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A variable terminal set NMPC construction: application to multicopter stabilisation

A variable terminal set NMPC construction: application to mu...

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European Control conference (ECC)

作者： Gheorghe, Bogdan Stoican, Florin Prodan, Ionela Univ Politehn Bucuresti Fac Automat Control & Comp Sci Bucharest Romania Univ Grenoble Alpes Grenoble INP LCIS F-26000 Valence France Univ Grenoble Alpes Inst Engn & Management Valence France

ISBN: (纸本)9783907144084

In this paper we relax the standard NMPC (nonlinear Model Predictive Control) through a variable terminal set construction for stabilizing a multicopter system. This contribution allows us to increase the feasible domain and/or reduce the required prediction horizon length. Furthermore, to reduce the complexity of the computations we use zonotopic sets which prove instrumental due to their efficient representation. The theoretical results are validated in simulation and experiment for the stabilisation along a trajectory of a nano-multicopter's translational dynamics.

关键词： Multicopter system Trajectory tracking nonlinear Model Predictive Control (NMPC) Terminal constraints Zonotopic sets

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A Bounded Model Checking Technique for Discrete-Time nonlinear Systems 1

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20th International conference on Quantitative Evaluation of Systems (QEST)

作者： Kwon, YoungMin Kim, Eunhee Agha, Gul State Univ New York Korea Dept Comp Sci Incheon South Korea Yonsei Univ Dept Lib & Informat Sci Seoul South Korea Univ Illinois Dept Comp Sci Champaign IL USA

ISBN: (数字)9783031438356

ISBN: (纸本)9783031438349;9783031438356

Validating properties of nonlinear systems is difficult given the complexity of solving nonlinear dynamics equations. In this paper, we develop an LTL-based model checking technique to specify and validate properties of a nonlinear system. The technique can hide the difficulties in handling nonlinear difference equations, simplify the specification of properties of physical systems, and provide a high level abstraction to analyze and control nonlinear systems. We apply the proposed technique to controller synthesis problems: determining a design for a simple nonlinear control system, and finding an appropriate dosage to prescribe for drug administration.

关键词： Model checking

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nonlinear Assessment of Gait Signal complexity in Neurodegenerative Disorders 46

Nonlinear Assessment of Gait Signal Complexity in Neurodegen...

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46th Annual International conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024

作者： Udhayakumar, Radhagayathri Gopakumar, Shivapratap Rahman, Saifur Karmakar, Chandan Amrita Vishwa Vidyapeetham Center for Wireless Networks & Applications Kerala Amritapuri690525 India Amrita Vishwa Vidyapeetham The School for Sustainable Futures Kerala Amritapuri690525 India Deakin University School of Information Technology BurwoodVIC3125 Australia

ISBN: (纸本)9798350371499

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. © 2024 IEEE.

关键词： Neurodegenerative diseases

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Linear feedback control of spreading dynamics in stochastic nonlinear network models: epileptic seizures 11

Linear feedback control of spreading dynamics in stochastic ...

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11th International IEEE EMBS conference on Neural Engineering (IEEE/EMBS NER)

作者： Moosavi, S. A. Truccolo, W. Brown Univ Dept Neurosci Providence RI 02912 USA Brown Univ Carney Inst Brain Sci Providence RI 02912 USA

ISBN: (纸本)9781665462921

The development of models and approaches for controlling the spreading dynamics of epileptic seizures is an essential step towards new therapies for people with pharmacologically resistant epilepsy. Beyond resective neurosurgery, in which epileptogenic zones (EZs) are the target of surgery, closed-loop control based on intracranial electrical stimulation, applied at the very early stage of seizure evolution, has been the main alternative, e.g. the RNS system from NeuroPace (Mountain View, CA). In this approach the electrical stimulation is delivered to target brain areas after detection of seizure initiation in the EZ. Here, we examined, on model simulations, some of the closed-loop control aspects of the problem. Seizure dynamics and spread are typically modeled with highly nonlinear dynamics on complex brain networks. Despite the nonlinearity and complexity, currently available optimal feedback control approaches are mostly based on linear approximations. Alternative machine learning control approaches might require amounts of data beyond what is commonly available in the intended application. We thus examined how standard linear feedback control approaches perform when applied to nonlinear models of neural dynamics of seizure generation and spread. In particular, we considered patient-specific epileptor network models for seizure onset and spread. The models incorporate network connectivity derived from (diffusion MRI) white-matter tractography, have been shown to capture the qualitative dynamics of epileptic seizures and can be fit to patient data. For control, we considered simple linear quadratic Gaussian (LQG) regulators. The LQG control was based on a discrete-time state-space model derived from the linearization of the patient-specific epileptor network model around a stable fixed point in the regime of preictal dynamics. We show in simulations that LQG regulators acting on the EZ node during the initial seizure period tend to be unstable. The LQG solution

关键词： Resistance Regulators Linear approximation Stochastic processes Electrical stimulation Brain modeling Feedback control

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Applying Joint and Dual State and Parameter Estimation Using Derivative-Free Kalman Filter for a Switched nonlinear System

Applying Joint and Dual State and Parameter Estimation Using...

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International conference on Robotics, Control, Automation and Artificial Intelligence, RCAAI 2023

作者： Elenchezhiyan, M. Thirunavukkarasu, I. Kumar, E. Govinda Department of Electrical and Electronics Engineering MVJ College of Engineering Karnataka Bangalore560067 India Department of Instrumentation and Control Engineering Manipal Institute of Technology Manipal Academy of Higher Education Karnataka Manipal576104 India Department of Electrical and Electronics Engineering PSG Institute of Technology and Applied Research Tamil Nadu Coimbatore641062 India

ISBN: (纸本)9789819746491

In a hybrid system, the continuous and discrete modes are interaction with each other which results that the system states are operated in nonlinear dynamics and complexity of the system is increased. When the system dynamics are subjected to state and measurement uncertainty with parametric uncertainty, online parameter estimation of such a hybrid system is a difficult problem. Estimation of hybrid system states and parameters is a critical aspect in fault classification and identification, as well as fault tolerant control and adaptive control applications. Dual unscented Kalman filter (DUKF) and joint unscented Kalman filter (JUKF) are used to estimate state and parameters of the system based on dual state and parameter estimation approaches. The simulations were carried out for the performance evaluation of JUKF and DUKF on benchmark system, namely switched mode continuous stirred tank reactor (CSTR). According to simulation data, DUKF outperforms JUKF for switched nonlinear systems, and choice of recommendation is DUKF for simultaneous state and parameter estimation of switched nonlinear hybrid systems. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Kalman filters

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A Hybrid FNS Generator for Human Trunk Posture Control with Incomplete Knowledge of Neuromusculoskeletal dynamics

A Hybrid FNS Generator for Human Trunk Posture Control with ...

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IEEE/RSJ International conference on Intelligent Robots and Systems (IROS)

作者： Bao, Xuefeng Friederich, Aidan R. Triolo, Ronald J. Audu, Musa L. Univ Wisconsin Milwaukee Coll Engn & Appl Sci Milwaukee WI 53211 USA Case Western Reserve Univ Dept Biomed Engn Cleveland OH 44106 USA US Dept Vet Affairs Adv Platform Technol Ctr Cleveland OH 44106 USA

ISBN: (纸本)9781665491907

The trunk movements of an individual paralyzed by spinal cord injury (SCI) can be restored by Functional Neuromuscular Stimulation (FNS), a technique that applies low-level current to motor nerves to activate the muscles generating torques, and thus, produce trunk motions. FNS can be modulated to control trunk movements. However, a stabilizing modulation policy (i.e., control law) is difficult to derive due to the complexity of neuromusculoskeletal dynamics, which consist of skeletal dynamics (i.e., multi-joint rigid body dynamics) and neuromuscular dynamics (i.e., a highly nonlinear, non-autonomous, and input redundant dynamics). Therefore, an FNS-based control method that can stabilize the trunk without knowing the accurate skeletal and neuromuscular dynamics is desired. This work proposed an FNS generator, which consists of a robust nonlinear controller (RNC) that provides stabilizing torque command and an artificial neural network (ANN)based torque-to-activation (T-A) map to ensure that the muscle generates the stabilizing torque to the skeleton. Due to the robustness and learning capability of this control framework, full knowledge of the trunk neuromusculoskeletal dynamics is not required. The proposed control framework has been tested in a simulation environment where an anatomically realistic 3D musculoskeletal model of the human trunk was manipulated to follow a time-varying reference that moves in the anterior-posterior and medial-lateral directions. From the results, it can be seen that the trunk motion converges to a satisfactory trajectory while the ANN is being updated. The results suggest the potential of this control framework for trunk tracking tasks in a clinical application.

关键词： Torque

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nonlinear PID Control for Automatic Docking of a Large Container Ship in Confined Waters Under the Influence of Wind and Currents 15

Nonlinear PID Control for Automatic Docking of a Large Conta...

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15th IFAC conference on Control Applications in Marine Systems, Robotics and Vehicles (CAMS)

作者： Lexau, Simon J. N. Lekkas, Anastasios M. Breivik, Morten Norwegian Univ Sci & Technol NTNU Dept Engn Cybernet NO-7491 Trondheim Norway Ctr Res Based Innovat SFI AutoShip Autonomous Shi Trondheim Norway

This study addresses the challenges of maneuvering a large container ship in confined waters under the influence of wind and currents. The proposed guidance, navigation, and control system presents a novel combination of modeling methodologies, control allocation techniques, and nonlinear control systems theory. We consider a docking scenario through a simulation of a realistic, narrow harbor accommodating area-specific currents and global wind forces. Control allocation is solved by utilizing detailed models of the actuators and hydrodynamics in a mixed-integer-like solution for optimal thrust allocation, and an inverse mapping to the control inputs. Furthermore, our approach introduces a modified Wageningen B-Series model, that is capable of modeling propellers with negative pitch dynamics. The complexity of safely docking in environments like the Antwerp harbor, where wind and currents pose significant risks, is tackled using a nonlinear PID control system integrated with Line-Of-Sight (LOS) guidance. This enables precise maneuvering of a fully actuated Roll-On/Roll-Of vessel to its docking position and orientation. Given that few studies on automated docking holistically address the intricate challenges of complex harbor environments and the concurrent impact of multiple external forces, our work proposes a comprehensive solution based on an integrated combination of guidance, navigation, and control systems. 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： Automated docking harbor navigation marine motion control nonlinear PID control thrust allocation actuator dynamics

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Analysis of the nonlinear behaviour of rainfall over Kerala 2

Analysis of the nonlinear behaviour of rainfall over Kerala

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2nd International conference on Current Trends in Physics and Photonics, ICCTPP 2024

作者： Parvathy, M. Ashok, Parvathi Madhu, Dhanya Department of Physics Amrita Vishwa Vidyapeetham Amritapuri India

ISBN: (纸本)9781510682948

In the current era of climate change, variability in rainfall patterns is an important research topic. This is significant in the context of extreme weather events and disasters, as well as in the context of the availability of usable water for communities. The current study presents an investigation into the nonlinear characteristics of rainfall over Kerala, India. The majority of rainfall received over Kerala is during the summer monsoon season (from June to September). However, a good amount of rainfall is obtained during the winter monsoon which is from October to December, as well as during the pre-monsoon season. Here the technique of correlation dimension is utilized to study nonlinear systems exhibiting intricate interdependencies over time. By calculating a value known as correlation dimension, if it is increasing with a parameter called embedding dimension, it would reveal the occurrence of complexity and unpredictability in the rainfall patterns. Otherwise, if correlation dimension stabilizes beyond a certain point, it would suggest that the rainfall dynamics settle into a more stable and potentially predictable pattern. The findings of this analysis revealed that if the embedding dimension increases, the correlation dimension also increases, indicating the existence of complexity and unpredictability in the rainfall pattern. © 2024 SPIE.

关键词： Rain

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COMPUTATION OF ISOLATED PERIODIC SOLUTIONS FOR FORCED RESPONSE BLADE-TIP/CASING CONTACT PROBLEMS

COMPUTATION OF ISOLATED PERIODIC SOLUTIONS FOR FORCED RESPON...

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ASME Turbomachinery Technical conference and Exposition (Turbo Expo) on Collaborate, Innovate and Empower - Propulsion and Power for a Sustainable Future

作者： Vadcard, Thibaut Thouverez, Fabrice Batailly, Alain Ecole Cent Lyon Lab Tribol & Dynam Syst CNRS UMR 5513 36 Ave Guy Collongue F-69134 Ecully France Ecole Polytech Montreal Dept Genie Mecan POB 6079Succ Ctr Ville Montreal PQ H3C 3A7 Canada

ISBN: (纸本)9780791887066

This article introduces a numerical procedure dedicated to the identification of isolated branches of solutions for nonlinear mechanical systems. It is here applied to a fan blade subject to rubbing interactions and harmonic forcing. Both contact, which is initiated by means of the harmonic forcing, and dry friction are accounted for. The presented procedure relies on the computation of the system's nonlinear normal modes and their analysis through the application of an energy principle derived from the Melnikov function. The dynamic Lagrangian frequency-time strategy associated with the harmonic balance method (DLFT-HBM) is used to predict the blade's dynamics response as well as to compute the autonomous nonlinear normal modes. The open industrial fan blade NASA rotor 67 is employed in order to avoid confidentiality issues and to promote the reproducibility of the presented results. Previous publications have underlined the complexity of NASA rotor 67's dynamics response as it undergoes structural contacts, thus making it an ideal benchmark blade when searching for isolated solutions. The application of the presented procedure considering a varying amplitude of the harmonic forcing allows to predict isolated branches of solutions featuring nonlinear resonances. With the use of the Melnikov energy principle, nonlinear modal interactions are shown to be responsible for the separation of branches of solutions from the main response curve. In the end, the application of the presented procedure on an industrial blade model with contact interactions demonstrates it is both industry-ready and applicable to highly nonlinear mechanical systems.

关键词： Harmonic Balance Method rotor/stator interaction fan blade nonlinear normal modes isola Melnikov energy principle

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nonlinear Dynamic Analysis of Seafloor Pressure Time Series with and without Internal Waves

Nonlinear Dynamic Analysis of Seafloor Pressure Time Series ...

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2023 International conference on Computational and Mathematical Methods in Engineering, CMME 2023

作者： Zhang, Sai He, Huizi School of Physics and Electronic Engineering Jiangsu University Zhenjiang212013 China School of Mathematical Sciences Jiangsu University Zhenjiang212013 China

Ocean internal wave as a nonlinear process oscillates within ocean interior rather than the surface. Internal waves have significant influences on the transport of material, energy and even global climate. The generation, transmission and attenuation of internal wave play a significant role in the ocean dynamics owing to the exchange of the energy within each process. In this paper, reduced complexity of seafloor pressure time series induced by internal wave in the southern Taiwan bank has been investigated using nonlinear dynamic analysis. Cao method has been used to distinguish between the pressure signal with internal wave and the random signal without internal wave. The reconstructed phase spaces and correlation dimensions of the time series with and without internal wave are compared. Internal wave leads the seafloor pressure time series to produce a more regular phase space reconstruction and more low dimensional dynamics. Our study suggests that nonlinear dynamic analysis could be a valuable and promising method in real-time ocean internal wave detection. © Published under licence by IOP Publishing Ltd.

关键词： Time series

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