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AOA-constrained adaptive fault-tolerant control of hypersonic flight vehicles with low computational complexity 41

AOA-constrained adaptive fault-tolerant control of hypersoni...

引用

第41届中国控制会议

作者： Haochun Miao Yajun Li Gen Wang Jiang Chang Jinping Li Xi'an Modern Control Technology Research Institute

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In this paper,the longitudinal control problem of hypersonic flight vehicles(HFVs) with the angle of attack(AOA)constraint,external disturbances,unknown time-varying actuator fault and dead-zone is ***,by applying nonlinear state transformation technique,the original model is converted into a new pure-feedback form,and the AOA constraint can be guaranteed by ensuring the boundness of the transformed ***,a novel fault-tolerance fuzzy adaptive controller is *** logic systems are introduced to approximate the unknown nonlinear dynamics with only one learning parameter being updated online,which leads to a low computational ***,the unknown actuator dynamics including unknown time-varying actuator fault and dead-zone are well addressed by constructing a bound-estimation *** stability of the closed-loop system is proved via Lyapunov method,and the effectiveness of the proposed control scheme is demonstrated with numerical simulations.

关键词： Hypersonic flight vehicle(HFV) Angle of attack(AOA) constraint unknown time-varying faults dead-zones low computational complexity bound-estimation approach

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Multi-hierarchical Dispersion Entropy: A Novel nonlinear Measurement Approach for Fault Diagnosis of Rolling Bearing 15

Multi-hierarchical Dispersion Entropy: A Novel Nonlinear Mea...

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15th IEEE Global Reliability and Prognostics and Health Management conference, PHM-Beijing 2024

作者： Song, Jiaqiu Yao, Chong Zou, Xianyu Song, Enzhe Ke, Yun Yantai Research Institute Harbin Engineering University Yantai China

ISBN: (纸本)9798350354010

Hierarchical dispersion entropy (HDisE)is an effective way to measure the dynamics of nonlinear signals. However, HDisE only extracts features at a single level, resulting in the loss of a large amount of deep information. In addition, HDisE is very sensitive to the length of time series. As the number of decomposition layers increases, the length of the original sequence decreases dramatically, which may lead to instability and inaccuracy of entropy estimation when dealing with short-term sequences. To solve these limitations, this paper proposes a new time series complexity measurement method, multi-hierarchical dispersion entropy (MHDisE), for feature extraction of signals. MHDisE not only enriches the hierarchical nature of information by integrating the high-frequency and low-frequency features of multiple decomposition levels, but also improves the stability and accuracy of short-time series entropy estimation. Based on the advantages of MHDisE, a fault diagnosis method for rolling bearing combining MHDisE and Support Vector Machin optimized by Spider Wasp Optimizer (SWO-SVM) was proposed. Finally, the CRWU public dataset and experimental data of rolling bearing are used for verification. The results show that the proposed method can effectively extract feature information, improve the fault identification accuracy and stability, and show significant advantages in processing short-term sequences. © 2024 IEEE.

关键词： Time series

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Learning Model Predictive Control for Quadrotors 39

Learning Model Predictive Control for Quadrotors

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IEEE International conference on Robotics and Automation (ICRA)

作者： Li, Guanrui Tunchez, Alex Loianno, Giuseppe NYU Tandon Sch Engn Brooklyn NY 11201 USA

ISBN: (纸本)9781728196817

Aerial robots can enhance their safe and agile navigation in complex and cluttered environments by efficiently exploiting the information collected during a given task. In this paper, we address the learning model predictive control problem for quadrotors. We design a learning receding-horizon nonlinear control strategy directly formulated on the system nonlinear manifold configuration space SO(3)xR(3). The proposed approach exploits past successful task iterations to improve the system performance over time while respecting system dynamics and actuator constraints. We further relax its computational complexity making it compatible with real-time quadrotor control requirements. We show the effectiveness of the proposed approach in learning a minimum time control task, respecting dynamics, actuators, and environment constraints. Several experiments in simulation and real-world set-up validate the proposed approach.

关键词： Manifolds Actuators System dynamics System performance Aerospace electronics Real-time systems Trajectory

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An Efficient Accelerator for nonlinear Model Predictive Control 34

An Efficient Accelerator for Nonlinear Model Predictive Cont...

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34th IEEE International conference on Application-Specific Systems, Architectures and Processors (ASAP)

作者： Pertuz, Sergio A. Podlubne, Ariel Goehringer, Diana Tech Univ Dresden Chair Adapt Dynam Syst Dresden Germany Tech Univ Dresden Ctr Tactile Internet Human In The Loop CeTI Dresden Germany

ISBN: (纸本)9798350346855

The computational complexity of nonlinear Model Predictive Control (NMPC) often hinders their application to cyber-physical systems with fast dynamics, such as mobile robots or Unmanned Aerial Vehicles. This complexity overhead comes from the control algorithm's backbone, an iterative solver that must ensure convergence and often takes the form of a highly structured convex Quadratic Program (QP). Such overhead could be overcome using specialized computer architectures. Field Programmable Gate Arrays are good candidates for making hardware accelerators that comply with the real-time constraints of fast-dynamic cyber-physical systems. Nevertheless, QP-solvers have been demonstrated to be complex to implement as a hardware accelerator. With this in mind, the present paper proposes a novel accelerator architecture that uses Knowledge-based Particle Swarm Optimization (PSO) as a solver while exploring its parallel nature. PSO is a stochastic global optimization algorithm that creates a fast and precise solution for NMPC. The proposed strategy in this papergrants system control stability for short sampling frequencies and long prediction horizons. It can also meet real-time constraints while achieving low hardware consumption. Additionally, it is generalized, so it can potentially be adapted to any application and is compatible with the Robot Operating System (ROS). The architecture is tested with two applications: an inverted pendulum swing-up procedure and a quadrotor drone with control and state constraints. Following, we analyze the accelerator performance and highlight our solution's advantages to other works in the literature. Namely, our architecture solves more complex problems with a greater dimension and longer horizon while using similar resources. The proposed solution also has good computational performance (29ms and 11ms) for both the quadrotor and inverted pendulum, respectively, while achieving the real-time requirements (50ms and 100ms, respectively). Pa

关键词： Memory-based particle swarm optimization HW/SW co-design nonlinear model predictive control robotics

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Cardiac Anomaly Detection using Embedded Attractors Reconstructed from Multichannel ECG 9

Cardiac Anomaly Detection using Embedded Attractors Reconstr...

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9th International conference on Biomedical and Bioinformatics Engineering (ICBBE)

作者： Purkayastha, Basab Bijoy Hazarika, Anakhi Thomas, K. Amal Poddar, Soumyajit Indian Inst Technol Guwahati Gauhati India

ISBN: (纸本)9781450397223

The degree of complexity associated with the dynamics of the human heart is different for different categories of cardiac abnormalities. A quantitative measure of the complexities associated with cardiac dynamics can be obtained with a nonlinear study like a Multifractal analysis of the electrocardiogram signals. Here in this work, we have modeled the heart as a nonlinear dynamical system and obtained its phase space structure or embedded attractor reconstructed out of the ECG time series corresponding to four channels. Then, studied the multifractal behavior of the embedded attractor in order to quantify the degree of complexities associated with the dynamics of the heart. In particular, we have derived a few parameters out of the multifractal singularity spectrum and used them as a discriminative measure between various kinds of cardiac conditions. We have demonstrated a gradient boosting-based parametric classification model to discriminate between different kinds of arrhythmias and normal sinus rhythms. This work achieves considerably high accuracy in classifying different variants of cardiac disorders when trained with the parameters obtained from the multifractal singularity spectrum associated with the embedded attractor reconstructed out of the ECG time series.

关键词： nonlinear dynamical system Multifractal singularity spectrum Cardiac dynamics Phase space structure Embedded attractor Gradient boosting algorithm

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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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CLEO: Science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of conference on Lasers and Electro-Optics

作者： Perron, Nicolas Fischer, Bennet Chemnitz, Mario Zhu, Yi Roztocki, Piotr MacLellan, Benjamin Di Lauro, Luigi Aadhi, A. Rimoldi, Cristina Falk, Tiago H. Morandotti, Roberto Institut National de la recherche scientifique 1650 Bd Lionel-Boulet VarennesQCJ3X 1P7 Canada Leibniz Institute of Photonic Technology Albert-Einstein-Straße 9 Jena07745 Germany Ki3 Photonics Technologies 2547 Rue Sicard MontrealQCH1V 2Y8 Canada Dipartimento di Elettronica e Telecomunicazioni Politecnico di Torino Corso Duca degli Abruzzi 24 Torino10129 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

关键词： Single mode fibers

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EFFICIENT AND ACCURATE REAL-TIME SIMULATIONS OF COUPLED MECHANICAL SYSTEMS USING THE UNIVERSAL HYDRAULIC SURROGATE

EFFICIENT AND ACCURATE REAL-TIME SIMULATIONS OF COUPLED MECH...

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ASME International Design Engineering Technical conferences / 43rd Annual Computers and Information in Engineering conference (IDETC-CIE) / 19th International conference on Multibody Systems, nonlinear dynamics, and Control (MSNDC)

作者： Khadim, Qasim Kurvinen, Emil Mikkola, Aki Orzechowski, Grzegorz Univ Oulu Oulu Finland LUT Univ Lappeenranta Finland

ISBN: (纸本)9780791887387

The real-time simulation of coupled multibody and hydraulics systems can be challenging due to the complexity, accuracy, and non-linear behavior of the modeling methods and the computational requirements. To this end, this study introduces the universal hydraulic surrogate approach instead of the conventional lumped fluid theory to solve the dynamics of hydraulically driven systems. The universal hydraulic surrogate is prepared with an approximated force model and trained with the behaviors of lumped fluid theory using the Covariance Matrix Adaption Evolutionary Strategy (CMA-ES). The universal hydraulic surrogate is used to solve the dynamics of the hydraulically actuated four-bar mechanism. The performance of the universal hydraulic surrogate is compared with the lumped fluid theory in terms of numerical accuracy and computational efficiency. The maximum percent normalized root mean square error (PN-RMSE) in the states of the four-bar mechanism using a simple force model compared to the lumped fluid theory is 2.06 %. The simulation with the universal hydraulic surrogate approach is up to 45 times faster than the lumped fluid theory in the studied case. The proposed study will enhance the computational efficiency of the coupled multibody systems and enhances their use in artificial intelligence, neural networks, and machine learning applications for complicated industrial systems.

关键词： Hydraulic universal surrogate Hydraulics Multi-body system dynamics Real-time simulation CMA-ES

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Boundary Control for Suppressing Chaotic Response to Dynamic Hydrogen Blending in a Gas Pipeline 7

Boundary Control for Suppressing Chaotic Response to Dynamic...

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7th IFAC conference on Analysis and Control of nonlinear dynamics and Chaos (ACNDC)

作者： Baker, Luke S. Zlotnik, Anatoly Los Alamos Natl Lab Div Theoret Ctr Nonlinear Studies Los Alamos NM 87544 USA Los Alamos Natl Lab Appl Math & Plasma Phys Grp Los Alamos NM USA

It is known that periodic forcing of nonlinear flows can result in a chaotic response under certain conditions. Such non-periodic and chaotic solutions have been observed in simulations of heterogeneous gas flow in a pipeline with periodic, time-varying boundary conditions. In this paper, we examine a proportional feedback law for boundary control of a parabolic partial differential equation system that represents the flow of two gases through a pipe. We demonstrate that periodic variation of the mass fraction of the lighter gas at the pipe inlet can result in the chaotic propagation of gas pressure waves, and show that appropriate flow control can suppress this response. We examine phase space solutions for the single pipe system subject to boundary control, and use numerical experiments to characterize conditions for the controller gain to suppress chaos. Copyright (C) 2024 The Authors. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0/)

关键词： Control of bifurcation and chaos Control of renewable energy resources Energy control in transportation Output feedback control Control of fluid flows and fluids-structures interactions

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A deep learning-based approach for hybrid nonlinear systems dynamics approximation 17

A deep learning-based approach for hybrid nonlinear systems ...

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17th International conference on Emerging Technologies (ICET)

作者： Bastos, Vasco Palma, Luis Cardoso, Alberto Gil, Paulo NOVA Sch Sci & Technol Dept Elect & Comp Engn Caparica Portugal NOVA Sch Sci & Technol Dept Elect & Comp Engn CTS UNINOVA Caparica Portugal Univ Coimbra Fac Sci & Techonol Dept Informat Engn CISUC Coimbra Portugal Univ Coimbra CISUC Coimbra Portugal

ISBN: (纸本)9781665459921

An increasingly important class of nonlinear systems includes the nonaffine hybrid systems, in particular those in which the underlying dynamics explicitly depends on a switching signal. When the inherent complexity is treatable and the phenomena governing the system dynamics are known an implicit model can be derived to describe its behaviour over time. When these assumptions are not met the system dynamics can still be approximated by regression-based techniques, provided datasets comprising input/output signals collected from the system are available. One approach relies on intelligent computing-based frameworks, in which artificial neural networks stand out as a class of universal approximation models. This paper, proposes a new approach for capturing nonlinear hybrid system dynamics based on 1D spatio-temporal convolutional neural networks, in which the inputs are represented by regressors and structural configuration parameters. The proposed deep neural network architecture is compared against a shallow multilayer layer perceptron framework, in which each structural configuration is independently approximated. Experimental results point out to the superiority of the 1D spatio-temporal convolutional network.

关键词： nonlinear systems hybrid systems data driven modelling deep learning spatio-temporal convolutional neural networks

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nonlinear dynamics Analysis for a Model-Reduced Rotor System with nonlinear Galerkin Method 10th

Nonlinear Dynamics Analysis for a Model-Reduced Rotor System...

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10th International conference on Wave Mechanics and Vibrations, WMVC 2022

作者： Xu, Yue Huang, Jin Wang, Yuefang Li, Cong Wei, Xuemin Aviation Industry Corporation of China Aerodynamic Research Institute Harbin150001 China Aviation Key Laboratory of Aerodynamics for Low Speed and High Renolds Number Harbin150001 China Dalian University of Technology Dalian116024 China

ISBN: (纸本)9783031157578

Rotor-bearing systems are important components of aircraft engines of which vibration response must be analyzed under normal and disturbed conditions. Due to the existence of strong nonlinearity from squeeze film dampers and ball bearings, it is often very time consuming to evaluate the vibration of the rotor excited by unbalanced mass, which makes efficient and reliable modeling reduction is pivotal to rotordynamic analyses. In this paper, the nonlinear vibration and dynamical behavior of a twin-spool rotor assembly supported on bearings and squeeze film dampers with centralizing springs is investigated through the post-processed nonlinear Galerkin method. The rotor is spatially discretized with the finite element method, and the nonlinear governing equation of motion of the system is derived. To reduce the scale of the full-sized model, the post-processed nonlinear Galerkin method is employed to project the original system onto a low-dimensional sub-manifold with a relatively smaller number of degrees of freedom. The convergence of the nonlinear Galerkin method is verified through comparisons energy between the original and the reduced systems. The optimal choice of the number of master modes is determined to form the reduced model for nonlinear vibration analyses. Through the NGM the vibration of the system is solved, and the amplitude-frequency response, bifurcation and the Poincaré map are obtained to demonstrate the complexity in the rotor dynamics. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Galerkin methods

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