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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331-340 订阅

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Identification of nonlinear road-vehicle dynamic behavior using autoregressive technique 11

Identification of nonlinear road-vehicle dynamic behavior us...

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11th International conference on Structural dynamics, EURODYN 2020

作者： Anwar, Mohab Tamer, Mostafa Tawfik, Mohamed Ibrahim, Hesham H. Research Assistant Mechatronics Department German University in Cairo New Cairo Egypt Academy of Knowledge Cairo Egypt Mechatronics Department German University in Cairo New Cairo Egypt

ISBN: (纸本)9786188507203

This work presents an identification technique for the suspension dynamics of a nonlinear full car model by implementing an autoregressive system with exogenous input (ARX). The ARX model was proposed as a simple and powerful tool, in terms of accuracy and computational time, compared to the complexity and significant computational cost involved with the neural networks approach which is commonly used. Firstly, the training data is provided through a full car model simulated by Matlab/Simulink. Then the training data is fed into the autoregressive algorithm, which in turn provided an autoregressive model for the suspension dynamic behavior, while this model was calibrated using another data set grabbed from the same Simulink model. Several RMS values of noise were added to different types of road excitation in order to assess the efficiency of the proposed ARX system in terms of noise filtration. Finally, the active response the autoregressive system is simulated, using a PID controller, and compared with those of the Simulink model. The proposed system identification technique proved it's efficiency in terms of accuracy in the light of its very fast computational speed. © 2020 European Association for Structural dynamics. All rights reserved.

关键词： Efficiency

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Trajectory Tracking of Underactuated Sea Vessels With Uncertain dynamics: An Integral Reinforcement Learning Approach

Trajectory Tracking of Underactuated Sea Vessels With Uncert...

引用

IEEE International conference on Systems, Man, and Cybernetics (SMC)

作者： Abouheaf, Mohammed Gueaieb, Wail Miah, Md Suruz Spinello, Davide Univ Ottawa Sch Elect Engn & Comp Sci Ottawa ON Canada Bradley Univ Dept Elect & Comp Engn Peoria IL USA Univ Ottawa Dept Mech Engn Ottawa ON Canada

ISBN: (纸本)9781728185262

Underactuated systems like sea vessels have degrees of motion that are insufficiently matched by a set of independent actuation forces. In addition, the underlying trajectory-tracking control problems grow in complexity in order to decide the optimal rudder and thrust control signals. This enforces several difficult-to-solve constraints that are associated with the error dynamical equations using classical optimal tracking and adaptive control approaches. An online machine learning mechanism based on integral reinforcement learning is proposed to find a solution for a class of nonlinear tracking problems with partial prior knowledge of the system dynamics. The actuation forces are decided using innovative forms of temporal difference equations relevant to the vessel's surge and angular velocities. The solution is implemented using an online value iteration process which is realized by employing means of the adaptive critics and gradient descent approaches. The adaptive learning mechanism exhibited well-functioning and interactive features in react to different desired reference-tracking scenarios.

关键词： Approximate Dynamic Programming Integral Reinforcement Learning Adaptive Critics Underactuated Vessels

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Evolution of the spatiotemporal complexity in a phase-conjugate feedback laser system 9

Evolution of the spatiotemporal complexity in a phase-conjug...

引用

conference on Semiconductor Lasers and Laser dynamics IX

作者： Malica, Tushar Bouchez, Guillaume Wolfersberger, Delphine Sciamanna, Marc Chaire Photon LMOPS Cent Supelec 2 Rue Edouard Belin F-57070 Metz France Univ Lorraine LMOPS 2 Rue Edouard Belin F-57070 Metz France

ISBN: (纸本)9781510634855

A semiconductor laser having an emission wavelength of 852 nm is subjected to phase-conjugated feedback. The phase conjugation is implemented using a Rh-doped BaTiO3 photorefractive crystal of the dimension 5mm x 5mm x 5mm. A combination of several phenomena including light fanning, total internal reflection and four-wave mixing occur in tandem inside the crystal to generate the phase conjugate of the light entering the crystal. Our recent works have established that such configuration exhibits significantly enhanced chaos bandwidth with high spatiotemporal complexity at varied feedback strengths, compared to its conventional optical feedback counterpart in a long external cavity setup. The presented work studies the systematic progression of spatiotemporal complexity in a long-length (approximate to 1.5 m) external cavity setup as a function of the feedback strength. System outputs at varied operating conditions are found to be highly complex with PE upwards of 0.9 and chaos BW in the order of several GHz. Such complex outputs have relevance for applications such as security-based communication and random-bit generation. These system outputs are shown to be dynamically diverse ranging from wide-band chaos to time-periodic oscillations of the output signal corresponding to a higher multiple of the external cavity frequency. The analyses performed in the temporal and frequency domain use several diagnostic tools including permutation entropy, continuous wavelet transform, and statistically calculated chaos bandwidth to unveil and dissect the evolution of the system's characteristic temporal signatures. Thus, we comprehensively determine the true chaotic nature of the system outputs in the spatiotemporal domain.

关键词： Semiconductor lasers nonlinear laser dynamics Phase-conjugate feedback Spatiotemporal complexity

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Safety-Critical Control Synthesis for Unknown Sampled-Data Systems via Control Barrier Functions

Safety-Critical Control Synthesis for Unknown Sampled-Data S...

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IEEE conference on Decision and Control

作者： Luyao Niu Hongchao Zhang Andrew Clark Worcester Polytechnic Institute Worcester MA USA

ISBN: (纸本)9781665436601

As the complexity of control systems increases, safety becomes an increasingly important property since safety violations can damage the plant and put the system operator in danger. When the system dynamics are unknown, safety-critical synthesis becomes more challenging. Additionally, modern systems are controlled digitally and hence behave as sampled-data systems, i.e., the system dynamics evolve continuously while the control input is applied at discrete time steps. In this paper, we study the problem of control synthesis for safety-critical sampled-data systems with unknown dynamics. We overcome the challenges introduced by sampled-data implementation and unknown dynamics by constructing a set of control barrier function (CBF)-based constraints. By satisfying the constructed CBF constraint at each sampling time, we guarantee the unknown sampled-data system is safe for all time. We formulate a non-convex program to solve for the control signal at each sampling time. We decompose the non-convex program into two convex sub-problems. We illustrate the proposed approach using a numerical case study.

关键词： System dynamics conferences Sampled data systems Control systems Safety nonlinear dynamical systems complexity theory

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DeepReach: A Deep Learning Approach to High-Dimensional Reachability

DeepReach: A Deep Learning Approach to High-Dimensional Reac...

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IEEE International conference on Robotics and Automation (ICRA)

作者： Somil Bansal Claire J. Tomlin ECE University of Southern California EECS UC Berkeley

Hamilton-Jacobi (HJ) reachability analysis is an important formal verification method for guaranteeing performance and safety properties of dynamical control systems. Its advantages include compatibility with general nonlinear system dynamics, formal treatment of bounded disturbances, and the ability to deal with state and input constraints. However, it involves solving a PDE, whose computational and memory complexity scales exponentially with respect to the number of state variables, limiting its direct use to small-scale systems. We propose DeepReach, a method that leverages new developments in sinusoidal networks to develop a neural PDE solver for high-dimensional reachability problems. The computational requirements of DeepReach do not scale directly with the state dimension, but rather with the complexity of the underlying reachable tube. DeepReach achieves comparable results to the state-of-the-art reachability methods, does not require any explicit supervision for the PDE solution, can easily handle external disturbances, adversarial inputs, and system constraints, and also provides a safety controller for the system. We demonstrate DeepReach on a 9D multi-vehicle collision problem, and a 10D narrow passage problem, motivated by autonomous driving applications.

关键词： Deep learning Limiting Handheld computers Control systems Safety complexity theory nonlinear dynamical systems

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Single-Cell Topological Simplicial Analysis Reveals Higher-Order Cellular complexity

Single-Cell Topological Simplicial Analysis Reveals Higher-O...

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IEEE International conference on Bioinformatics and Biomedicine (BIBM)

作者： Baihan Lin Department of Systems Biology Columbia University Irving Medical Center New York USA

ISBN: (数字)9781665468190

ISBN: (纸本)9781665468206

The absence of a conventional association between the cell-cell cohabitation and its emergent dynamics into cliques during development has hindered our understanding of how cell populations proliferate, differentiate, and compete, i.e. the cell ecology. With the recent advancement of the single-cell RNA-sequencing (RNA-seq), we can potentially describe such a link by constructing network graphs that characterize the similarity of the gene expression profiles of the cell-specific transcriptional programs, and analyzing these graphs systematically using the summary statistics informed by the algebraic topology. We propose the single-cell topological simplicial analysis (scTSA). Applying this approach to the single-cell gene expression profiles from local networks of cells in different developmental stages with different outcomes reveals a previously unseen topology of cellular ecology. These networks contain an abundance of cliques of single-cell profiles bound into cavities that guide the emergence of more complicated habitation forms. We visualize these ecological patterns with topological simplicial architectures of these networks, compared with the null models. Benchmarked on the single-cell RNA-seq data of zebrafish embryogenesis spanning 38,731 cells, 25 cell types and 12 time steps, our approach highlights the gastrulation as the most critical stage, consistent with consensus in developmental biology. As a nonlinear, model-independent, and unsupervised framework, our approach can also be applied to tracing multi-scale cell lineage, identifying critical stages, or creating pseudo-time series. 1 1 For an extended version of this work and a systematic evaluation of our approach, please refer to [1] for more details.

关键词： Filtration Microprocessors Data visualization Computer architecture Biology Ecology complexity theory

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Continuous nonlinear State Prediction by Finite Volume Method on Logically Rectangular Grids

Continuous Nonlinear State Prediction by Finite Volume Metho...

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IEEE conference on Decision and Control

作者： J. Matoušek M. Brandner J. Duník Faculty of Applied Sciences University of West Bohemia Pilsen Czech Republic

ISBN: (纸本)9781665436601

This paper deals with the state estimation of the nonlinear stochastic models with continuous dynamics and discrete measurement. Namely, the numerical solution to the Fokker-Planck equation, representing the estimator time update, is explored. Unlike the classical approaches, which use the finite difference method and operate on a standard rectangular grid, this paper utilizes finite volume method on the logically rectangular grid. In particular, the circular grid is chosen, which better approximates an estimated conditional probability density function support and improves time update accuracy without any impact on the its computational complexity. The benefits of the solution are illustrated in a numerical example. Keywords: State estimation, Bayesian inference, nonlinear systems.

关键词： Stochastic processes Probability density function Particle measurements Mathematical models Numerical models State estimation nonlinear systems

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Nonparametric nonlinear restoring force and excitation identification with legendre polynomial and data fusion 11

Nonparametric nonlinear restoring force and excitation ident...

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11th International conference on Structural dynamics, EURODYN 2020

作者： Xu, Bin Zhao, Ye Deng, Baichuan College of Civil Engineering Huaqiao University Xiamen361021 China Key Laboratory for Intelligent Infrastructures and Monitoring of Fujian Province Huaqiao University Xiamen361021 China College of Civil Engineering Hunan University Changsha410082 China

ISBN: (纸本)9786188507203

Identification of nonlinear restoring force (NRF) and dynamic loadings provides useful information for structural damage prognosis (DP). Due to higher complexity of structural nonlinearities, it is difficult to establish an exact parametric mathematical model in prior to describe the nonlinear behavior of a structural member or a substructure under strong dynamic loadings in practice. Moreover, external dynamic loading applied on an engineering structure is usually unknown and only acceleration responses at limited degrees of freedom (DOFs) of the structure are monitored. In this study, a nonparametric NRF and excitation identification approach combining Legendre polynomial and extended Kalman filter with unknown input (EKF-UI) is proposed using limited acceleration measurements fused with displacement measurement for the purpose of eliminating drift problem. The performance of the proposed approach is illustrated via numerical simulation with a multi-degree-of-freedom (MDOF) frame structure equipped with an MR damper mimicking nonlinearity under different unknown loading scenarios. Partial acceleration measurement of the structure polluted by intensive measurement noises is employed for the identification. The parameter identification convergency procedure and the effect of initial estimation errors of structural parameters on the final identification results are investigated. Identified results demonstrate that the proposed approach is capable of identifying structural nonlinear behavior, excitation and dynamic response measurement in a nonparametric way with acceptable accuracy. © 2020 European Association for Structural dynamics. All rights reserved.

关键词： Extended Kalman filters

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Fast solution of optimal control problems with l1 cost

Fast solution of optimal control problems with l1 cost

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AAS/AIAA Astrodynamics Specialist conference, 2019

作者： Cleac’h, Simon Le Manchester, Zachary Department of Mechanical Engineering Stanford University StanfordCA94305 United States Department of Aeronautics & Astronautics Stanford University StanfordCA94305 United States

ISBN: (纸本)9780877036654

We propose a fast algorithm for solving optimal control problems with L1 control cost. Convergence to the global optimum is guaranteed for systems with linear dynamics, and the algorithm can also be used to find local optima for nonlinear dynamical systems. Our approach relies on the alternating direction method of multipliers (ADMM) and uses a fast trajectory optimization solver based on iterative LQR. The low computational complexity coupled with the fast execution of this algorithm make it suitable for implementation in flight software. © 2020, Univelt Inc. All rights reserved.

关键词： nonlinear dynamical systems

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Advances in System Identification: Theory and Applications

Advances in System Identification: Theory and Applications

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IEEE conference on Decision and Control

作者： Damien Guého Puneet Singla Manoranjan Majji Jer-Nan Juang The Pennsylvania State University PA Texas A&M University College Station TX Texas AM University College Station TX

ISBN: (纸本)9781665436601

This paper describes the main features and the most recent developments of system identification in the sense of data-driven modeling of dynamical systems. A brief summary of discrete time-invariant system identification techniques is provided, from the modern work of Gilbert, Kalman and Ho and the introduction of state-space realization, to the most recent developments of the identification of discrete time-varying and nonlinear systems. Important concepts of state-space realization, controllability and observability for linear systems are introduced along with more advanced methods to identify nonlinear dynamics. Numerical examples of varying complexity are considered to demonstrate the capability of the different approaches presented in this paper.

关键词： Linear systems Heuristic algorithms Robustness nonlinear dynamical systems System identification Trajectory Kalman filters

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