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检索条件"任意字段=Conference on Complexity and Nonlinear Dynamics"

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Pattern dynamics of Prey–Predator Model with Swarm Behavior via Turing Instability and Amplitude Equation 1st

Pattern Dynamics of Prey–Predator Model with Swarm Behavior...

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1st International conference on Mathematical Modelling, Computational Intelligence and Renewable energy, MMCITRE 2020

作者： Singh, Teekam Shivam Kumar, Mukesh Vimal, Vrince Department of Mathematics Graphic Era Deemed to be University Dehradun248002 India Department of Mathematics Graphic Era Hill University Dehradun248002 India Department of Computer Science & Engineering Graphic Era Hill University Dehradun248002 India

ISBN: (纸本)9789811599521

In this paper, we propose and analyze the spatial prey–predator system with swarm behavior. Firstly, we examine the possibility and uniqueness of the coexistence equilibrium solutions of the model. We obtain Turing instability for spatial prey–predator model. By the use of weakly nonlinear analysis near the threshold value of parameter for patterns, we obtain the amplitude equation. Finally, we present numerical outcomes to justify the numerical results. Some interesting patterns show the spatial dynamical complexity of prey–predator model. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： nonlinear analysis

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Towards a Framework for nonlinear Predictive Control using Derivative-Free Optimization 7

Towards a Framework for Nonlinear Predictive Control using D...

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7th IFAC conference on nonlinear Model Predictive Control (NMPC)

作者： McInerney, Ian Nita, Lucian Nie, Yuanbo Oliveri, Alberto Kerrigan, Eric C. Imperial Coll London Dept Elect & Elect Engn London SW7 2AZ England Imperial Coll London Dept Aeronaut London SW7 2AZ England Univ Genoa Dept Elect Elect Telecommun Engn & Naval Architec Via Opera Pia 11a I-16145 Genoa Italy

The use of derivative-based solvers to compute solutions to optimal control problems with non-differentiable cost or dynamics often requires reformulations or relaxations that complicate the implementation or increase computational complexity. We present an initial framework for using the derivative-free Mesh Adaptive Direct Search (MADS) algorithm to solve nonlinear Model Predictive Control problems with non-differentiable features without the need for reformulation. The MADS algorithm performs a structured search of the input space by simulating selected system trajectories and computing the subsequent cost value. We propose handling the path constraints and the Lagrange cost term by augmenting the system dynamics with additional states to compute the violation and cost value alongside the state trajectories, eliminating the need for reconstructing the state trajectories in a separate phase. We demonstrate the practicality of this framework by solving a robust rocket control problem, where the objective is to reach a target altitude as close as possible, given a system with uncertain parameters. This example uses a non-differentiable cost function and simulates two different system trajectories simultaneously, with each system having its own free final time. Copyright (C) 2021 The Authors.

关键词： optimal control mesh adaptive direct search derivative-free optimization

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Siting and Sizing of Shunt Compensation Considering Dynamic Reactive Power Optimization Strategy

Siting and Sizing of Shunt Compensation Considering Dynamic ...

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IEEE Asia Power and Energy Engineering conference (APEEC)

作者： Zongbao Zhang Haoran Wang Biao Zhao Xinwei Shen Power Dispatch Control Center Shenzhen Power Supply Co. Ltd. Shenzhen China Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen China

ISBN: (数字)9798350373479

ISBN: (纸本)9798350373486

China's power system is currently undergoing a transformation and upgrade towards new power system that prioritizes renewable energy sources. Strengthening reactive power and voltage control is crucial to ensure the safe and economical operation of this system. In this paper, we propose a siting and sizing method of shunt reactive power compensation that considers dynamic reactive power optimization strategy, aiming to minimize power transmission loss in each time period from an economic perspective. The dynamic reactive power optimization problem is characterized by its large-scale, multi-period, and strong coupling nature, which makes it a mixed-integer nonlinear programming problem. The main challenges with solving this problem lie in handling the highly nonlinear AC power flow equation constraints and the constraints associated with switching operation times of discrete reactive power compensation devices. To address these challenges, we propose a siting and sizing method of shunt reactive power compensation that considers operational optimization. The AC power flow equation constraints are handled using second-order cone relaxation, while the switching operation times constraints are equivalently transformed into a linear inequality constraint set. This approach reduces computational complexity while ensuring sufficient accuracy to meet practical engineering needs. The proposed method's effectiveness and economic viability are validated through case studies conducted on the IEEE 30-bus system.

关键词： Economics Reactive power Power system dynamics Power transmission Switches Propagation losses Mathematical models

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Multiscale Diffusion Entropy Analysis for the Detection of Crucial Events in Cardiac Pathology

Multiscale Diffusion Entropy Analysis for the Detection of C...

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Annual International conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Sara A. Nasrat Korosh Mahmoodi Ahsan H. Khandoker Paolo Grigolini Herbert F. Jelinek Biomedical Engineering Department Khalifa University of Science and Technology Abu Dhabi UAE Center for Nonlinear Science University of North Texas Denton TX USA

The significance of crucial events in explaining the dynamics of a physiological system has only been recently emerging. Crucial events are yet to be fully understood and implemented in clinical applications of physiological signal processing. This paper proposes the application of modified diffusion entropy (MDEA) and novel multiscale diffusion entropy analyses (MSDEA) on measuring the temporal complexity of the ECG time series to improve crucial events detection performance. Thirty samples of each of three groups of ECG datasets from PhysioNet with recordings of cardiac arrhythmia (ARR), congestive heart failure (CHF) and normal sinus rhythm (NSR) were analyzed using MDEA with stripes followed by MSDEA. Healthy NSR ECGs showed an approximate 15% greater inverse power law (IPL) and scaling δ indices than pathologic CHF and ARR signals. Additionally, the scaling indices for the pathologic groups showed higher standard deviations, indicating that crucial events determined by MDEA reveal latent differences in ECG complexity that could better be investigated across multiple time scales of temporally decomposed signals using MSDEA which combines multiscale entropy (MSE) and MDEA. Hence, MSDEA showed an improved, clearer discrimination between the healthy and pathological cardiac signals (p<0.0005) characterized by a range of NSR complexity indices twice the range of the pathological values associated with ARR and CHF across twenty temporal scales as well as more reliable trend lines (R 2 >=0.95).Clinical Relevance— This research proposes a novel and enhanced diagnostic discrimination across healthy and pathologic cardiac conditions based on biomedical signal processing of ECG recordings utilizing the principle of crucial events detection.

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THE EVOLVED MOTIONS OF A MARINE RISER OR PIPELINE 40

THE EVOLVED MOTIONS OF A MARINE RISER OR PIPELINE

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40th ASME International conference on Ocean, Offshore and Arctic Engineering (OMAE)

作者： Zueck, Robert F. US Navy NAVFAC EXWC Port Hueneme CA USA

ISBN: (纸本)9780791885147

Analytical, experimental and computational models have historically been heavily simplified, linearized, and otherwise reduced. This paper shows how such model reductions eliminate the fundamental geometric changes that determine real behavior in cables, strings, moorings, guys, pipelines, riser, plates, skins, subsea hulls, and other such slender and thin structures. The paper details each physical quantity that we must add back into our overly reduced models to improve the basic nature, evolution, and accuracy of the resulting motions and vibrations. For example, even slight changes in local rotation anywhere along a cable can create large nonlinear changes in the dynamic nature of its behavior. The evolved complexity of the resulting global motions and vibrations in space and time often defy what we normally expect from such a simple structure. Although this paper focuses on the modeling of deep-water moorings and risers of an ocean platform, the same geometric effect is fundamental to most science and engineering models. Understanding how small changes in geometry can nonlinearly affect any structured behavior will help demystify much of the poorly-understood motions and vibrations in a large diversity of applications, including induced vibrations, sound, structural acoustics, aero-elasticity, sound, light and atomic radiation.

关键词： cable string rope pipe mooring structure fluid drag catenary nonlinear dynamics geometry vibration

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Advancing Optimized nonlinear Control Strategies for Cancerous Tumor dynamics

Advancing Optimized Nonlinear Control Strategies for Cancero...

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Emerging Trends in Electrical, Control, and Telecommunication Engineering (ETECTE), International conference on

作者： Atif Rehman Rimsha Ghias Syed Hassan Ahmed Shah Shabab Saleem Iftikhar Ahmad School of Interdisciplinary Engineering and Sciences (SINES) National University of Sciences and Technology (NUST) Islamabad Pakistan School of Electrical Engineering and Computer Science (SEECS) National University of Sciences and Technology (NUST) Islamabad Pakistan

Cancer presents a substantial worldwide health concern, with its uncontrolled cell growth, invasive nature, and intricate diagnostic and treatment requisites. Exploring this complexity, the nonlinear mathematical models of cancerous tumor cells provide deep insights into their actions and feasible intervention approaches. Researchers have carefully constructed these mathematical structures to enhance our understanding of how cancerous tumors develop, focusing particularly on untangling the intricate interactions among tumor cells, hunting predator cells, and resting predator cells. This paper introduces a variety of nonlinear controllers, with a specific emphasis on integral sliding mode control (ISMC) and integral super-twisting sliding mode control (ISTSMC). The main aim of implementing these controllers is to mitigate the expansion of tumor cells to a non-threatening magnitude, optimize the abundance of hunting predator cells, and sustain resting predator cells at a level equivalent to 40% of the count of hunting predator cells. The controller gains have been meticulously refined through the utilization of a genetic algorithm, wherein the optimization objective is anchored on the integral time absolute error. The mathematical analysis incorporates the Lyapunov stability criteria to firmly establish the asymptotic stability of the introduced controllers. Employing MATLAB/Simulink, all simulations are meticulously executed, enabling a comprehensive and insightful performance comparison among the proposed control strategies. Advancing beyond the realm of simulation, real-time validation entails a hardware-in-loop experimental configuration, seamlessly integrating the capabilities of the C2000 Delfino alongside the MCU F28379D Launchpad.

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complexity and nonlinearities of Short-Term Cardiovascular and Cerebrovascular Controls after Surgical Aortic Valve Replacement 42

Complexity and Nonlinearities of Short-Term Cardiovascular a...

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42nd Annual International conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC)

作者： Porta, Alberto Fantinato, Angela Bari, Vlasta Cairo, Beatrice De Maria, Beatrice Bertoldo, Enrico Giuseppe Fiolo, Valentina Callus, Edward De Vincentiis, Carlo Volpe, Marianna Molfetta, Raffaella Ranucci, Marco Univ Milan Dept Biomed Sci Hlth Milan Italy IRCCS Policlin San Donato Dept Cardiothorac Vasc Anesthesia & Intens Care Milan Italy IRCCS Ist Clin Sci Maugeri Milan Italy IRCCS Policlin San Donato Clin Psychol Serv Milan Italy IRCCS Policlin San Donato Dept Cardiac Surg Milan Italy IRCCS Policlin San Donato Dept Cardiac Rehabil Milan Italy

ISBN: (纸本)9781728119908

We assessed the effect of surgical aortic valve replacement (SAVR) on cardiovascular and cerebrovascular controls with particular attention to their complexity and presence of nonlinear behaviors via the analysis of spontaneous variability of heart period (HP), systolic and diastolic arterial pressure (SAP and DAP) and mean cerebral blood flow (MCBF). Variability series were acquired before (PRE) and after (POST) SAVR in 12 patients (age: 76 +/- 4.7 yrs, 7 males) at rest in supine position and during active standing. complexity was assessed via a local nonlinear prediction approach exploiting the k-nearest neighbor strategy. The presence of nonlinear dynamics was checked by comparing the complexity marker computed over the original series with the distribution of values assessed over 100 surrogates preserving distribution and power spectral density of the original series but with random phases. We found that: i) HP variance was significantly reduced in POST;ii) the complexity of SAP and DAP variabilities increased in POST with a greater likelihood of observing nonlinear dynamics over SAP compared to PRE at supine rest;iii) the amplitude of MCBF fluctuations and its complexity in POST remained similar to PRE. SAVR induces important changes of the cardiac and vascular autonomic controls, while cerebrovascular regulation seems to be less affected.

关键词： dynamics

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A Comprehensive Study of Artificial Neural Networks in Power System Stability

A Comprehensive Study of Artificial Neural Networks in Power...

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IEEE SSD International Multi-conference on Systems, Signals and Devices

作者： Shaimaa Shukri Abd. Alhalim Wissem Bahloul Mohamed Chtourou Nabil Derbel Department of Electrical Engineering University of Technology Baghdad Iraq University of Sfax ENIS Laboratory of Control & Energy Management (CEM-Lab) Sfax Tunisia

ISBN: (数字)9798350374131

ISBN: (纸本)9798350374148

The stability of the power system is important for ensuring the power grid's reliable operation. Traditional stability analysis and stabilization methods have limitations in handling the complexity and nonlinearity of modern power systems. The combination of artificial neural network (ANN)based approaches holds particular promise for power system stability and addressing stabilization challenges. This paper aims to investigate the use of neural methods to improve the analysis and stabilization of complex power systems. Research will focus on neural network architectures and algorithms that can accurately predict and ensure the stability of power systems under various operating conditions. By using neural networks, the research aims to overcome the limitations of traditional methods and provide intelligent solutions to ensure the stability and the robustness of power systems in the face of challenges in the ongoing process. This comprehensive review provides in-depth insights into the applications, techniques, and advancements of ANN in power system stability analysis and control. The study includes ANN basic principles and appropriateness to model complex nonlinear relationships in dynamical systems and evaluate them, including feedforward. This study looks into how ANNs can be used to improve system stability and response to disturbances in areas like fault detection, dynamic modeling, control strategies, and stability assessment.

关键词： Regulators Reviews Power system dynamics Artificial neural networks Power system stability Prediction algorithms Stability analysis

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A Matching Energy based approach in wavelet domain to distinguish hyper-responsive behavior in Autism Spectrum Disorders

A Matching Energy based approach in wavelet domain to distin...

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IEEE India conference (INDICON)

作者： Priyalakshmi Sheela Subha D Puthankattil Department of Electrical Engineering National Institute of Technology Calicut Kozhikode India

ISBN: (纸本)9781665452724

Hyper-or hypo-responsive behavior to sensory stimulus confers heterogeneity to Autism Spectrum Disorders (ASD), and deteriorates the communication skills and learning ability of such individuals. Treatment should be tailored to the individual based on inter-individual variability. The current study is an attempt to differentiate the hyper-responsive subgroup from ASD by examining the complexity variations in Visual Evoked Potentials (VEPs), measured from a group of 30 individuals with ASD, in presence of achromatic sinusoidal gratings under low (5%), medium (50%) and high (90%) contrasts. This study proposes a diagnostic framework that includes an optimization-based denoising method, wavelet decomposition and extraction of matching energy (ME) to analyze complexity. Transient Artifact Reduction Algorithm (TARA) is employed to eliminate majority of the noise components in VEPs. Seven-level wavelet decomposition is performed on the denoised VEPs to decompose it into five frequency bands of gamma, beta, alpha, theta and delta. ME, a nonlinear complexity metric is extracted from these bands to perform relative complexity analysis (RC) with the variation in contrasts. The ME-based RC analysis reveals an increasing complexity pattern with progressing contrasts in 43%-50% of the ASD group in all the frequency bands. This pattern highlights the presence of heterogeneity and identifies the hyper-responsive subgroup in ASD. Overall, the results of this research highlight the potential of nonlinear dynamics in examining the heterogeneity and discerning the hyper-responsive subgroup in ASD thus aiding in targeted medical intervention which could improve the social skills of individuals with ASD.

关键词： Autism Visualization Wavelet domain Current measurement Wavelet analysis complexity theory Behavioral sciences

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nonlinear Robust Control for Dual-UAV Collaborative Aerial Transportation System

Nonlinear Robust Control for Dual-UAV Collaborative Aerial T...

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Artificial Intelligence Technology (ACAIT), Asian conference on

作者： Huiying Ye Hai Yu Bingbing Liu Jianda Han Yongchun Fang Xiao Liang Institute of Robotics and Automatic Information System Nankai University Tianjin China

ISBN: (数字)9798350359145

ISBN: (纸本)9798350359152

Quadrotor UAVs have the advantages of high flexibility and mobility, and the use of UAVs for transportation tasks can avoid the restrictions of complex terrain while improving transportation efficiency and reducing transportation costs. However, as the load capacity of a single UAV is very limited, multiple UAVs are introduced for coordinated transport to increase the system’s capacity. Aiming at transporting bar-shaped cargos, this paper studies the dual-UAV cooperative transportation system. However, compared with the single UAV transportation system, the dual-UAV cooperative transportation system has higher degrees of freedom, stronger nonlinearity, and more complex state coupling. Besides, considering the uncertainty and complexity of the actual environment, the system may encounter external disturbances during actual flight. Thus, to overcome the aforementioned challenges, an effective control scheme is urgently needed to ensure precise UAV positioning and cargo swing suppression for smooth cargo transportation. Therefore, this paper proposes a nonlinear robust control scheme based on the finite-time disturbance observer for the dual-UAV collaborative aerial transportation system. Subsequently, the convergence of the equilibrium point is proved by Lyapunov techniques and LaSalle’s Invariance Theorem. Finally, the excellent performance and robustness of the proposed control scheme are verified by groups of simulations.

关键词： Robust control Uncertainty System dynamics Transportation Collaboration Autonomous aerial vehicles Robustness

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