Search results for: complex adaptive system (CAS)

Authors: Pornthep Rachnavy

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The purpose of this paper is twofold. First, we believe that there are a significant relationship between sculling angle and sculling style among adaptive rowing. Second, we introduce a methodology used for adaptive rowing, namely simulation, to identify effectiveness of adaptive rowing. For our study we simulate the arms only single scull of adaptive rowing. The method for rowing fastest under the 1000 meter was investigated by study sculling angle using the simulation modeling. A simulation model of a rowing system was developed using the Matlab software package base on equations of motion consist of many variation for moving the boat such as oars length, blade velocity and sculling style. The boat speed, power and energy consumption on the system were compute. This simulation modeling can predict the force acting on the boat. The optimum sculling angle was performing by computer simulation for compute the solution. Input to the model are sculling style of each rower and sculling angle. Outputs of the model are boat velocity at 1000 meter. The present study suggests that the optimum sculling angle exist depends on sculling styles. The optimum angle for blade entry and release with respect to the perpendicular through the pin of the first style is -57.00 and 22.0 degree. The optimum angle for blade entry and release with respect to the perpendicular through the pin of the second style is -57.00 and 22.0 degree. The optimum angle for blade entry and release with respect to the perpendicular through the pin of the third style is -51.57 and 28.65 degree. The optimum angle for blade entry and release with respect to the perpendicular through the pin of the fourth style is -45.84 and 34.38 degree. A theoretical simulation for rowing has been developed and presented. The results suggest that it may be advantageous for the rowers to select the sculling angles proper to sculling styles. The optimum sculling angles of the rower depends on the sculling styles made by each rower. The investigated of this paper can be concludes in three directions: 1;. There is the optimum sculling angle in arms only single scull of adaptive rowing. 2. The optimum sculling angles depend on the sculling styles. 3. Computer simulation of rowing can identify opportunities for improving rowing performance by utilizing the kinematic description of rowing. The freedom to explore alternatives in speed, thrust and timing with the computer simulation will provide the coach with a tool for systematic assessments of rowing technique In addition, the ability to use the computer to examine the very complex movements during rowing will help both the rower and the coach to conceptualize the components of movements that may have been previously unclear or even undefined.

Keywords: simulation, sculling, adaptive, rowing

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Authors: Herlandson C. Moura, Jorge H. Bidinotto, Eduardo M. Belo

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The present work proposes the development of an adaptive control system which enables the suppression of Pilot Induced Oscillations (PIO) in Digital Fly-By-Wire (DFBW) aircrafts. The proposed system consists of a Modified Model Reference Adaptive Control (M-MRAC) integrated with the Gain Scheduling technique. The PIO oscillations are detected using a Real Time Oscillation Verifier (ROVER) algorithm, which then enables the system to switch between two reference models; one in PIO condition, with low proneness to the phenomenon and another one in normal condition, with high (or medium) proneness. The reference models are defined in a closed loop condition using the Linear Quadratic Regulator (LQR) control methodology for Multiple-Input-Multiple-Output (MIMO) systems. The implemented algorithms are simulated in software implementations with state space models and commercial flight simulators as the controlled elements and with pilot dynamics models. A sequence of pitch angles is considered as the reference signal, named as Synthetic Task (Syntask), which must be tracked by the pilot models. The initial outcomes show that the proposed system can detect and suppress (or mitigate) the PIO oscillations in real time before it reaches high amplitudes.

Keywords: adaptive control, digital Fly-By-Wire, oscillations suppression, PIO

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Authors: Hernández Yasmín, Ochoa Alberto, Hurtado Diego

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The aim of this study is developing an intelligent tutoring system for electrical operators training with virtual reality systems at the laboratory center of partials discharges LAPEM. The electrical domain requires efficient and well trained personnel, due to the danger involved in the partials discharges field, qualified electricians are required. This paper presents an overview of the intelligent tutor adaptive learning design and user interface with VR. We propose the develop of constructing a model domain of a subset of partial discharges enables adaptive training through a trainee model which represents the affective and knowledge states of trainees. According to the success of the intelligent tutor system with VR, it is also hypothesized that the trainees will able to learn the electrical domain installations of partial discharges and gain knowledge more efficient and well trained than trainees using traditional methods of teaching without running any risk of being in danger, traditional methods makes training lengthily, costly and dangerously.

Keywords: intelligent tutoring system, artificial intelligence, virtual reality, partials discharges, adaptive learning

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Authors: Daehyoung Kim, Pervez Khan, Hoon Kim

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Efficient utilization of spectrum resources is a fundamental issue of wireless communications due to its scarcity. To improve the efficiency of spectrum utilization, the spectrum sharing for unlicensed bands is being regarded as one of key technologies in the next generation wireless networks. A number of schemes such as Listen-Before-Talk(LBT) and carrier sensor adaptive transmission (CSAT) have been suggested from this aspect, but more efficient sharing schemes are required for improving spectrum utilization efficiency. This work considers an opportunistic transmission approach and a dynamic Contention Window (CW) adjustment scheme for LTE-U users sharing the unlicensed spectrum with Wi-Fi, in order to enhance the overall system throughput. The decision criteria for the dynamic adjustment of CW are based on the collision evaluation, derived from the collision probability of the system. The overall performance can be improved due to the adaptive adjustment of the CW. Simulation results show that our proposed scheme outperforms the Distributed Coordination Function (DCF) mechanism of IEEE 802.11 MAC.

Keywords: spectrum sharing, adaptive opportunistic transmission, unlicensed bands, heterogeneous networks

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Authors: Isabelle Snyder

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Microgrid protection presents challenges to conventional protection techniques due to the low induced fault current. Protection relays present in microgrid applications require a combination of settings groups to adjust based on the architecture of the microgrid in islanded and grid-connected mode. In a radial system where the microgrid is at the other end of the feeder, directional elements can be used to identify the direction of the fault current and switch settings groups accordingly (grid connected or microgrid connected). However, with multiple microgrid connections, this concept becomes more challenging, and the direction of the current alone is not sufficient to identify the source of the fault current contribution. ORNL has previously developed adaptive relaying schemes through other DOE-funded research projects that will be evaluated and used as a baseline for this research. The four protection techniques in this study are the following: (1) Adaptive Current only Protection System (ACPS), Intentional (2) Unbalanced Control for Protection Control (IUCPC), (3) Adaptive Protection System with Communication Controller (APSCC) (4) Adaptive Model-Driven Protective Relay (AMDPR). The first two methods focus on identifying the islanded mode without communication by monitoring the current sequence component generated by the system (ACPS) or induced with inverter control during islanded mode (IUCPC) to identify the islanding condition without communication at the relay to adjust the settings. These two methods are used as a backup to the APSCC, which relies on a communication network to communicate the islanded configuration to the system components. The fourth method relies on a short circuit model inside the relay that is used in conjunction with communication to adjust the system configuration and computes the fault current and adjusts the settings accordingly.

Keywords: adaptive relaying, microgrid protection, sequence components, islanding detection, communication controlled protection, integrated short circuit model

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Authors: Jin-Siang Shaw, Patricia Moya Caceres, Sheng-Xiang Xu

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This paper aims to integrate the particle swarm optimization (PSO) method with the adaptive fuzzy sliding mode controller (AFSMC) to achieve vibration attenuation in a piezoelectric actuator subject to base excitation. The piezoelectric actuator is a complicated system made of ferroelectric materials and its performance can be affected by nonlinear hysteresis loop and unknown system parameters and external disturbances. In this study, an adaptive fuzzy sliding mode controller is proposed for the vibration control of the system, because the fuzzy sliding mode controller is designed to tackle the unknown parameters and external disturbance of the system, and the adaptive algorithm is aimed for fine-tuning this controller for error converging purpose. Particle swarm optimization method is used in order to find the optimal controller parameters for the piezoelectric actuator. PSO starts with a population of random possible solutions, called particles. The particles move through the search space with dynamically adjusted speed and direction that change according to their historical behavior, allowing the values of the particles to quickly converge towards the best solutions for the proposed problem. In this paper, an initial set of controller parameters is applied to the piezoelectric actuator which is subject to resonant base excitation with large amplitude vibration. The resulting vibration suppression is about 50%. Then PSO is applied to search for an optimal controller in the neighborhood of this initial controller. The performance of the optimal fuzzy sliding mode controller found by PSO indeed improves up to 97.8% vibration attenuation. Finally, adaptive version of fuzzy sliding mode controller is adopted for further improving vibration suppression. Simulation result verifies the performance of the adaptive controller with 99.98% vibration reduction. Namely the vibration of the piezoelectric actuator subject to resonant base excitation can be completely annihilated using this PSO based adaptive fuzzy sliding mode controller.

Keywords: adaptive fuzzy sliding mode controller, particle swarm optimization, piezoelectric actuator, vibration suppression

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Authors: Hussein Shaman

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This study introduces an innovative design for an RF phase shifter that can maintain a consistent phase shift across a broad spectrum of frequencies. The proposed design integrates an adaptive control system into a reflective-type phase shifter, typically showing frequency-related variations. Adjusting the DC voltage according to the frequency ensures a more reliable phase shift across the frequency span of operation. In contrast, conventional frequency-dependent reflective-type phase shifters may exhibit significant fluctuations in phase shifts exceeding 60 degrees in the same bandwidth. The proposed phase shifter is configured to deliver a 90-degree operation with an expected deviation of around 15 degrees. The fabrication of the phase shifter and adaptive control circuit has been verified through experimentation, with the measured outcomes aligning with the simulation results.

Keywords: phase shifter, adaptive control, varactors, electronic circuits.

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Authors: Golnaz Salehi Mourkani

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Two conception of Integrity and authenticity, in texts have just applied respectively for adaptive reuse and conservation, which in comparison with word “Integrity” in texts related to adaptive reuse is much more seen than Authenticity, which is often applied with conservation. According to Stove, H. (2007) in some cases, this conception have used with this form “integrity/authenticity” in texts, that cause to infer one conception of both. In this article, with referring to definitions and comparison of aspects specialized to both concept of “Authenticity and Integrity” through literature review, it was attempted to examine common and distinctive aspects of each one, then with this method we can reach their differences in adaptive reuse.

Keywords: adaptive reuse, integrity, authenticity, conservation

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Authors: Aprilia, Wei Liang Keith Nguyen, Shu Beng Tor, Gerald Gim Lee Seet, Chee Kai Chua

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Automated remanufacturing process is of great interest in today’s marine and offshore industry. Most of the current remanufacturing processes are carried out manually and hence they are error prone, labour-intensive and costly. In this paper, a conceptual framework for automated remanufacturing is presented. This framework involves the integration of 3D non-contact digitization, adaptive surface reconstruction, additive manufacturing and machining operation. Each operation is operated and interconnected automatically as one system. The feasibility of adaptive surface reconstruction on marine and offshore engineering components is also discussed. Several engineering components were evaluated and the results showed that this proposed system is feasible. Conclusions are drawn and further research work is discussed.

Keywords: adaptive surface reconstruction, automated remanufacturing, automatic repair, reverse engineering

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Authors: Imil Hamda Imran, Sami El Ferik

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This paper deals with adaptive cooperative control of non holonomic mobile robot moved together in a given formation. The controller is designed based on the Immersion and Invariance (I&I) approach. I&I is a framework for adaptive stabilization of nonlinear systems with uncertain parameters. We investigate the tracking control of non holonomic mobile robot with uncertainties in The I&I-based adaptive controller regulates the angular and linear velocity of non holonomic mobile robot. The results demonstrate that the ability of I&I-based adaptive cooperative control in tracking the position of non holonomic mobile robot.

Keywords: nonholonomic mobile robot, immersion and invariance, adaptive control, uncertain nonlinear systems

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Authors: Oya Bulut, Oguzhan Avci, Zafer Bulut, Atilla Simsek

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Livestock breeders have focused on the improvement of production traits with little or no attention for improvement of disease resistance traits. In order to determine the association between the genetic structure of the individual gene loci with possibility of the occurrence and the development of diseases, MHC (major histocompatibility complex) are frequently used. Because of their importance in the immune system, MHC locus is considered as candidate genes for resistance/susceptibility against to different diseases. Major histocompatibility complex (MHC) molecules play a critical role in both innate and adaptive immunity and have been considered candidate molecular markers of an association between polymorphisms and resistance/susceptibility to diseases. The purpose of this study is to give some information about MHC genes become an important area of study in recent years in terms of animal husbandry and determine the relation between MHC genes and resistance/susceptibility to disease.

Keywords: MHC, polymorphism, disease, resistance

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Authors: Magdi. M. Nabi, Ding-Li Yu

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Control of a semi-batch polymerization reactor using an adaptive radial basis function (RBF) neural network method is investigated in this paper. A neural network inverse model is used to estimate the valve position of the reactor; this method can identify the controlled system with the RBF neural network identifier. The weights of the adaptive PID controller are timely adjusted based on the identification of the plant and self-learning capability of RBFNN. A PID controller is used in the feedback control to regulate the actual temperature by compensating the neural network inverse model output. Simulation results show that the proposed control has strong adaptability, robustness and satisfactory control performance and the nonlinear system is achieved.

Keywords: Chylla-Haase polymerization reactor, RBF neural networks, feed-forward, feedback control

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Authors: Halim Djerroud, Arab Ali Cherif

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We assume that conscious functions are implemented automatically. In other words that consciousness as well as the non-consciousness aspect of human thought, planning, and perception, are produced by biologically adaptive algorithms. We propose that the mechanisms of consciousness can be produced using similar adaptive algorithms to those executed by the mechanism. In this paper, we propose a computational model of consciousness, the ”Global Abstraction Workspace” which is an internal environmental modelling perceived as a multi-agent system. This system is able to evolve and generate new data and processes as well as actions in the environment.

Keywords: artificial consciousness, cognitive architecture, global abstraction workspace, multi-agent system

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Authors: Massra M. Sabeima, Myriam lamolle, Mohamedade Farouk Nanne

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Adapting the learning resources of an e-learning system to the characteristics of the learners is an important aspect to consider when designing an adaptive e-learning system. However, this adaptation is not a simple process; it requires the extraction, analysis, and modeling of user information. This implies a good representation of the user's profile, which is the backbone of the adaptation process. Moreover, during the e-learning process, collaboration with similar users (same geographic province or knowledge context) is important. Productive collaboration motivates users to continue or not abandon the course and increases the assimilation of learning objects. The contribution of this work is the following: we propose an adaptive e-learning semantic platform to recommend learning resources to learners, using ontology to model the user profile and the course content, furthermore an implementation of a multi-agent system able to progressively generate the learning graph (taking into account the user's progress, and the changes that occur) for each user during the learning process, and to synchronize the users who collaborate on a learning object.

Keywords: adaptative learning, collaboration, multi-agent, ontology

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Authors: B. T. Chew, S. N. Kazi, A. Amiri

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This paper presents an adaptive thermal comfort model study in the tropical country of Malaysia. A number of researchers have been interested in applying the adaptive thermal comfort model to different climates throughout the world, but so far no study has been performed in Malaysia. For the use as a thermal comfort model, which better applies to hot and humid climates, the adaptive thermal comfort model was developed as part of this research by using the collected results from a large field study in six lecture halls with 178 students. The relationship between the operative temperature and behavioral adaptations was determined. In the developed adaptive model, the acceptable indoor neutral temperatures lay within the range of 23.9-26.0 oC, with outdoor temperatures ranging between 27.0–34.6oC. The most comfortable temperature for students in the lecture hall was 25.7 oC.

Keywords: hot and humid, lecture halls, neutral temperature, adaptive thermal comfort model

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Authors: Rajat Raj, Rohini S. Hallikar

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The ever-increasing integration of renewable energy sources in the power grid necessitates the development of efficient and reliable microgrid systems. Photovoltaic (PV) systems coupled with energy storage technologies, such as batteries, offer promising solutions for sustainable and resilient power generation. This paper proposes an adaptive power control topology for a PV-battery microgrid system, aiming to optimize the utilization of available solar energy and enhance the overall system performance. In order to provide a smooth transition between the OFF-GRID and ON-GRID modes of operation with proportionate power sharing, a self-adaptive control method for a microgrid is proposed. Three different modes of operation are discussed in this paper, i.e., GRID connected, the transition between Grid-connected and Islanded State, and changing the irradiance of PVs and doing the transitioning. The simulation results show total harmonic distortion to be 0.08, 1.43 and 2.17 for distribution generation-1 and 4.22,3.92 and 2.10 for distribution generation-2 in the three modes, respectively which helps to maintain good power quality. The simulation results demonstrate the superiority of the adaptive power control topology in terms of maximizing renewable energy utilization, improving system stability and ensuring a seamless transition between grid-connected and islanded modes.

Keywords: islanded modes, microgrids, photo voltaic, total harmonic distortion

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Authors: Mohammad Shams Esfand Abadi, Mehrdad Zalaghi, Reza ebrahimpour

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In this paper, we propose a sign adaptive filter algorithm with the ability of dynamic selection of subband filters which leads to low computational complexity compared with conventional sign subband adaptive filter (SSAF) algorithm. Dynamic selection criterion is based on largest reduction of the mean square deviation at each adaption. We demonstrate that this simple proposed algorithm has the same performance of the conventional SSAF and somewhat faster than it. In the presence of impulsive interferences robustness of the simple proposed algorithm as well as the conventional SSAF and outperform the conventional normalized subband adaptive filter (NSAF) algorithm. Therefore, it is preferred for environments under impulsive interferences. Simulation results are presented to verify these above considerations very well have been achieved.

Keywords: acoustic echo cancellation (AEC), normalized subband adaptive filter (NSAF), dynamic selection subband adaptive filter (DS-NSAF), sign subband adaptive filter (SSAF), impulsive noise, robust filtering

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Authors: Andrey V. Timofeev

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An adaptive nonparametric method is proposed for stable real-time detection of seismoacoustic sources in multichannel C-OTDR systems with a significant number of channels. This method guarantees given upper boundaries for probabilities of Type I and Type II errors. Properties of the proposed method are rigorously proved. The results of practical applications of the proposed method in a real C-OTDR-system are presented in this report.

Keywords: guaranteed detection, multichannel monitoring systems, change point, interval estimation, adaptive detection

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Authors: Samah Riache, Madjid Kidouche

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In this paper, we propose a nonlinear controller for Aerial Manipulator (AM) consists of a Quadrotor equipped with two degrees of freedom robotic arm. The kinematic and dynamic models were developed by considering the aerial manipulator as a coupled system. The proposed controller was designed using Nonsingular Terminal Sliding Mode Control. The objective of our approach is to improve performances and attenuate the chattering drawback using an adaptive algorithm in the discontinuous control part. Simulation results prove the effectiveness of the proposed control strategy compared with Sliding Mode Controller.

Keywords: adaptive algorithm, quadrotor, robotic arm, sliding mode control

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Authors: Sade Ogundipe

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The private healthcare sector in the United Kingdom has experienced unprecedented challenges during times of crisis, necessitating effective leadership adaptability. This qualitative study delves into the dynamic landscape of leadership within the sector, particularly during crises, employing the lenses of complexity theory and institutional theory to unravel the intricate mechanisms at play. Through in-depth interviews with 25 various levels of leaders in the UK private healthcare sector, this research explores how leaders in UK private healthcare organizations navigate complex and often chaotic environments, shedding light on their adaptive strategies and decision-making processes during crises. Complexity theory is used to analyze the complicated, volatile nature of healthcare crises, emphasizing the need for adaptive leadership in such contexts. Institutional theory, on the other hand, provides insights into how external and internal institutional pressures influence leadership behavior. Findings from this study highlight the multifaceted nature of leadership adaptability, emphasizing the significance of leaders' abilities to embrace uncertainty, engage in sensemaking, and leverage the institutional environment to enact meaningful changes. Furthermore, this research sheds light on the challenges and opportunities that leaders face when adapting to crises within the UK private healthcare sector. The study's insights contribute to the growing body of literature on leadership in healthcare, offering practical implications for leaders, policymakers, and stakeholders within the UK private healthcare sector. By employing the dual perspectives of complexity theory and institutional theory, this research provides a holistic understanding of leadership adaptability in the face of crises, offering valuable guidance for enhancing the resilience and effectiveness of healthcare leadership within this vital sector.

Keywords: leadership, adaptability, decision-making, complexity, complexity theory, institutional theory, organizational complexity, complex adaptive system (CAS), crises, healthcare

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Authors: Michael B. C. Khoo, J. L. Khoo, W. C. Yeong, W. L. Teoh

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The Shewhart Xbar control chart is a useful process monitoring tool in manufacturing industries to detect the presence of assignable causes. However, it is insensitive in detecting small process shifts. To circumvent this problem, adaptive control charts are suggested. An adaptive chart enables at least one of the chart’s parameters to be adjusted to increase the chart’s sensitivity. Two common adaptive charts that exist in the literature are the double sampling (DS) Xbar and variable sampling interval (VSI) Xbar charts. This paper compares the performances of the DS and VSI Xbar charts, based on the average time to signal (ATS) criterion. The ATS profiles of the DS Xbar and VSI Xbar charts are obtained using the Mathematica and Statistical Analysis System (SAS) programs, respectively. The results show that the VSI Xbar chart is generally superior to the DS Xbar chart.

Keywords: adaptive charts, average time to signal, double sampling, charts, variable sampling interval

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Authors: Hamid Sharif, Nazish Saleem Abbas, Muhammad Haris Jamil

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An adaptive filter is a filter that self-adjusts its transfer function according to an optimization algorithm driven by an error signal. Because of the complexity of the optimization algorithms, most adaptive filters are digital filters. Adaptive filtering constitutes one of the core technologies in digital signal processing and finds numerous application areas in science as well as in industry. Adaptive filtering techniques are used in a wide range of applications, including adaptive noise cancellation and echo cancellation. Acoustic echo cancellation is a common occurrence in today’s telecommunication systems. The signal interference caused by acoustic echo is distracting to both users and causes a reduction in the quality of the communication. In this paper, we review different techniques of adaptive filtering to reduce this unwanted echo. In this paper, we see the behavior of techniques and algorithms of adaptive filtering like Least Mean Square (LMS), Normalized Least Mean Square (NLMS), Variable Step-Size Least Mean Square (VSLMS), Variable Step-Size Normalized Least Mean Square (VSNLMS), New Varying Step Size LMS Algorithm (NVSSLMS) and Recursive Least Square (RLS) algorithms to reduce this unwanted echo, to increase communication quality.

Keywords: adaptive acoustic, echo cancellation, LMS algorithm, adaptive filter, normalized least mean square (NLMS), variable step-size least mean square (VSLMS)

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Authors: Abderrahim Siam, Ramdane Maamri, Zaidi Sahnoun

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The development of adaptive user interfaces (UI) presents for a long time an important research area in which researcher attempt to call upon the full resources and skills of several disciplines. The adaptive UI community holds a thorough knowledge regarding the adaptation of UIs with users and with contexts of use. Several solutions, models, formalisms, techniques, and mechanisms were proposed to develop adaptive UI. In this paper, we propose an approach based on the fuzzy set theory for modeling the concept of the appropriateness of different solutions of UI adaptation with different situations for which interactive systems have to adapt their UIs.

Keywords: adaptive user interfaces, adaptation solution’s appropriateness, fuzzy sets

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Authors: Xue Xiao, Sun Hao, Liu Donghua

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E-commerce is experiencing rapid development and evolution, but traditional research methods are difficult to fully demonstrate the relationship between micro factors and macro evolution in the development process of e-commerce, which cannot provide accurate assessment for the existing strategies and predict the future evolution trends. To solve these problems, this paper presents the concept of e-commerce service ecosystem based on the characteristics of e-commerce and business ecosystem theory, describes e-commerce environment as a complex adaptive system from the perspective of ecology, constructs a e-commerce service ecosystem model by using Agent-based modeling method and Java language in RePast simulation platform and conduct experiment through the way of computational experiment, attempt to provide a suitable and effective researching method for the research on e-commerce evolution. By two experiments, it can be found that system model built in this paper is able to show the evolution process of e-commerce service ecosystem and the relationship between micro factors and macro emergence. Therefore, the system model constructed by Agent-based method and computational experiment provides proper means to study the evolution of e-commerce ecosystem.

Keywords: e-commerce service ecosystem, complex system, agent-based modeling, computational experiment

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Authors: Henni Mansour Abdelwaheb

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This study discusses the design of a bounded position/force feedback controller developed to ensure position and force tracking for bilateral teleoperation arms operating with variable delay, and actuator saturation. Also, an adaptive robust Radial Basis Function (RBF) neural network is used to estimate the environment torque. The parameters of the environment torque are then sent from the slave site to the master site as a non-power signal to avoid passivity problems. Moreover, a nonlinear function is applied to each controller term as a smooth saturation function, providing a bounded control signal and preserving the system’s actuators. Lastly, the Lyapunov approach demonstrates the global stability of the controlled system, and numerical experiment results further confirm the validity of the presented strategy.

Keywords: teleoperation manipulators system, time-varying delay, actuator saturation, adaptive robust rbf neural network approximation, uncertainties

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Authors: Huan Li, Jianchun Li, Yancheng Li, Yang Yu

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As a seismic protection method of civil and engineering structures, weakening and damping is effective during the elastic region, while it somehow leads to the early yielding of the entire structure accompanying with large excursions and permanent deformations. Adaptive negative stiffness device is attractive for realizing yielding property without changing the stiffness of the primary structure. In this paper, a new modification negative stiffness device (MNSD) with constant force-displacement characteristic is proposed by combining a magnetic negative stiffness spring, a piecewise linear positive spring and a passive damper with a certain adaptive stiffness device. The proposed passive control MNSD preserves no effect under small excitation. When the displacement amplitude increases beyond the pre-defined yielding point, the force-displacement characteristics of the system with MNSD will keep constant. The seismic protection effect of the MNSD is evaluated by employing it to a single-degree-of-freedom system under sinusoidal excitation, and real earthquake waves. By comparative analysis, the system with MNSD performs better on reducing acceleration and displacement response under different displacement amplitudes than the scenario without it and the scenario with unmodified certain adaptive stiffness device.

Keywords: negative stiffness, adaptive stiffness, weakening and yielding, constant force-displacement characteristic

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Authors: Stephanie Chen, Mitja Echim, Christof Büskens

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To describe and propagate the behavior of a system mathematical models are formulated. Parameter identification is used to adapt the coefficients of the underlying laws of science. For complex systems this approach can be incomplete and hence imprecise and moreover too slow to be computed efficiently. Therefore, these models might be not applicable for the numerical optimization of real systems, since these techniques require numerous evaluations of the models. Moreover not all quantities necessary for the identification might be available and hence the system must be adapted manually. Therefore, an approach is described that generates models that overcome the before mentioned limitations by not focusing on physical laws, but on measured (sensor) data of real systems. The approach is more general since it generates models for every system detached from the scientific background. Additionally, this approach can be used in a more general sense, since it is able to automatically identify correlations in the data. The method can be classified as a multivariate data regression analysis. In contrast to many other data regression methods this variant is also able to identify correlations of products of variables and not only of single variables. This enables a far more precise and better representation of causal correlations. The basis and the explanation of this method come from an analytical background: the series expansion. Another advantage of this technique is the possibility of real-time adaptation of the generated models during operation. Herewith system changes due to aging, wear or perturbations from the environment can be taken into account, which is indispensable for realistic scenarios. Since these data driven models can be evaluated very efficiently and with high precision, they can be used in mathematical optimization algorithms that minimize a cost function, e.g. time, energy consumption, operational costs or a mixture of them, subject to additional constraints. The proposed method has successfully been tested in several complex applications and with strong industrial requirements. The generated models were able to simulate the given systems with an error in precision less than one percent. Moreover the automatic identification of the correlations was able to discover so far unknown relationships. To summarize the above mentioned approach is able to efficiently compute high precise and real-time-adaptive data-based models in different fields of industry. Combined with an effective mathematical optimization algorithm like WORHP (We Optimize Really Huge Problems) several complex systems can now be represented by a high precision model to be optimized within the user wishes. The proposed methods will be illustrated with different examples.

Keywords: adaptive modeling, automatic identification of correlations, data based modeling, optimization

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Authors: Odd Ivar Haugen

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Society increasingly relies on complex systems whose behaviour is determined, not by the properties of each part, but by the interaction between them. The behaviour of such systems is emergent. Modelling emergent system behaviour requires a systems approach that incorporates the necessary concepts that are capable of determining such behaviour. The CESM metamodel is a model of system models. A set of system models needs to address the elements of CESM at different levels of abstraction to be able to model the behaviour of a complex system. Modern ships contain numerous sophisticated equipment, often accompanied by a local safety system to protect its integrity. These control systems are then connected into a larger integrated system in order to achieve the ship’s objective or mission. The integrated system becomes what is commonly known as a system of systems, which can be termed a complex system. Examples of such complex systems are the dynamic positioning system and the power management system. Three ship accidents are provided as examples of how system complexity may contribute to accidents. Then, the three accidents are discussed in terms of how the Multi-Level/Multi-Model Safety Analysis might catch scenarios such as those leading to the accidents described.

Keywords: emergent properties, CESM metamodel, multi-level/multi-model safety analysis, safety, system complexity, system models, systems thinking

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Authors: Rami Faraj, Cezary Graczykowski, Błażej Popławski, Grzegorz Mikułowski, Rafał Wiszowaty

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Progress in the field of sensors, electronics and computing results in more and more often applications of adaptive techniques for dynamic response mitigation. When it comes to systems excited with mechanical impacts, the control system has to take into account the significant limitations of actuators responsible for system adaptation. The paper provides a comprehensive discussion of the problem of appropriate design and implementation of adaptation techniques and mechanisms. Two case studies are presented in order to compare completely different adaptation schemes. The first example concerns a double-chamber pneumatic shock absorber with a fast piezo-electric valve and parameters corresponding to the suspension of a small unmanned aerial vehicle, whereas the second considered system is a safety air cushion applied for evacuation of people from heights during a fire. For both systems, it is possible to ensure adaptive performance, but a realization of the system’s adaptation is completely different. The reason for this is technical limitations corresponding to specific types of shock-absorbing devices and their parameters. Impact mitigation using a pneumatic shock absorber corresponds to much higher pressures and small mass flow rates, which can be achieved with minimal change of valve opening. In turn, mass flow rates in safety air cushions relate to gas release areas counted in thousands of sq. cm. Because of these facts, both shock-absorbing systems are controlled based on completely different approaches. Pneumatic shock-absorber takes advantage of real-time control with valve opening recalculated at least every millisecond. In contrast, safety air cushion is controlled using the semi-passive technique, where adaptation is provided using prediction of the entire impact mitigation process. Similarities of both approaches, including applied models, algorithms and equipment, are discussed. The entire study is supported by numerical simulations and experimental tests, which prove the effectiveness of both adaptive impact mitigation techniques.

Keywords: adaptive control, adaptive system, impact mitigation, pneumatic system, shock-absorber

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Authors: Zheng Zhihao

Abstract:

Recently, Knowledge Graph Framework Network (KGCN) has developed powerful capabilities in knowledge representation and reasoning tasks. However, traditional KGCN often uses a fixed weight mechanism when aggregating information, failing to make full use of rich structural information, resulting in a certain expression ability of node representation, and easily causing over-smoothing problems. In order to solve these challenges, the paper proposes an new graph neural network model called KGCN-STAR (Knowledge Graph Convolutional Network with Structural Adaptive Receptive Fields). This model dynamically adjusts the perception of each node by introducing a structural adaptive receptive field. wild range, and a subgraph aggregator is designed to capture local structural information more effectively. Experimental results show that KGCN-STAR shows significant performance improvement on multiple knowledge graph data sets, especially showing considerable capabilities in the task of representation learning of complex structures.

Keywords: knowledge graph, graph neural networks, structural adaptive receptive fields, information aggregation

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