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

共 1436 条记录，以下是181-190 订阅

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Brained-Inspired Optical Computing Unit Based on Transient nonlinear dynamics of Single-Mode Fibers

Brained-Inspired Optical Computing Unit Based on Transient N...

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conference on Lasers and Electro-Optics (CLEO)

作者： Nicolas Perron Bennet Fischer Mario Chemnitz Yi Zhu Piotr Roztocki Benjamin MacLellan Luigi Di Lauro A. Aadhi Cristina Rimoldi Tiago H. Falk Roberto Morandotti Institut National de la recherche scientifique Varennes Canada Leibniz Institute of Photonic Technology Jena Germany Ki3 Photonics Technologies Quebec Canada Dipartimento di Elettronica e Telecomunicazioni Politecnico di Torino Torino Italy

We developed and studied a hardware-based neuromorphic wave computer using optical nonlinearities. Here, we showcase the low-power consumption, robustness, and scalable complexity of soliton-based spectral broadening ... 详细信息

ISBN: (纸本)9798350369311

关键词： Optical fibers Neuromorphics Optical solitons Optical computing Hardware Robustness Optical network units nonlinear dynamical systems Transient analysis Photonics

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A Pontryagin-Based Game-Theoretic Approach for Robust nonlinear Model Predictive Control

A Pontryagin-Based Game-Theoretic Approach for Robust Nonlin...

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IEEE conference on Decision and Control

作者： Michele Pagone Lorenzo Zino Carlo Novara Department of Electronics and Telecommunications Politecnico di Torino Torino Italy

A Pontryagin-based differential game approach to solve a class of robust nonlinear Model Predictive Control is proposed. The methodology defines an optimal control policy that takes into account non-accurate predictions of the system dynamics due to modeling errors and/or unknown exogenous disturbance, which may seriously compromise the controller performances. To this end, we propose a Pontryagin-based solution to the nonlinear min-max problem, which can be viewed as a zero-sum differential game, where the two players are the controlled input and the system's uncertainty/external disturbance. We show that, under suitable assumptions on system's dynamics, the game admits a Nash equilibrium, whose knowledge drastically decreases the high algorithmic complexity usually required for min-max optimization schemes. Finally, the theoretical results are confirmed by numerical simulations, performed on the Van der Pol nonlinear oscillator.

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Event-triggered adaptive gradient descent neural network backstepping control for a class of uncertain nonlinear systems

Event-triggered adaptive gradient descent neural network bac...

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Chinese Control and Decision conference, CCDC

作者： Jiaxing Yang Xuebo Yang Zhongbo Chen Jiatong Wang Xiaolong Zheng Harbin Institute of Technology Bohai University

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

This paper presents an event-triggered adaptive neural network (NN) backstepping control method for a class of uncertain nonlinear systems. The combination of NN and backstepping technique solves the complexity explosion and compensates for the system unmodeled dynamics. At the same time, the NN weight trained by the gradient descent algorithm can ensure NN approximation performance to the unknown nonlinear function. Further, a smooth switching trigger strategy is introduced to achieve a lower updating frequency of the system control signal. According to the Lyapunov criterion, the tracking error of the system is semi-globally uniformly bounded and the system controller does not behave Zeno. Finally, the proposed method is applied to the simulation model of a DC motor control system.

关键词： Backstepping Adaptive systems Heuristic algorithms Artificial neural networks Switches Control systems DC motors

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Inverse dynamics vs. Forward dynamics in Direct Transcription Formulations for Trajectory Optimization

Inverse Dynamics vs. Forward Dynamics in Direct Transcriptio...

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IEEE International conference on Robotics and Automation (ICRA)

作者： Ferrolho, Henrique Ivan, Vladimir Merkt, Wolfgang Havoutis, Ioannis Vijayakumar, Sethu Univ Edinburgh Sch Informat Edinburgh Midlothian Scotland Univ Oxford Oxford Robot Inst Oxford England

ISBN: (纸本)9781728190778

Benchmarks of state-of-the-art rigid-body dynamics libraries report better performance solving the inverse dynamics problem than the forward alternative. Those benchmarks encouraged us to question whether that computational advantage would translate to direct transcription, where calculating rigid-body dynamics and their derivatives accounts for a significant share of computation time. In this work, we implement an optimization framework where both approaches for enforcing the system dynamics are available. We evaluate the performance of each approach for systems of varying complexity, for domains with rigid contacts. Our tests reveal that formulations using inverse dynamics converge faster, require less iterations, and are more robust to coarse problem discretization. These results indicate that inverse dynamics should be preferred to enforce the nonlinear system dynamics in simultaneous methods, such as direct transcription.

关键词： Automation System dynamics conferences Benchmark testing Libraries nonlinear dynamical systems complexity theory

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A Minimum-Propellant Pontryagin-Based nonlinear MPC for Spacecraft Rendezvous in Lunar Orbit

A Minimum-Propellant Pontryagin-Based Nonlinear MPC for Spac...

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IEEE conference on Decision and Control

作者： Giordana Bucchioni Francesco Alfino Michele Pagone Carlo Novara Department of Information Engineering of University of Pisa Pisa Italy Department of Electronics and Telecommunications of Politecnico di Torino Torino Italy

We propose a nonlinear Model Predictive Control approach to spacecraft rendezvous in non-Keplerian Lunar orbits. The approach is based on the Pontryagin Minimum Prin-ciple and allows the accomplishment of minimum-propellant maneuvers. The relative motion between the chaser and the target is described by the nonlinear and unstable dynamics of the circular restricted three body-problem. In the pro-posed formulation, we design a minimum-propellant controller, which leads to a bang-bang behavior of the control signal. Under suitable assumptions, simplified dynamics is employed as prediction model, in order to reduce the complexity of the controller algorithm but, at the same time, without penalizing the controller tracking performance. The proposed approach's effectiveness is validated by a simulation example.

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nonlinear Assessment of Gait Signal complexity in Neurodegenerative Disorders

Nonlinear Assessment of Gait Signal Complexity in Neurodegen...

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

作者： Radhagayathri Udhayakumar Shivapratap Gopakumar Saifur Rahman Chandan Karmakar Center for Wireless Networks & Applications Amrita Vishwa Vidyapeetham Amritapuri Kerala India The School for Sustainable Futures Amrita Vishwa Vidyapeetham Amritapuri Kerala India School of Information Technology Deakin University Burwood VIC Australia

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

The human gait cycle undergoes discernible alterations upon the onset of neurodegenerative diseases (NDD) such as Parkinson’s, Huntington’s, and Amyotrophic lateral sclerosis. Each specific neurodegenerative disorder imparts a distinct influence on human gait dynamics, and precise quantification of these changes holds the potential for accurate methods of NDD *** entropy algorithms, such as sample entropy (SampEn), find widespread use in physiological signal analysis. SampEn gauges signal complexity by identifying pattern matches within windowed sub-segments of the signal. However, traditional SampEn is notably dependent on user-defined parameters, particularly the tolerance parameter r, leading to inaccuracies in complexity *** profiling emerges as an alternative concept, eliminating the need for an input r parameter. This data-driven algorithm autonomously generates a set of ’r’ values based on the signal’s dynamics, yielding a comprehensive SampEn profile. The SampEn profile, containing extensive information about the signal’s complexity, serves as a valuable resource for extracting secondary entropy *** this study, we have contrasted the efficacy of traditional SampEn with SampEn profile-based secondary features such as Total SampEn (TSE) and Median SampEn (MSE), in identifying neurological states. Our findings consistently reveal that secondary features derived from the reduced-parametric SampEn profiling method outperform the traditional parametric SE in distinguishing control cohorts from specific Neurodegenerative Disease (NDD) cohorts.

关键词： Neurological diseases Heuristic algorithms Feature extraction Motors Entropy Physiology complexity theory Data mining Signal analysis Pattern matching

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Optimization of Power in Power Converters Using Machine Learning: An Overview

Optimization of Power in Power Converters Using Machine Lear...

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Sustainable Energy Technologies and Computational Intelligence (SETCOM), International conference on

作者： Prashant Kumar Nayak Debabrata Swain Kaibalya Prasad Panda Department of Computer Science and Engineering Pandit Deendayal Energy University Gandhinagar India Department of Electrical Engineering School of Energy Technology Pandit Deendayal Energy University Gandhinagar India

ISBN: (数字)9798331520540

ISBN: (纸本)9798331520557

The rapid evolution in power electronics have brought significant attention to the optimization of power converters, which are essential for efficient energy conversion and management. Traditional techniques for optimizing power converters often struggle with the increasing complexity of modern systems, including nonlinear dynamics, diverse operating conditions, and stringent efficiency requirements. Last few decades, it has been observed that machine learning has evolved as hopeful solution with data driven methodologies to address various challenges. This survey provides the integration of machine learning for optimizing power converter, reviewing new approaches, key procedures and application in different domain. This categorizes different types of machine learning techniques and evaluate their usage in multiple fields like real-time control, fault detection, thermal management and system design. The paper also discusses different datasets, evaluation metrics and implementation framework in field of power converters. Lastly, challenges like computational complexity, data security and real-world deployment are highlighted along with direction towards future research to enhance the integration between machine learning and power converters. The comprehensive review aims to provide insight of researchers carried out to develop an intelligent power system.

关键词： Training Surveys Reviews Neural networks Machine learning Thermal management Real-time systems Power systems nonlinear dynamical systems Optimization

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Flatness-Based Identification of nonlinear dynamics

Flatness-Based Identification of Nonlinear Dynamics

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Mediterranean conference on Control and Automation (MED)

作者： Alexander M. Kopp Lisa Fuchs Christoph Ament Chair of Control Engineering at the Faculty of Applied Computer Science University of Augsburg Augsburg Germany

ISBN: (数字)9798350395440

ISBN: (纸本)9798350395457

The identification of a nonlinear system model given only measurement data is a frequently encountered task. Uncovering the structure of differential equations as system model alongside with the determination of the optimal parameters is still problem under investigation. Assuming a differentially flat system under investigation, an algorithm for single input single output systems is proposed that faces this identification task. To find a proper state space model, an iterative strategy is presented expanding an initial solution in every step. Harnessing only the measurement data and not their time derivatives a criterion is proposed to select promising extensions to the model avoiding extensive simulation studies on possible model structures. Applying a subset selection reduces the complexity of the resulting models and avoids overfitting. To show the capability of the presented approach to identify a nonlinear state space model from data, a simulation example is presented.

关键词： Training Neural networks Differential equations Solids Polynomials Mathematical models Data models

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Design and Experiment of Hierarchical Coordinated Control for Trajectory Tracking of Unmanned Motorcycles

Design and Experiment of Hierarchical Coordinated Control fo...

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conference on Vehicle Control and Intelligence (CVCI)

作者： Jinghao Liu Lu Yang Bo Cui Yahong Li Yijie Chen School of Mechanical Engineering Beijing Institute of Technology Beijing P. R. China National Key Laboratory of Multi-perch Vehicle Driving Systems and the National Key Laboratory of Automotive Chassis Integration and Bionics China North Vehicle Research Institute Beijing P. R. China

ISBN: (数字)9798331504892

ISBN: (纸本)9798331504908

The non-coaxial two-wheeled unmanned plat-forms, such as unmanned motorcycles and unmanned bicycles, have garnered significant interest from both academic and industrial communities because of compact structure and high maneuverability in narrow and uneven terrain environment. However, such unmanned platforms are essentially underactu-ated system with a strong coupling between the steering, drive and rolling subsystems, contributing to significant challenges in balancing and trajectory tracking control. To address such issues, this paper proposes a hierarchical coordinated trajectory tracking control scheme for unmanned motorcycles operating in complex environment with unmodeled dynamics and external disturbances. Specifically, an upper-level motion planner is designed to account for velocity constraints by using a nonlinear saturation function. Meanwhile, a lower-level dynamic tracking controller based on the linear quadratic regulation (LQR) method is constructed to track the planned velocity signal due to its simple control structure and parametric adaptability characteristic. By integrating kinematics and dynamics control in this hierarchical approach, the design complexity of the control system is considerably reduced, and the robustness of the system is further enhanced. Finally, numerical simulation and experimental test are performed to validate the feasibility and effectiveness of the proposed hierarchical coordinated trajectory tracking control scheme.

关键词： Trajectory tracking Simulation dynamics Motorcycles Robustness Mathematical models Software nonlinear dynamical systems Trajectory Vehicle dynamics

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A Transient Voltage Security Analysis Method Considering the dynamics of Renewable Energy Stations and Impact Loads

A Transient Voltage Security Analysis Method Considering the...

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Power Energy Systems and Applications (ICoPESA), International conference on

作者： Yilin Cui Shaoyang He Xiaofeng Yu Weikun Liang Shunjiang Lin Yuhang Xiao Xuquan Xie Heyuan Power Supply Bureau Guangdong Power Grid Co. Ltd. Heyuan China School of Electric Power Engineering South China University of Technology Guangzhou China

ISBN: (数字)9798350351668

ISBN: (纸本)9798350351675

A transient voltage security analysis (TVSA) method considering the dynamics of renewable energy stations and impact loads in power system is proposed. Base on the physical mechanism analysis of the third-order electromechanical transient model of induction motors, a data-driven method for identifying time-varying parameters is proposed and an accurate impact dynamic model is established to describe the startup process of impact loads. Considering the dynamic modeling of impact loads, renewable energy stations, synchronous generators and conventional loads, differential algebraic equations (DAEs) for TVSA of power systems are established. An improved implicit trapezoidal integration method is proposed to transform DAEs into nonlinear algebraic equations, and a polynomial interpolation function curve correction method is proposed to solve the nonlinear equations efficiently, which is not required to calculate Jacobian matrices. It has low computational complexity and fast convergence speed. Case study on a modified IEEE 39-bus system demonstrate that the proposed method can efficiently obtain the time-domain simulation results of DAEs for the TVSA of power systems and has high computational accuracy.

关键词： Renewable energy sources Analytical models Accuracy Power system dynamics Voltage Mathematical models Computational efficiency Security Transient analysis Load modeling

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