most fundamental opinion dynamics models, which seek to mathematically capture observed social phenomena, a brief discussion follows on several recent themes pursued by the authors building on the fundamental ideas. In the first theme, we study the way an individual′s self-confidence can develop through contributing to discussions on a sequence of topics, reaching a consensus in each case, where the consensus value to some degree reflects the contribution of that individual to the conclusion. During this process, the individuals in the network and the way they interact can change. The second theme introduces a novel discrete-time model of opinion dynamics to study how discrepancies between an individual′s expressed and private opinions can arise due to stubbornness and a pressure to conform to a social norm. It is also shown that a few extremists can create " pluralistic ignorance”, where people believe there is majority support for a position but in fact the position is privately rejected by the majority. Last, we consider a group of individuals discussing a collection of logically related topics. In particular, we identify that for topics whose logical interdependencies take on a cascade structure, disagreement in opinions can occur if individuals have competing and/or heterogeneous views on how the topics are related, i.e., the logical interdependence structure varies between individuals.
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This paper investigates the necessity of feasibility considerations in a fault tolerant control system using the constrained control allocation methodology where both static and dynamic actuator constraints are considered. In the proposed feasible control allocation scheme, the constrained model predictive control (MPC) is employed as the main controller. This considers the admissible region of the control allocation problem as its constraints. Using the feasibility notion in the control allocation problem provides the main controller with information regarding the actuator′s status, which leads to closed loop system performance improvement. Several simulation examples under normal and faulty conditions are employed to illustrate the effectiveness of the proposed methodology. The main results clearly indicate that closed loop performance and stability characteristics can be significantly degraded by neglecting the actuator constraints in the main controller. Also, it is shown that the proposed strategy substantially enlarges the domain of attraction of the MPC combined with the control allocation as compared to the conventional MPC.
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The choice of fulcrums for control of socio-economic systems represented by directed weighted signed graphs is a topic of current interest. This article proposes a new method for identifying nodes of impact and influential nodes, which will provide a guaranteed positive system response over the growth model. The task is posed as an optimization problem to maximize the ratio of the norms of the accumulated increments of the growth vector and the exogenous impact vector. The algorithm is reduced to solving a quadratic programming problem with nonlinear restrictions. The selection of the most effective vertices is based on the cumulative gains of the component projections onto the solution vector. Numerical examples are provided to illustrate the effectiveness of the proposed method.
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The growth of environmental energy harvesting has been explosive in wireless computing systems especially when replacing or recharging batteries manually is impracticable. This work investigates the scheduling of periodic weekly hard real-time tasks under energy constraints. Based on this motivation, we proposed a real-time scheduling algorithm, namely energy guarantee dynamic voltage and frequency scaling (EG-DVFS), that utilizes the earliest deadline-harvesting (ED-H) scheduling algorithm combined with dynamic voltage and frequency scaling. This one is qualified as real-time since tasks must satisfy their timing constraints. We assume that the preemptable tasks receive dynamic priorities according to the earliest deadline first (EDF) rule. EG-DVFS adjusts the processor′s behavior by characterizing the properties of the energy source module, capacity of the stored energy as well as the harvested energy in a future duration. Specifically, tasks are executed at full processor speed if the amount of energy in the battery is enough to finish its execution. Otherwise, the processor slows down task execution to the lowest possible processor speed while still guaranteeing to meet all the timing constraints. EG-DVFS mainly depends on the on-line computation of the slack time and the slack energy with dynamic voltage and frequency selection in order to achieve an improved system performance. Experimental results show that EG-DVFS can achieve capacity savings up of up to 33% when compared to ED-H.
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In this paper, we report on the identification and modeling of unknown and higher order processes into first order plus dead time (FOPDT) plants based on the limit cycle information obtained from a single relay feedback test with an online fractional order proportional integral (FOPI) controller. The parameters of the test processes are accurately determined by the state space method while the FOPI controller settings are re-tuned to achieve enhanced performance based on the identified model parameters based on the balanced-tuning method. A new performance index, integral time fractional order absolute error (ITFIAE) is introduced in this paper for balanced tuning of fractional order (FO) controllers. It requires minimum design specifications without a-priori knowledge of gain and phase crossover frequencies and is done non-iteratively without disrupting the closed loop. Four test processes and experimental analysis on a coupled tank system (CTS) validate the theory proposed.
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As condition monitoring of systems continues to grow in both complexity and application, an overabundance of data is amassed. Computational capabilities are unable to keep abreast of the subsequent processing requirements. Thus, a means of establishing computable prognostic models to accurately reflect process condition, whilst alleviating computational burdens, is essential. This is achievable by restricting the amount of information input that is redundant to modelling algorithms. In this paper, a variable clustering approach is investigated to reorganise the harmonics of common diagnostic features in rotating machinery into a smaller number of heterogeneous groups that reflect conditions of the machine with minimal information redundancy. Naïve Bayes classifiers established using a reduced number of highly sensitive input parameters realised superior classification powers over higher dimensional classifiers, demonstrating the effectiveness of the proposed approach. Furthermore, generic parameter capabilities were evidenced through confirmatory factor analysis. Parameters with superior deterministic power were identified alongside complimentary, uncorrelated, variables. Particularly, variables with little explanatory capacity could be eliminated and lead to further variable reductions. Their information sustainability is also evaluated with Naïve Bayes classifiers, showing that successive classification rates are sufficiently high when the first few harmonics are used. Further gains were illustrated on compression of chosen envelope harmonic features. A Naïve Bayes classification model incorporating just two compressed input variables realised an 83.3% success rate, both an increase in classification rate and an immense improvement volume-wise on the former ten parameter model.
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Research has demonstrated a significant overlap between sleep issues and other medical conditions. In this paper, we consider mild difficulty in falling asleep (MDFA). Recognition of MDFA has the potential to assist in the provision of appropriate treatment plans for both sleep issues and related medical conditions. An issue in the diagnosis of MDFA lies in subjectivity. To address this issue, a decision support tool based on dual-modal physiological feature fusion which is able to automatically identify MDFA is proposed in this study. Special attention is given to the problem of how to extract candidate features and fuse dual-modal features. Following the identification of the optimal feature set, this study considers the correlations between each feature and class and evaluates correlations between the inter-modality features. Finally, the recognition accuracy was measured using 10-fold cross validation. The experimental results for our method demonstrate improved performance. The highest recognition rate of MDFA using the optimal feature set can reach 96.22%. Based on the results of current study, the authors will, in projected future research, develop a real-time MDFA recognition system.
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This paper describes the development and modeling of a remotely operated scaled multi-wheeled combat vehicle (ROMWCV) using system identification methodology for heading angle tracking. The vehicle was developed at the vehicle dynamics and crash research (VDCR) Lab at the University of Ontario Institute of Technology (UOIT) to analyze the characteristics of the full-size model. For such vehicles, the development of controllers is considered the most crucial issue. In this paper, the ROMWCV is developed first. An experimental test was carried out to record and analyze the vehicle input/output signals in open loop system, which is considered a multi-input-single-output (MISO) system. Subsequently, a fuzzy logic controller (FLC) was developed for heading angle tracking. The experiments showed that it was feasible to represent the dynamic characteristics of the vehicle using the system identification technique. The estimation and validation results demonstrated that the obtained identified model was able to explain 88.44% of the output variation. In addition, the developed FLC showed a good heading angle tracking.
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Image registration is an indispensable component in multi-source remote sensing image processing. In this paper, we put forward a remote sensing image registration method by including an improved multi-scale and multi-direction Harris algorithm and a novel compound feature. Multi-scale circle Gaussian Combined invariant moments and multi-direction gray level co-occurrence matrix are extracted as features for image matching. The proposed algorithm is evaluated on numerous multi-source remote sensor images with noise and illumination changes. Extensive experimental studies prove that our proposed method is capable of receiving stable and even distribution of key points as well as obtaining robust and accurate correspondence matches. It is a promising scheme in multi-source remote sensing image registration.
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The aim of this work is to model and analyze the behavior of a new smart nano force sensor. To do so, the carbon nanotube has been used as a suspended gate of a metal-oxide-semiconductor field-effect transistor (MOSFET). The variation of the applied force on the carbon nanotube (CNT) generates a variation of the capacity of the transistor oxide-gate and therefore the variation of the threshold voltage, which allows the MOSFET to become a capacitive nano force sensor. The sensitivity of the nano force sensor can reach 0.124 31 V/nN. This sensitivity is greater than results in the literature. We have found through this study that the response of the sensor depends strongly on the geometric and physical parameters of the CNT. From the results obtained in this study, the increase in the applied force has as a consequence an increase in the value of the threshold voltage VTh of the MOSFET. In this paper, we first used artificial neural networks to faithfully reproduce the response of the nano force sensor model. This neural model is called direct model. Then, secondly, we designed an inverse model called an intelligent sensor which allows linearization of the response of our developed force sensor.
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The objective of this paper is to propose a reduced-order observer for a class of Lipschitz nonlinear discrete-time systems. The conditions that guarantee the existence of this observer are presented in the form of linear matrix inequalities (LMIs). To handle the Lipschitz nonlinearities, the Lipschitz condition and the Young′s relation are adequately operated to add more degrees of freedom to the proposed LMI. Necessary and sufficient conditions for the existence of the unbiased reduced-order observer are given. An extension to \begin{document}$\mathcal{H}_\infty$\end{document} performance analysis is considered in order to deal with \begin{document}$\mathcal{H}_\infty$\end{document} asymptotic stability of the estimation error in the presence of disturbances that affect the state of the system. To highlight the effectiveness of the proposed design methodology, three numerical examples are considered. Then, high performances are shown through real time implementation using the ARDUINO MEGA 2560 device.
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2019,  vol. 16,  no. 2,   pp. 213-225 ,  doi: 10.1007/s11633-017-1062-2
Abstract:
This work deals with robust inverse neural control strategy for a class of single-input single-output (SISO) discrete-time nonlinear system afiected by parametric uncertainties. According to the control scheme, in the flrst step, a direct neural model (DNM) is used to learn the behavior of the system, then, an inverse neural model (INM) is synthesized using a specialized learning technique and cascaded to the uncertain system as a controller. In previous works, the neural models are trained classically by backpropagation (BP) algorithm. In this work, the sliding mode-backpropagation (SM-BP) algorithm, presenting some important properties such as robustness and speedy learning, is investigated. Moreover, four combinations using classical BP and SM-BP are tested to determine the best conflguration for the robust control of uncertain nonlinear systems. Two simulation examples are treated to illustrate the efiectiveness of the proposed control strategy.
2019,  vol. 16,  no. 2,   pp. 226-237 ,  doi: 10.1007/s11633-016-1017-z
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In a conventional direct torque control (CDTC) of the induction motor drive, the electromagnetic torque and the stator flux are characterized by high ripples. In order to reduce the undesired ripples, several methods are used in the literature. Nevertheless, these methods increase the algorithm complexity and dependency on the machine parameters such as the space vector modulation (SVM). The fuzzy logic control method is utilized in this work to decrease these ripples. Moreover, to eliminate the mechanical sensor the extended kalman filter (EKF) is used, in order to reduce the cost of the system and the rate of maintenance. Furthermore, in the domain of controlling the real-time induction motor drives, two principal digital devices are used such as the hardware (FPGA) and the digital signal processing (DSP). The latter is a software solution featured by a sequential processing that increases the execution time. However, the FPGA is featured by a high processing speed because of its parallel processing. Therefore, using the FPGA it is possible to implement complex algorithms with low execution time and to enhance the control bandwidth. The large bandwidth is the key issue to increase the system performances. This paper presents the interest of utilizing the FPGAs to implement complex control algorithms of electrical systems in real time. The suggested sensorless direct torque control using the fuzzy logic (DTFC) of an induction motor is successfully designed and implemented on an FPGA Virtex 5 using xilinx system generator. The simulation and implementation results show proposed approach's performances in terms of ripples, stator current harmonic waves, execution time, and short design time.
2019,  vol. 16,  no. 2,   pp. 238-247 ,  doi: 10.1007/s11633-016-1020-4
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A new method is presented to study the function projective lag synchronization (FPLS) of chaotic systems via adaptive-impulsive control. To achieve synchronization, suitable nonlinear adaptive-impulsive controllers are designed. Based on the Lyapunov stability theory and the impulsive control technology, some effective sufficient conditions are derived to ensure the drive system and the response system can be rapidly lag synchronized up to the given scaling function matrix. Numerical simulations are presented to verify the effectiveness and the feasibility of the analytical results.
2010,  vol. 7,  no. 3,   pp. 324-329, doi: 10.1007/s11633-010-0510-z
2011,  vol. 8,  no. 3,   pp. 326-332, doi: 10.1007/s11633-011-0588-y
2015,  vol. 12,  no. 3,   pp. 229-242, doi: 10.1007/s11633-015-0893-y
2011,  vol. 8,  no. 2,   pp. 215-220, doi: 10.1007/s11633-011-0576-2
2013,  vol. 10,  no. 4,   pp. 281-287, doi: 10.1007/s11633-013-0722-0
2012,  vol. 9,  no. 3,   pp. 237-247, doi: 10.1007/s11633-012-0640-6
2012,  vol. 9,  no. 4,   pp. 358-368, doi: 10.1007/s11633-012-0656-y
2012,  vol. 9,  no. 3,   pp. 331-336, doi: 10.1007/s11633-012-0652-2
2011,  vol. 8,  no. 2,   pp. 147-153, doi: 10.1007/s11633-011-0567-3
2011,  vol. 8,  no. 2,   pp. 244-253, doi: 10.1007/s11633-011-0579-z
2015,  vol. 12,  no. 2,   pp. 134-141, doi: 10.1007/s11633-015-0880-3
2014,  vol. 11,  no. 3,   pp. 299-307, doi: 10.1007/s11633-014-0792-7
2013,  vol. 10,  no. 3,   pp. 181-193, doi: 10.1007/s11633-013-0711-3
2011,  vol. 8,  no. 3,   pp. 280-285, doi: 10.1007/s11633-011-0583-3
2011,  vol. 8,  no. 2,   pp. 262-268, doi: 10.1007/s11633-011-0581-5
2011,  vol. 8,  no. 3,   pp. 348-356, doi: 10.1007/s11633-011-0591-3
2012,  vol. 9,  no. 5,   pp. 555-560, doi: 10.1007/s11633-012-0679-4
2013,  vol. 10,  no. 4,   pp. 288-295, doi: 10.1007/s11633-013-0723-z
2012,  vol. 9,  no. 5,   pp. 487-491, doi: 10.1007/s11633-012-0671-z
2013,  vol. 10,  no. 1,   pp. 85-90 , doi: 10.1007/s11633-013-0700-6
Current Issue

2019 Vol.16 No.2

Table of Contents

ISSN 1476-8186

E-ISSN 1751-8520

CN 11-5350/TP

Editors-in-chief
Tieniu TAN, Chinese Academy of Sciences Guoping LIU, University of South Wales Huosheng HU, University of Essex
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