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Robust model reference adaptive Intelligent control

INTERNATIONAL JOURNAL OF control AUTOMATION AND SYSTEMS 2012年第2期10卷 396-406页

作者： Prakash, Raghupathy Anita, Rajapalan Muthayammal Engn Coll Fac Ctr Adv Res Rasipuram Tamil Nadu India Inst Rd & Transport Technol Dept Elect & Elect Engn Erode Tamil Nadu India

In this paper a Neural Network based model reference adaptive control scheme (NN-MRAC) is proposed. In this scheme, the controller is designed by using parallel combination of the conventional model reference adaptive control (MRAC) scheme and Neural Network (NN) controller. In the conventional MRAC scheme, the controller is designed to realize plant output converging to reference model output based on the plant which is linear. This scheme is used to control linear plant effectively with unknown parameters. However, it is difficult for a nonlinear system to control the plant output in real time applications. In order to overcome the above limitations, the NN-MRAC scheme is proposed to improve the system performances. The control input of the plant is given by the sum of the MRAC output and NN controller output. The NN controller is used to compensate the nonlinearities and disturbances of the plant that are not taken into consideration in the conventional MRAC. The simulation results clearly show that the proposed NN-MRAC scheme have better steady state and transient performances than those of the current adaptive control schemes. Thus, the proposed NN-MRAC scheme named as Robust model reference adaptive Intelligent control (RMRAIC) is found to be extremely effective, efficient and useful in the field of control system.

关键词： MATLAB model reference adaptive control neural network nonlinear system

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Design of one adaptive controller for Dynamic Framework and Study of its Tracking

Design of one Adaptive Controller for Dynamic Framework and ...

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2020 International Conference on Computer, Electrical and Communication Engineering, ICCECE 2020

作者： Maiti, Samiran Das, Achintya Maulana Abul Kalam Azad University of Technology Department of E.C.E. West Bengal Haringhata741249 India Kalyani Government Engineering College Department of E.C.E. West Bengal Kalyani741235 India

ISBN: (纸本)9781728144757

The processes having time fluctuating nature execution of conventional controller isn't agreeable. In such cases, adaptive controllers are reasonable as they are able to adjust the control activity as indicated by the adaptive modifications of process elements and undesired burden varieties. Present work proposes a compelling strategy for accomplishing the desired tracking of dynamic framework. Contingent upon the vulnerability parameters a model reference adaptive control (MRAC) is structured and outlined. The idea of adaption component for controlling the framework execution is incredibly influenced by the estimation of adaption gain. Lyapunov Stability approach has been applied to the shut circle elements to guarantee global stability on a variety of plant parameters. Result for analysis is done in MATLAB and the outcomes are looked at for changing the adaption mechanism. © 2020 IEEE.

关键词： model reference adaptive control

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Speed estimator for direct torque and flux control of PMSM Drive using MRAC based on rotor flux 9

Speed estimator for direct torque and flux control of PMSM D...

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9th IEEE Power India International Conference, PIICON 2020

作者： Vujji, Avinash Dahiya, Ratna National Institute of Technology Department of Electrical Engineering Kurukshetra India

ISBN: (纸本)9781728166643

This paper deals with the detailed study of model reference adaptive control (MRAC) based on rotor flux for speed estimation in a direct torque and flux control (DTFC) for permanent magnet synchronous motor (PMSM) drive. In this scheme the speed estimated is given as feedback to DTFC of PMSM drive. From reference model (RM) and adaptive model (AM), the rotor flux linkage components of the PMSM drive are obtained. The error signal of speed, which is obtained from the difference of RM and AM quantities are fed through PI controller to obtain the speed estimated. In order to reduce the error signal, the speed estimated is feedback to AM. Using MATLAB/SIMULINK software the MRAC based on rotor flux is compared with the quantities measured for PMSM drive. And the performance of PMSM drive is studied at zero load, loaded condition, sudden speed changes and sinusoidal speed respectively. © 2020 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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第三十一届中国控制会议

作者： Ronghui Zhou,Tong Zhao,Yong Li,Xiangming Shen~1 1.Real-Time controls and Instrumentation Laboratory,Global Research Center,General Electric Company.Shanghai,201203.P.R.China

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 *** 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 *** 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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model reference adaptive control for Magnetorheological Damper Subjected to High Impact Load

Model Reference Adaptive Control for Magnetorheological Damp...

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2nd International Conference on Advanced Measurement and Test (AMT 2011)

作者： Hu Hongsheng Wang Juan Univ Jiaxing Dept Mech & Elect Jiaxing Zhejiang Peoples R China Univ Jiaxin Lib Jiaxin Univ Jiaxing Zhejiang Peoples R China

ISBN: (纸本)9783037851975

Using the developed hardware-in-the-loop simulation platform for weapon system under impact load excitation and a novel large-scale single-ended MR damper without the accumulator, impact tests for the special designed long-stroke magnetorheological recoil damper were done and its dynamic performances under different impact loads and input current were examined in this paper. model of damping force was established by using the model reference adaptive control method. Its dynamic performances of MR damper under model reference adaptive control strategies were analyzed by numerical simulations and tests. Experimental results show that the model reference adaptive control method could reduce its peak value of recoil damping force to 27.33% and its peak value of stroke to 48.75%, and its adjustability of damping force could be well applied for its impact resistance design of gun recoil mechanism.

关键词： Magnetorheological damper model reference adaptive control impact load controllability

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Design of a Robust model reference adaptive control System

Design of a Robust Model Reference Adaptive Control System

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2012 3rd International Conference on Information Technology for Manufacturing Systems(ITMS 2012)

作者： Xiuchun Zhao Guokai Xu Tao Zhang Pingsu Ge College of Electromechanical & Information Engineering Dalian Nationalities University

This paper addresses a robust adaptive control system based on Popov hyper-stability theory, which has strong robustness for the particular *** the error between model and controlled object into adaptive controller, the system has accurate tracking capability and the convergence even in the presence of external disturbances and *** results are given to illustrate the effectiveness of the proposed robust adaptive control law in comparison with PID control.

关键词： model reference adaptive control Popov hyper-stability theory Tracking capability Disturbances and uncertainties

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Optimising Weighting Factor Design for model Predictive Torque control in IPMSM Drives: A Grey Relational Analysis Approach

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IET Power Electronics 2025年第1期18卷

作者： Hassan, Mannan Zhang, Guoqiang Mastoi, Muhammad Shahid Li, Zhengqing Yu, Xiaopeng Xu, Kunpeng Atif, Rao Haris, Malik School of Information Science and Engineering NingboTech University Zhejiang Ningbo China College of information science and Electronic Engineering Zhejiang University Zhejiang Hangzhou China School of Electrical Engineering Southwest Jiaotong University Sichuan Chengdu China College of Integrated circuits Zhejiang University Hangzhou China Beijing Smartchip Microelectronics Technology Co. Ltd. Beijing China

AC electric drives have widely incorporated model predictive control (MPC) over the past decade. Even with a variety of proposed solutions, there are still challenges related to designing influential weighting factors (WF), reducing parameter dependence, mitigating current/torque harmonics, managing variable switching frequencies and minimising computational complexity. The performance of controllers can be significantly reduced by incorrectly selecting WFs. The cost function of conventional finite-control set model predictive torque control (MPTC) includes multiple control objectives with different units of measurement. WFs are therefore introduced so that these objectives can be prioritized. An extensive comparison of WF design techniques for MPTC strategies in interior permanent magnet synchronous motors (IPMSM) drives is presented in this paper. The first step in the MPTC process is to present a description of conventional MPTC techniques with manual WF tuning, VIKOR and the entropy method for WF optimisation. To address the issue of WF design, the grey relational analysis (GRA) approach is proposed. This method separates the flux and torque objective functions using a single cost function and the grey relational grade is employed for each sampling to determine the appropriate action. Experimental validation of the proposed approach is performed by means of real-time hardware-in-the-loop (HIL) simulations on a prototype IPMSM drive with a TMS320F28335 floating-point digital signal processor. Finally, MPTC is compared with conventional MPTC, VIKOR and entropy-based WF optimisation methods to compare its performance. © 2025 The Author(s). IET Power Electronics published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.

关键词： model reference adaptive control

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DEVELOPMENT AND IN-SILICO EVALUATION OF A CLOSED-LOOP FLUID RESUSCITATION control ALGORITHM WITH MEAN ARTERIAL PRESSURE FEEDBACK

DEVELOPMENT AND IN-SILICO EVALUATION OF A CLOSED-LOOP FLUID ...

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作者： Alsalti, Mohammad University of Maryland

学位级别：硕士

In this thesis, a model-based closed-loop fluid resuscitation controller using mean arterial pressure (MAP) feedback is designed and later evaluated on an in-silico testbed. The controller is based on a subject specific model of blood volume and MAP response to fluid infusion. This simple hemodynamic model is described using five parameters only. The model was able to reproduce blood volume and blood pressure response to fluid infusion using an experimental dataset collected from 23 sheep and is therefore suitable to use for control design purposes. A model-reference adaptive control scheme was chosen to account for inter-subject variability captured in the parametric uncertainties of the underlying physiological model. Three versions of the control algorithm were studied under different measurement availability scenarios. In-silico evaluation of the three controllers was done using a comprehensive cardiovascular physiology model on a cohort of 100 virtually generated patients. Results clearly show that a tradeoff exists between tracking and estimation performance depending on measurement availability.

关键词： Mechanical engineering adaptive control Blood pressure Closed-loop control Composite adaptive control Fluid resuscitation model reference adaptive control

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Improving the performance of a Printing System using model reference adaptive control: an LMI Approach

Improving the performance of a Printing System using Model R...

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American control Conference

作者： M. Ezzeldin S. Weiland P.P.J. van den Bosch Department of Electrical Engineering Eindhoven University of Technology P.O. Box 513 5600 MB Eindhoven The Netherlands

ISBN: (纸本)9781457710957

A novel model reference adaptive control (MRAC) scheme is proposed. The formulation involves recasting the error dynamics, which comprise of the tracking error and error of the controller parameters, into a Takagi-Sugeno model. Instead of using a single adaptation gain, multiple adaptation gains are employed. A sufficient condition is derived to ensure the asymptotic stability of the system for both state and output feedback cases. The adaptive control problem is formulated as a minimization of the L_2 gain. The optimal adaptation gains are obtained by solving a linear matrix inequality problem. A numerical example compares the proposed approach with the standard MRAC. Moreover, the proposed approach is applied to control a real printing system to improve the printing quality where large parameter variations, owing to different print jobs, and disturbances are presence.

关键词： model reference adaptive control Printing system print quality parameter variation Self tuning Interim Local Management Interface asymptotic stability region Output feedback System stability

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Know3-RAG: A Knowledge-aware RAG Framework with adaptive Retrieval, Generation, and Filtering

arXiv

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arXiv 2025年

作者： Liu, Xukai Liu, Ye Wu, Shiwen Zhang, Yanghai Yuan, Yihao Zhang, Kai Liu, Qi School of Computer Science and Technology University of Science and Technology of China China State Key Laboratory of Cognitive Intelligence Anhui Hefei China The Hong Kong University of Science and Technology Hong Kong

Recent advances in large language models (LLMs) have led to impressive progress in natural language generation, yet their tendency to produce hallucinated or unsubstantiated content remains a critical concern. To improve factual reliability, Retrieval-Augmented Generation (RAG) integrates external knowledge during inference. However, existing RAG systems face two major limitations: (1) unreliable adaptive control due to limited external knowledge supervision, and (2) hallucinations caused by inaccurate or irrelevant references. To address these issues, we propose Know3-RAG, a knowledge-aware RAG framework that leverages structured knowledge from knowledge graphs (KGs) to guide three core stages of the RAG process, including retrieval, generation, and filtering. Specifically, we introduce a knowledge-aware adaptive retrieval module that employs KG embedding to assess the confidence of the generated answer and determine retrieval necessity, a knowledge-enhanced reference generation strategy that enriches queries with KG-derived entities to improve generated reference relevance, and a knowledge-driven reference filtering mechanism that ensures semantic alignment and factual accuracy of references. Experiments on multiple open-domain QA benchmarks demonstrate that Know3-RAG consistently outperforms strong baselines, significantly reducing hallucinations and enhancing answer reliability. © 2025, CC BY.

关键词： model reference adaptive control

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