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Quasi-LPV Interconnected Observer Design for Full Vehicle dynamics Estimation With Hardware Experiments

IEEE-ASME TRANSACTIONS ON MECHATRONICS 2021年第4期26卷 1763-1772页

作者： Fouka, Majda Sentouh, Chouki Popieul, Jean-Christophe Univ Polytech Hauts de France CNRS UMR 8201 Lab Automat Mecan & Informat Ind & Humaines F-59313 Valenciennes France INSA Hauts de France F-59313 Valenciennes France

Safety systems claim an in-depth study of vehicle motion and tire-ground interaction for the design of a partially automated driving vehicle. This article addresses the quasi-linear parameter-varying Luenberger interconnected fuzzy observer to estimate both longitudinal and lateral vehicle dynamics simultaneously. In a different manner from the commonplace state of the art of vehicle state observers that consider single driving motion, the proposed approach considers the coupled dynamics with the tire-ground interaction to estimate the most important states while reducing the complexity related to the observability and conservatism. This consideration leads to a nonlinear parameter-dependent interconnected model with unmeasured premise variables. Then, the Takagi-Sugeno fuzzy form is considered to deal with the nonlinearities of the vehicle longitudinal and lateral speeds and the slip velocities as well as the steering angle. The concept of "input to state stability" is exploited using fuzzy nonquadratic Lyapunov stability arguments to guarantee the boundness of the estimation errors. A refinement has been proposed through the so-called Polya's theorem aiming to further reduce the conservativeness. Finally, performances and effectiveness of the suggested approach are evaluated through hardware experiments performed with the well-known Sherpa dynamic car simulator under real-world driving situations.

关键词： Input to state stability (ISS) longitudinal and lateral dynamics quasi-linear parameter-varying interconnected observer vehicle safety

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A Predictive Trading Framework Using Functional Linear Discriminant Analysis

A Predictive Trading Framework Using Functional Linear Discr...

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IEEE Annual Computing and Communication Workshop and conference (CCWC)

作者： Declan P. Mallamo Helene P. Hoang Michael H. Azarian Michael Pecht Center for Advanced Life Cycle Engineering (CALCE) University of Maryland College Park MD Costello College of Business George Mason University Fairfax VA

ISBN: (数字)9798331507695

ISBN: (纸本)9798331507701

Predicting stock movements remains a significant challenge due to the volatility, complexity, and nonlinear dynamics of financial markets. Accurate forecasting is essential for optimizing trading strategies and achieving financial gains. However, existing models often struggle to integrate multivariate functional patterns, effectively balance the bias-variance tradeoff, and maintain computational efficiency for real-time trading. This study proposes a novel feature extraction framework that combines functional Principal Component Analysis (fPCA) and functional Linear Discriminant Analysis (fLDA). The approach captures the intrinsic variability and continuous nature of financial time-series data, transforming it into structured and interpretable representations for decision-making. A Mahalanobis distance-based decision function is applied within the discriminant space to classify buy, hold, and sell signals, leveraging clusters formed by the functional discriminant directions. The framework's performance is validated through simulated trading strategies on historical stock data, with evaluations based on portfolio growth and predictive accuracy. Results demonstrate the method's effectiveness in capturing market dynamics and providing actionable insights for financial analytics.

关键词： Reactive power Accuracy Profitability Transforms Vectors Real-time systems Linear discriminant analysis nonlinear dynamical systems Portfolios Principal component analysis

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On the PID-structured model-free adaptive control: a comparison of different approaches

On the PID-structured model-free adaptive control: a compari...

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European Control conference (ECC)

作者： Soheil Salighe Dirk Söffker Chair of Dynamics and Control University of Duisburg-Essen Duisburg

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

In this paper, a PID-structured controller with time-varying gains is introduced using model-free adaptive control (MFAC) methodologies. The MFAC uses a control-oriented linearized data-model to produce control input only using input/output (I/O) data of the system. One of the data-model structures is full form dynamic linearization (FFDL), which considers the effect of a time-window of previous I/O in the linearized model. A specific I/O window length in FFDL leads to a MFAC controller whose structure is similar to discrete multivariable type PID. By manipulating the control objective function, however, similar PID-structured (PIDs) controller can be realized using a less sophisticated data-model exploiting the compact form dynamic linearization (CFDL) technique. The complexity of the new PIDsMFAC-CFDL and the one realized by MFAC-FFDL are compared in terms of the total number of adjustable parameters when dealing with MIMO systems. The controllers are also applied on a simulated model of a nonlinear MIMO three-tank system (3TS). The results demonstrate that the number of parameters to be tuned can decrease heavily by considering the new approach. In addition, PIDsMFAC-CFDL delivers a smooth transition toward the given reference with less error and less consumed energy.

关键词： Adaptation models Europe Linear programming Control systems nonlinear dynamical systems Error correction codes complexity theory

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Supercapacitor Voltage Prediction Using a Dynamic Fractional Order Parameter Optimization

Supercapacitor Voltage Prediction Using a Dynamic Fractional...

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International conference on Power Electronic Drives

作者： Shifa H Rahman Jagadanand G Shreelakshmi M P Dept. of Electrical Engg. NIT Calicut Kozhikode India

ISBN: (数字)9798350372472

ISBN: (纸本)9798350372489

The accuracy of the model for the analysis of supercapacitor dynamics is critical for its application. Traditional models often fail to capture supercapacitor's nonlinear dynamics and complex behaviors, such as charge redistribution and leakage currents. This study addresses these limitations by incorporating real-time parameter estimation during various operational phases, including the charging, discharging, and rest periods. The experimental setup included multiple SC cells and precise measurement tools to capture the terminal voltage under constant-current conditions. By utilizing only 10each stage, the model parameters were optimized, and accurate voltage predictions for the subsequent stages were achieved. The proposed methodology significantly reduces computational complexity while maintaining high fidelity in SC management, making it suitable for electric vehicles and renewable energy systems applications.

关键词： Renewable energy sources Accuracy Voltage measurement Computational modeling Supercapacitors Predictive models Real-time systems Reliability Vehicle dynamics Integrated circuit modeling

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Set-Valued State Estimation for nonlinear Systems Using Hybrid Zonotopes

Set-Valued State Estimation for Nonlinear Systems Using Hybr...

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IEEE conference on Decision and Control

作者： Jacob A. Siefert Andrew F. Thompson Jonah J. Glunt Herschel C. Pangborn Department of Mechanical Engineering The Pennsylvania State University University Park PA USA

This paper proposes a method for set-valued state estimation of nonlinear, discrete-time systems. This is achieved by combining graphs of functions representing system dynamics and measurements with the hybrid zonotope set representation that can efficiently represent nonconvex and disjoint sets. Tight over-approximations of complex nonlinear functions are efficiently produced by leveraging special ordered sets and neural networks, which enable computation of set-valued state estimates that grow linearly in memory complexity with time. A numerical example demonstrates significant reduction of conservatism in the set-valued state estimates using the proposed method as compared to an idealized convex approach.

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Identifying Complex dynamics of Power Grid Frequency 24

Identifying Complex Dynamics of Power Grid Frequency

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Proceedings of the 15th ACM International conference on Future and Sustainable Energy Systems

作者： Xinyi Wen Ulrich Oberhofer Leonardo Rydin Gorjão G.Cigdem Yalcin Veit Hagenmeyer Benjamin Schäfer Karlsruhe Institute of Technology Germany Norwegian University of Life Sciences Norway Istanbul University Turkiye

ISBN: (纸本)9798400704802

The energy system is undergoing rapid changes to integrate a growing number of intermittent renewable generators and facilitate the broader transition toward sustainability. This increases the complexity of the energy system in many aspects, including the power grid and its dynamics. As millions of consumers and thousands of (volatile) generators are connected to the same synchronous grid, no straightforward bottom-up models describing the dynamics are available on a continental scale comprising all of these necessary details. Hence, to identify this unknown power grid dynamics, we propose to leverage the Sparse Identification of nonlinear dynamics (SINDy) method. Thereby, we unveil the governing equations underlying the dynamical system directly from data measurements. Investigating the power grids of Iceland, Ireland and the Balearic islands as sample systems, we observe structurally similar dynamics with remarkable differences in both quantitative and qualitative behavior. Overall, we demonstrate how complex, i.e. non-linear, noisy, and time-dependent, dynamics can be identified straightforwardly.

关键词： Power grid frequency noisy dynamics sparse identification of non-linear dynamics (SINDy) symbolic regression time-dependent dynamics

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On Some General Methods for Mathematical Modeling of the dynamics of Manipulators with Parallel Kinematics

On Some General Methods for Mathematical Modeling of the Dyn...

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2022 International conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2022

作者： Krasinskiy, Aleksandr Ya Dept. of Physical and Mathem. Disciplines Moscow Russia Moscow Aviation Institute National Research University Dept. of Computer Modeling and Probability Theory Moscow Russia

ISBN: (纸本)9781665483698

The level of development of technology for obtaining and processing measurement information, power electronics and actuators allows the use of the results of mathematical control theory with incomplete information in modern mechatronic systems. These results create the possibility of minimizing interference in the behavior of the object by minimizing the amount of measurement information and the number of actuators involved. A necessary condition for the realization of this possibility is the presence of an adequate nonlinear mathematical model of the control object. The development of methods for creating such models is hampered not so much by the technical complexity of the system under study, but by the fact that fundamentally new problems often arise in the study of a specific actually functioning device, which have never been encountered before in the relevant theory. Their solution requires research by theoretical specialists on the further development of the complex application of areas of analytical mechanics, nonlinear theory of stability, mathematical control theory with incomplete information, information technologies, etc., which were previously quite distant from each other. Rigorous justification of methods for obtaining such mathematical models, is based on complex sections of mathematics, mechanics and control theory, which have never been included in the curricula of standard engineering education. However, in our opinion, a significant expansion of the practical application of the latest results in engineering practice is possible due to such a presentation of algorithms for their qualified application, which does not require a complete understanding of all the abstract-theoretical foundations of their justification. © 2022 IEEE.

关键词： Control theory

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Geometric Tracking Control of A Quadrotor with Tilted Propellers

Geometric Tracking Control of A Quadrotor with Tilted Propel...

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IEEE/ASME (AIM) International conference on Advanced Intelligent Mechatronics

作者： Shangkun Zhong Xinyu Cai Zhao Ma Yibo Ding Shaohui Foong Aviation Key Laboratory of Science and Technology on Flight Control AVIC Xi’an Automatic Flight Control Research Institute Xi’an Engineering Product Development (EPD) Pillar Singapore University of Technology and Design (SUTD) Singapore School of Astronautics Northwestern Polytechnical University Xi’an

ISBN: (数字)9798350355369

ISBN: (纸本)9798350355376

This paper considers the control of the quadrotors with the unaligned thrust. Unlike the conventional quadrotor, the translational dynamics of these vehicles are sophisticatedly correlated with the rotational dynamics. This arises because the bearing of the total thrust in the body frame varies, in contrast to the unidirectional total thrust of regular quadrotors. This complexity poses a significant challenge to the control design for the quadrotor with the unaligned propellers. To address the challenge, we propose a geometric tracking control method that compensates for the thrust direction variation by incorporating additional vehicle inclination. The nonlinear tracking controller is characterized by defining the tracking error on the special Euclidean group SE(3). Through Lyapunov analysis, we proved almost globally exponential stability of zero equilibrium of the error dynamics. Simulation results illustrate the success of the proposed tracking control in achieving spiral trajectory tracking and recovering from the initial upside-down orientation for quadrotors with distinct propeller alignment configurations.

关键词： Spirals Mechatronics Propellers Trajectory tracking Simulation dynamics Stability analysis

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nonlinear Method to Assess Autonomic Modulation During Controlled Breathing

Nonlinear Method to Assess Autonomic Modulation During Contr...

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conference of the European Study Group on Cardiovascular Oscillations

作者： Agnieszka Uryga Monika Najdek Mikołaj Najda Cyprian Mataczy´Ski Teodor Buchner Wrocław University of Science and Technology Wroclaw Poland Warsaw University of Technology Warsaw Poland

ISBN: (数字)9798350392050

ISBN: (纸本)9798350392067

This paper addresses the problem of characterizing cardiovascular signals describing the autonomic nervous system (ANS), considering the nonlinearity and complexity of its dynamics. We propose three approaches to reveal the dynamics of the ANS: joint symbolic analysis (JSA), phase-rectified signal averaging (PRSA), and Fuzzy Entropy (FuzzyEn). The analyzed dataset consisted of 34 young volunteers, in whom arterial blood pressure was measured non-invasively during controlled breathing sessions (6,10, and 15 breaths $/ \mathrm{min}$). The results show that quasiperiodicities in the tachogram, quantified using PRSA as heart acceleration and deceleration capacity, decreased with breathing frequency ($p(\lt)0.001$ for both). Cardiovascular interaction, quantified by JSA as the relative frequency of symmetric word types, decreased with breathing frequency ($\mathbf{p}\lt \mathbf{0. 0 0 1}$). FuzzyEn increased with breathing frequency but did not correlate with PRSA and JSA metrics. Our results demonstrate that JSA, PRSA, and FuzzyEn are sensitive to ANS modulation during breathing frequency challenges, providing complementary information about ANS modulation.

关键词： Heart Frequency modulation Autonomic nervous system Europe Arterial blood pressure Entropy Pressure measurement complexity theory Oscillators Frequency control

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Adaptive Neural Network Dynamic Surface Trajectory Tracking Control for Underactuated Autonomous Underwater Vehicles

Adaptive Neural Network Dynamic Surface Trajectory Tracking ...

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Robotics and Computer Vision (ICRCV), International conference on

作者： Guohong Jiang Meng Joo Er Huibin Gong Siqi Wang Institute of Artificial Intelligence and Marine Robotics College of Marine Electrical Engineering Dalian Maritime University Dalian China

ISBN: (数字)9798331527426

ISBN: (纸本)9798331527433

Aiming at the trajectory tracking control problem of underactuated autonomous underwater vehicles (AUVs) with unknown dynamic model parameters and time-varying ocean disturbances, a dynamic surface adaptive control strategy based on radial basis function neural network is proposed to complete the desired three-dimensional trajectory tracking. Firstly, an output redefinition method is used to solve the underactuated problem. Secondly, a dynamic surface control method is used to overcome the “explosion of complexity” problem in traditional backstepping control, and complexity of the control law design is simplified. At the same time, a nonlinear damping term is added in control law to overcome unknown external disturbances. Finally, unknown dynamic model parameters are approximated by a neural network, and the neural network weights are estimated online by an adaptive law. The Lyapunov theory is used to prove that all signals of closed-loop system are semi-globally uniformly bounded, and effectiveness of the control law is verified by comparative simulations.

关键词： Damping Sea surface Autonomous underwater vehicles Adaptation models Trajectory tracking Computational modeling Explosions complexity theory Vehicle dynamics Adaptive control

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