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International Conference on Guidance, Navigation and control, ICGNC 2020

作者： Niu, Qiushi Li, Qingdong Liu, Yishi Han, Liang Ren, Zhang School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China School of Sino-French Engineer Beihang University Beijing100191 China

ISBN: (纸本)9789811581540

A fault-tolerant control for launch vehicle actuator with actuator faults is proposed assuming the fault has been diagnosed in this paper. Firstly, the model for the launch vehicle with actuator failures is established considering faults. The tracking differentiator is used to process the angle signal of the program for the subsequent controller design. Using the attitude angle and angular velocity information measured by the control components, a basic controller is designed by LQR method to make the launch vehicle stable, thus a reference model with good stability is obtained. Moreover, the adaptive control law is designed in the form of integral by means of model reference adaptive control (MRAC) method to ensure attitude stability in flight. Finally, the validity of the algorithm was verified by simulation. © 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： model reference adaptive control

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An Exponentially Convergent adaptive Robust Based Space Manipulator Noise control Method 51

An Exponentially Convergent Adaptive Robust Based Space Mani...

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51st International Congress and Exposition on Noise control Engineering, Internoise 2022

作者： Liu, Jinglong Li, Ning Hu, Xueping Ma, Xiaolong Shanghai Institute of Aerospace System Engineering No. 3888 Yuanjiang Road Minhang District Shanghai China Shanghai Key Laboratory of Spacecraft Mechanism No. 3888 Yuanjiang Road Minhang District Shanghai China

ISBN: (纸本)9781906913427

Because most of the traditional nonlinear control methods are model-based control methods, it will dramatically increase the parameter identification burden of multi-rigid-body system dynamic model. Meanwhile, Unmodeled dynamics, parameter drift, model uncertainty, complex motor hysteresis characteristics, etc are unfortunately in the practical systems, which makes it very hard to accurately build the noise model and identify the model parameters. Among them, the accurate values of the viscous friction coefficient, elastic friction coefficient, the distance between the centroid and the rotation center of the connecting rod, the inertial moment and products of each joint, these exact values can hardly be obtained. In this paper, direct adaptive control and the robust model reference adaptive control based on Lyapunov direct method are adopted, which can make the noise error close to zero under the condition of parameter uncertainty and unknown nonlinear friction characteristics. © 2022 Internoise 2022 - 51st International Congress and Exposition on Noise control Engineering. All rights reserved.

关键词： model reference adaptive control

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A torque-based MRAS estimator for position/speed sensor-less control of DFIG systems 1

A torque-based MRAS estimator for position/speed sensor-less...

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1st IEEE Industrial Electronics Society Annual On-Line Conference, ONCON 2022

作者： Mbukani, M.W.K. Gitau, M.N. Naidoo, R. Masike, L. University of Pretoria Dept. of Electrical Electronic and Computer Engineering Pretoria South Africa

ISBN: (纸本)9798350398069

In this paper, an electromagnetic torque-based model reference adaptive system (MRAS) is proposed for sensor-less control of doubly-fed induction generator (DFIG) systems. The proposed electromagnetic torque based MRAS estimator aims at extracting the rotor speed in the synchronous reference frame. The advantage of the proposed MRAS estimator is its simplicity due to the fact that it requires only the three-phase rotor current and the reference three-phase rotor voltage as inputs. The small signal analysis is used to conduct stability study of the proposed rotor speed estimator. The PI gains of the MRAS estimator are determined using pole placement. The performance of the proposed rotor speed estimator is validated under various operating conditions of the DFIG using MATLAB/SIMULINK. © 2022 IEEE.

关键词： model reference adaptive control

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adaptive control of Dubins Vehicle in the Presence of Loss of Effectiveness (Extended Version)

arXiv

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arXiv 2025年

作者： Naranjo, Daniel Maldonado Annaswamy, Anuradha M. Department of Mechanical Engineering Massachusetts Institute of Technology CambridgeMA02139 United States

The control of a Dubins Vehicle when subjected to a loss of control effectiveness is considered. A complex state-space representation is used to model the vehicle dynamics. An adaptive control design is proposed, with the underlying stability analysis guaranteeing closed-loop boundedness and tracking of a desired path. It is shown that a path constructed by waypoints and a minimum turn radius can be specified using a reference model which can be followed by the closed loop system. The control design utilizes the complex representation as well as a PID controller for the nominal closed-loop. How the design can be modified to ensure that the control input does not saturate is also discussed. Simulation studies are carried out to complement the theoretical derivations. © 2025, CC BY.

关键词： model reference adaptive control

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adaptive model Predictive control for Permanent Magnet Synchronous Motor 26

Adaptive Model Predictive Control for Permanent Magnet Synch...

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26th International Conference on Industrial Technology, ICIT 2025

作者： Zhang, Zhiwei Luo, Wensheng Zhang, Ruifang Li, Haofei Jin, Zhongqi Li, Chaoyi School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China

ISBN: (纸本)9798331521950

In order to solve the problem of speed fluctuation existing in PMSM model predictive control after loading, an optimization strategy based on model reference adaptation is proposed, which take torque and flux as state variables, constantly identified the actual inductance and flux parameters of the motor, and then compensated the adverse effects of parameter changes on the model predictive controller. It makes the whole control system form a complete adaptive optimization control. Secondly, the model prediction controller forms a closed loop between the motor and the controller through the identification algorithm, simplifying the problem of parameter matching and subsequent debugging. © 2025 IEEE.

关键词： model reference adaptive control

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KL Penalty control via Perturbation for Direct Preference Optimization

arXiv

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arXiv 2025年

作者： Lee, Sangkyu Han, Janghoon Song, Hosung Choi, Stanley Jungkyu Lee, Honglak Yu, Youngjae Yonsei University Korea Republic of LG AI Research University of Michigan Ann Arbor United States

Direct Preference Optimization (DPO) demonstrates the advantage of aligning a large language model with human preference using only an offline dataset. However, DPO has the limitation that the KL penalty, which prevents excessive deviation from the reference model, is static throughout the training process. Several methods try to turn this static KL penalty into a dynamic one, but no approach can adaptively assign different KL penalties for each preference pair. In this paper, we propose Ε-Direct Preference Optimization (ΕDPO), which allows adaptive control of the KL penalty strength β for each preference pair. Specifically, Ε-DPO adaptively controls β for each preference pair based on the monotonicity of logits as a preference model under the perturbation of β during training by simply reusing the logit of the current policy and the reference policy. Experimental results show that Ε-DPO outperforms existing direct alignment algorithms and KL penalty relaxation methods on general chatbot benchmarks, highlighting the significance of adaptive KL penalty relaxation at the instance-level in DPO1 © 2025, CC BY.

关键词： model reference adaptive control

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MRAC with fractional order adaptation law design for a class of fractional order systems 19

MRAC with fractional order adaptation law design for a class...

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19th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2022

作者： Leulmi, Mohammed Islam Ladaci, Samir National Polytechnic School of Constantine Department of E.E.A. Constantine Algeria National Polytechnic School of Algiers Department of Automatics Algiers Algeria

ISBN: (数字)9781665471084

ISBN: (纸本)9781665471084

This papers presents a model reference adaptive control (MRAC) with fractional order reference model and fractional order adaptation law. Simulations show that the proposed adaptation law for the control action is able to stabilize the fractional order system, and guarantee the convergence of the output to the reference signal in relatively short time. The simulation results are compared to the results of MRAC with regular adaptation law. © 2022 IEEE.

关键词： model reference adaptive control

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IMC-based model reference adaptive control for IPM machines

IMC-based Model Reference Adaptive Control for IPM machines

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31st Chinese control Conference

作者： Zhou, Ronghui Zhao, Tong Li, Yong Shen, Xiangming GE Co Real Time Controls & Instrumentat Lab Global Res Ctr Shanghai 201203 Peoples R China

ISBN: (纸本)9789881563811

A model reference adaptive control algorithm for interior permanent magnet machines is presented in this paper, in particular, the initial value of the adaptive control gains and the reference model are set based on the internal model control principle. Compared with the traditional model reference adaptive control, the proposed adaptive control law provides a better machine torque transient response and is robust to the machine parameter variation. The effectiveness of the whole system has been validated in a 40kW interior permanent magnet machine simulation platform.

关键词： model reference adaptive control Internal model control Interior Permanent Magnet Machine control

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TD3 Deep Reinforcement Learning-Based Improved Sensorless MRAS control Strategy for Multi-Electric Aircraft PMSM 1st

TD3 Deep Reinforcement Learning-Based Improved Sensorless MR...

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1st Electrical Artificial Intelligence Conference, EAIC 2024

作者： Wu, Han Li, Bingqiang Zhou, Xiong Wang, Dongheng Deng, Yuening School of Automation Northwestern Polytechnical University Xian710072 China

ISBN: (纸本)9789819640584

To mitigate position sensor failures in multi-electric aircraft systems operating under extreme conditions such as high temperature, high pressure, and turbulent vibrations, this paper presents a sensorless position control strategy based on a model reference adaptive System (MRAS) enhanced with deep reinforcement learning. Specifically designed for Permanent Magnet Synchronous Motors (PMSM), the strategy integrates a Twin Delayed Deep Deterministic Policy Gradient (TD3) controller within an Actor-Critic framework to improve dynamic performance and reduce output angle tracking errors caused by MRAS estimation inaccuracies and suboptimal control parameters. The controller’s real-time online learning capability and extensive data-driven training confer enhanced robustness against various system disturbances, ensuring overall system stability. Simulation experiments validate the effectiveness and reliability of the proposed control strategy, demonstrating its potential for application in demanding aerospace 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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Sensorless control Design and Stability Analysis of High-Speed Dual Three-Phase Permanent Motor Drive for Future Aircraft Applications

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IEEE Transactions on Power Electronics 2025年

作者： Bi, Guangdong Chen, Yuzheng Wang, Kaixuan Cao, Shengyu Yang, Tao

Dual three-phase PMSM sensorless drive systems become attractive solutions for more electric aircraft applications due to their high-power density and potential fault tolerance capabilities. The model reference adaptive system (MRAS) is a commonly used sensorless control method. The high-speed operation of aircraft engines places higher demands on its discretisation design. In this paper, to improve the discretisation precision and stability of the control system, a second-order Taylor expansion based MRAS sensorless control design method in the discrete-time domain is proposed, which also includes the modelling and analysis of the entire current-loop control system. This method can directly derive the discrete nonlinear mathematical models of both the MRAS and current control parts, reducing the impact of discretisation step size. To further analyse the stability and parameter influence, relevant linearized discrete small-signal models are developed. On this basis, a full-order discrete state evolution equation of sensorless control system is presented. By analysing the eigenvalues of the state matrix, the stable regions of the system under different operation conditions are illustrated, providing guidance for parameter selection and validating that the proposed method has superior stability than the traditional first-order Taylor expansion-based method in the higher-speed range. The effectiveness of this approach is verified by experiments on a dual three-phase PMSM drive platform. © 1986-2012 IEEE.

关键词： model reference adaptive control

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