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IEEE Transactions on Industrial Cyber-Physical Systems 2025年 3卷 262-272页

作者： Blevins, Jacob Ueda, Jun Georgia Institute of Technology G.W.W. School of Mechanical Engineering AtlantaGA30332 United States

Cloud-based control is prevalent in many modern control applications. Such applications require security for the sake of data secrecy and system safety. The presented research proposes an encrypted adaptive control framework that can be secured for cloud computing with encryption and without issues caused by encryption overflow and large execution delays. This objective is accomplished by implementing a somewhat homomorphic encryption (SHE) scheme on a modified model reference adaptive controller with accompanying encryption parameter tuning rules. Additionally, this paper proposes a virtual false data injection attack (FDIA) trap based on the SHE scheme. The trap guarantees a probability of attack detection by the adjustment of encryption parameters, thus protecting the system from malicious third parties. The formulated algorithm is then simulated, verifying that after tuning encryption parameters, the encrypted controller produces desired plant outputs while guaranteeing detection or compensation of FDIAs. With the utilization of this novel control framework, adaptively controlled systems will maintain data confidentiality and integrity against malicious adversaries. © 2023 IEEE.

关键词： model reference adaptive control

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Experimental Results with an Embedded model reference adaptive control System on a Multirotor UAS

Experimental Results with an Embedded Model Reference Adapti...

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AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Cartaya, Samuel Jaramillo, Jesse Yucelen, Tansel ControlX Inc. in Santa Clara CA95054 United States

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

Electric vertical take-off and landing (eVTOL) aerial vehicles have many practical applications and are a cornerstone of growing research in recent years. These types of vehicles possess highly nonlinear, coupled dynamics and come across a wide array of uncertainties and disturbances during flight. Many control architectures have been used for the stability and control of eVTOL vehicles during flight. One promising and advantageous method is the implementation of a model reference adaptive control (MRAC) architecture. These types of MRAC systems have a learning mechanism that learns the nature of an uncertainty present in the system dynamics and subsequently alter the controller gains online. It does so in a way that drives the states of the uncertain system to that of a known, desired reference model. This paper describes a standard MRAC architecture and discusses the benefits of its implementation in flight, specifically on a multirotor UAS vehicle. The construction of a medium-sized hexacopter is detailed, along with a discussion of the performance results in the presence of unknown uncertainties. Specifically, we demonstrate an improved flight tracking performance, while in the presence of uncertainties over that of a standard PID control architecture. In addition, we show that the adaptive control architecture allows for a more optimal battery usage during flight, which aids in improved performance. The implementation of adaptive flight control structures paves a beneficial path for future eVTOL aircraft, due to the capability of these control architectures being able to handle a wide class of uncertainties and improve system performance. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： model reference adaptive control

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Enhancing Voltage Regulation in Standalone Microgrid Using a model reference adaptive control Approach

Enhancing Voltage Regulation in Standalone Microgrid Using a...

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International Conference on Electric Power and Renewable Energy, EPREC 2024

作者： Panda, Sweta Biswal, Gyan Ranjan Subudhi, Bidyadhar Department of Electrical and Electronics Engineering Veer Surendra Sai University of Technology Burla Odisha Sambalpur768018 India School of Electrical Sciences Indian Institute of Technology Goa Goa403401 India

ISBN: (纸本)9789819601035

This paper presents an adaptive voltage controller for secondary control (SC) of standalone AC microgrid systems, adaptive parametric estimation features inherent in model reference adaptive control (MRAC) systems. The designed controller establishes precise sharing of active and reactive power, coupled with efficient restoration of voltage reference values even in the presence of unpredictable disturbances. The proposed approach utilizes reference models to represent desired voltage behavior, while an adaptive algorithm continuously updates these models based on changing system conditions. Communication and coordination among distributed controllers enable decentralized decision-making for optimized voltage regulation. One of its key advantages lies in its simplified tuning process and a straightforward mathematical formulation, facilitating a more accessible implementation. Comprehensive simulation results underscore the superior performance of the proposed control approach compared to traditional secondary controllers, particularly in navigating voltage tracking challenges amid uncertain conditions and load fluctuations. The outcomes of this study emphasize the robustness and efficacy of the proposed MRAC as a pivotal solution for augmenting voltage stability in islanded microgrid environments. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： model reference adaptive control

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Multiple model reference adaptive control with Blending for Non-Square Multivariable Systems

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IEEE Transactions on Automatic control 2025年

作者： Lovi, Alex Fidan, Barıs Nielsen, Christopher University of Waterloo Department of Electrical and Computer Engineering WaterlooONN2L 3G1 Canada University of Waterloo Department of Mechanical and Mechatronics Engineering WaterlooONN2L 3G1 Canada

In this article, we develop a multiple model reference adaptive controller (MMRAC) with blending. The systems under consideration are non-square, i.e., the number of inputs is not equal to the number of states;multi-input, linear, time-invariant with uncertain parameters that lie inside of a known, compact, and convex set. Moreover, the full state of the plant is available for feedback. A multiple model online identification scheme for the plant's state and input matrices is developed that guarantees the estimated parameters converge to the underlying plant model under the assumption of persistence of excitation. Using an exact matching condition, the parameter estimates are used in a control law such that the plant's states asymptotically track the reference signal generated by a state-space reference model. The control architecture is proven to provide boundedness of all closed-loop signals and to asymptotically drive the state tracking error to zero. Numerical simulations illustrate the stability and efficacy of the proposed MMRAC scheme, even in the presence of noise. Statistical analysis is included to showcase the improvements of using multiple models. © 1963-2012 IEEE.

关键词： adaptive control model reference adaptive control multiple model polytopic uncertainty uncertain systems

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Bridging model reference adaptive control and Data Informativity

arXiv

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arXiv 2025年

作者： Wang, Jiwei Baldi, Simone van Waarde, Henk J. School of Cyber Science and Engineering Southeast University China Bernoulli Institute for Mathematics Computer Science and Artificial Intelligence University of Groningen Netherlands School of Mathematics Southeast University China

The goal of model reference adaptive control (MRAC) is to ensure that the trajectories of an unknown dynamical system track those of a given reference model. This is done by means of a feedback controller that adaptively changes its gains using data collected online from the closed-loop system. One of the approaches to solve the MRAC problem is to impose conditions on the data that guarantee convergence of the gains to a solution of the so-called matching equations. In the literature, various extensions of the concept of persistent excitation have been proposed in an effort to weaken the conditions on the data required for this convergence. Despite these efforts, it is not well-understood what are the weakest possible data requirements ensuring convergence of MRAC. In this paper, we propose a new framework to study the MRAC problem, using the concept of data informativity. Our main contribution is to provide necessary and sufficient conditions for the convergence of the adaptive gains to a solution of the matching equations. These necessary and sufficient conditions can be readily checked online as new data are generated by the closed-loop system. Our results reveal that existing excitation conditions impose stronger requirements on the collected data than required. Notably, the necessary and sufficient conditions provided in this paper are weaker than those for unique system identification. Copyright © 2025, The Authors. All rights reserved.

关键词： model reference adaptive control

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model reference adaptive control of Cross-Coupling Hysteresis in Piezoceramics With Dynamic Loads

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IEEE ACCESS 2022年 10卷 14691-14697页

作者： Zhang, Lue Zhu, Zipeng Zhou, Xiaochong Sun, Lining Soochow Univ Sch Mech & Elect Engn Jiangsu Prov Key Lab Adv Robot Suzhou 215123 Peoples R China

During the ultraprecise cutting of micro-structure surface with fast tool servo (FTS), the hysteresis of piezoelectric actuators (PEAs) are affected by dynamic voltage excitations and real-time cutting force, which declines the servo accuracy and cutting performance. In this paper, for a multi-input-single-output (MISO) cutting system, a cross-coupling rate-dependent Prandtl-Ishlinskii (CRPI) model is proposed and identified for the dynamic hysteresis of PEAs under dynamic voltage excitation and external loads. A model reference adaptive control method is then presented to eliminate the positioning nonlinearity of PEAs. The hysteresis modeling accuracy is discussed and the adaptive controller is validated through experiments.

关键词： Hysteresis Adaptation models Load modeling Autoregressive processes Dynamics adaptive control Voltage measurement Piezoelectric actuator dynamic hysteresis model cross-coupling model reference adaptive control

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model-reference adaptive-control WITH UNKNOWN RELATIVE DEGREE

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INTERNATIONAL JOURNAL OF adaptive control AND SIGNAL PROCESSING 1993年第5期7卷 457-474页

作者： MOCTEZUMA, RG LOZANO, R SUAREZ, DA UNIV TECHNOL COMPIEGNE HEUDIASYCCNRSURA 817F-60206 COMPIEGNEFRANCE

This work presents an indirect, model reference adaptive control for minimum phase linear systems of arbitrary relative degree. Global stability of the closed-loop system is proved in spite of bounded disturbances and... 详细信息

关键词： model reference adaptive control CONVERGENCE ANALYSIS LEAST-SQUARES ESTIMATION PARAMETER ESTIMATION HYSTERESIS

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Observer-based model reference adaptive control for offshore wind turbines subjected to wind and wave loads

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Transactions of the Institute of Measurement and control 2025年

作者： Zhang, Yun Wang, Yi-Long Zhao, Yan-Dong Zhang, Bao-Lin College of Automation and Electronic Engineering Qingdao University of Science and Technology China

In this paper, an observer-based model reference adaptive controller is proposed to solve the vibration control problem for offshore wind turbines. The process begins with the formulation of a dynamic model that accounts for the inherent complex coupling among the deflection of the floating platform, the displacement at the top of the tower, and the behavior of winds and waves. Subsequently, a model reference adaptive control system is implemented with a disturbance rejection mechanism. A key disturbance observer for the complicated wind-wave mixed loads is developed using a stochastic configuration neural network. Then, the existence conditions and gains for the adaptive controller are meticulously derived from a specific Lyapunov function. The performance of the disturbance observer is evaluated through simulations under various sea conditions. Moreover, the proposed adaptive control system has been shown to significantly reduce half of the control cost while effectively attenuating the responses of deflection and displacement, outperforming existing control solutions. © The Author(s) 2025.

关键词： model reference adaptive control

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model reference adaptive control of discrete-time piecewise linear systems

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INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR control 2013年第7期23卷 709-730页

作者： di Bernardo, Mario Montanaro, Umberto Olm, Josep M. Santini, Stefania CNR Ist Motori I-80125 Naples Italy Univ Naples Federico II Dept Syst & Comp Engn I-80125 Naples Italy Univ Bristol Dept Engn Math Bristol BS8 1TR Avon England Univ Politecn Cataluna Dept Appl Math 4 Castelldefels 08860 Spain

This article presents a switched model reference adaptive controller for discrete-time piecewise linear systems. In the spirit of the work by Landau in the late seventies, proof of asymptotic stability of the closed-loop error system is obtained, recasting its dynamics as a feedback system and showing the feedforward and the feedback paths are both passive. The challenge is that both paths can be piecewise linear. Numerical results show excellent performance of the proposed controller even in the face of sudden variations of the plant parameters. Copyright (c) 2012 John Wiley & Sons, Ltd.

关键词： discrete-time systems model reference adaptive control piecewise linear systems passivity

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model reference adaptive control for nonlinear time-varying hybrid dynamical systems

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INTERNATIONAL JOURNAL OF adaptive control AND SIGNAL PROCESSING 2023年第8期37卷 2162-2183页

作者： L'Afflitto, Andrea Virginia Tech Grad Dept Ind & Syst Engn Blacksburg VA 24061 USA

This paper presents the first model reference adaptive control system for nonlinear, time-varying, hybrid dynamical plants affected by matched and parametric uncertainties, whose resetting events are unknown functions of time and the plant's state. In addition to a control law and an adaptive law, which resemble those of the classical model reference adaptive control framework for continuous-time dynamical systems, the proposed framework allows imposing instantaneous variations in the reference model's trajectory to rapidly steer the trajectory tracking error to zero, while retaining the closed-loop system's ability to follow a user-defined signal. These results are enabled by the first extension of the classical LaSalle-Yoshizawa theorem to time-varying hybrid dynamical systems, which is presented in this paper as well. A numerical simulation shows the key features of the proposed adaptive control system and highlights its ability to reduce both the control effort and the trajectory tracking error over a classical model reference adaptive control system applied to the same problem.

关键词： hybrid dynamical systems LaSalle-Yoshizawa theorem model reference adaptive control

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