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modelling and Neuro-adaptive Robust control Algorithms for Solid Fuel Rockets

JOURNAL OF AEROSPACE TECHNOLOGY AND MANAGEMENT 2025年 17卷

作者： de Carvalho, Christian Danner Ramos Neto, Joao Viana da Fonseca Univ Fed Maranhao Ctr Ciencias Exatas & Tecnol Programa Posgrad Engn Aerosp Sao Luis MA Brazil Univ Fed Maranhao Ctr Ciencias Exatas & Tecnol Programa Posgrad Engn Elect Sao Luis MA Brazil

This study presents the development of a methodology for designing neuro-adaptive robust controllers based on a reference model associated with an artificial neural network of radial basis functions (ANN-RBF) for solid fuel suborbital rockets. The modelling and neuro-adaptive robust control algorithms for these rockets are presented. Initially, the methodology is evaluated for a robust controller based on a reference model with ANN-RBF for altitude control. The main objective of the control is to suppress the effect of non-linear uncertainties inherent in the process. The method involves mathematical and computational modelling, together with the design of adaptive controllers for stability and performance analysis. The controllers considered include model reference adaptive control (MRAC) techniques and a model reference neuro-adaptive control (MRNAC) approach. The analysis, carried out using computer simulations, evaluates the behavior of each controller in relation to system stability and performance. The final objective is to select the most suitable controller for the suborbital rocket, taking into account the system constraints, robust performance requirements, robust stability, and optimal adaptability. This research promotes the development of adaptive controllers for suborbital rockets, with possible applications in scientific research and commercial launches.

关键词： Robust control Rocket model reference adaptive control model reference neuro-adaptive control Artificial neural networks Radial basis function neural networks

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Improved MRAC Based Sensorless PMSM Drive With Enhanced Speed control for LEV Application

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IEEE TRANSACTIONS ON ENERGY CONVERSION 2025年第2期40卷 1153-1164页

作者： Kumar, Sumit Singh, Bhim Indian Inst Technol Delhi Elect Engn Dept New Delhi 110016 India

This paper introduces a sensorless speed and position control for a permanent magnet synchronous motor (PMSM) drive designed for light electric vehicles (LEVs). This approach utilizes a model reference adaptive control (MRAC) strategy, featuring novel flux and torque error based MRAC with an enhanced voltage model. Notably, this method does not rely on speed error and eliminates need for derivative terms in estimation process. Presented sensorless estimation method reduces effect of load variation in estimation as well as improves response from low to high speed. Moreover, to enhance speed controller working, an adaptive improved sliding mode controller (ISMC) is adopted, which adapts changes in terms of finite time convergence as well as accurate tracking and reduced chattering. To achieve fast convergence in finite time, fast integral terminal sliding surface along with novel reaching law is selected for sliding mode controller design. Furthermore, a simple predictive current controller is utilized, which eliminates need of a modulator and incorporates inverter nonlinearities. Simulation implementation of control is executed in Simulink and its experimental performance is verified on a laboratory test setup. A comparative analysis of PI controller with improved SMC and sensorless position estimation by improved flux MRAC with conventional MRAC is done.

关键词： Torque Estimation Adaptation models Rotors Robustness PI control Observers Mathematical models Inverters Tuning PMSM sensorless control light electric vehicle model reference adaptive control speed controller

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adaptive fuzzy sliding mode control for high-speed train using multi-body dynamics model

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IET INTELLIGENT TRANSPORT SYSTEMS 2023年第2期17卷 450-461页

作者： Guo, Youxing Sun, Pengfei Feng, Xiaoyun Yan, Keqin Southwest Jiaotong Univ Sch Elect Engn Chengdu 610031 Peoples R China

In this paper, an equivalent multi-body dynamics model of high-speed train with uncertain parameter is established. Based on this detailed model and neural network minimum parameter learning algorithm, an adaptive sliding mode control method is designed for speed and position tracking control of high-speed train, and the stability of the proposed control method is proved strictly. Then an adaptive fuzzy sliding mode control method (AFSMC) is presented to avoid chattering caused by excessive robust switching gain. Finally, numerical tests are carried out on the proposed AFSMC under different scenarios and operation strategies, and model reference adaptive control (MRAC), PID control and sliding mode control are also tested under the same condition for performance comparison. The results show that the proposed control method is superior to the currently used method. More specifically, compared with MRAC and PID, the average speed tracking accuracy of AFSMC is improved by 0.25 km/h and 0.18 km/h, and the average position tracking accuracy is improved by 0.68 m and 0.7 m, respectively.

关键词： uncertain parameter position control railways Rail-traffic system control stability adaptive fuzzy sliding mode control method uncertain systems variable structure systems PID control robust switching gain model reference adaptive control systems position tracking control Fuzzy control Self-adjusting control systems learning algorithm speed tracking Neurocontrol high-speed train fuzzy control three-term control MRAC neurocontrollers Multivariable control systems neural network velocity control multibody dynamics model Velocity, acceleration and rotation control robust control Stability in control theory model reference adaptive control Spatial variables control AFSMC

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Uncertainty modeling Enabled Meta adaptive control for Aerial Manipulators

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JOURNAL OF GUIDANCE control AND DYNAMICS 2024年第10期47卷 2148-2163页

作者： Gao, Shiqi Hong, Haichao Sun, Sihao Luo, Lingkun Hu, Shiqiang Shanghai Jiao Tong Univ Sch Aeronaut & Astronaut Shanghai 200240 Peoples R China Delft Univ Technol Dept Cognit Robot NL-2628 CD Delft Netherlands

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Distributed adaptive control for H8tracking of uncertain interconnected dynamical systems

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INTERNATIONAL JOURNAL OF adaptive control AND SIGNAL PROCESSING 2023年第5期37卷 1102-1116页

作者： Gebremedhin, Atsede G. Fujisaki, Yasumasa Osaka Univ Dept Informat & Phys Sci Suita Japan

A distributed adaptive control is proposed for H-infinity tracking of an interconnected dynamical system in the presence of L-2 disturbances and system/interconnection uncertainties. A reference model which achieves a robust tracking against L-2 disturbances is introduced by using H-infinity control with transients. Then a distributed adaptive control law is developed for an uncertain interconnected dynamical system, where it employs the specified reference model. It is shown that the boundedness of the error dynamics behaviors as well as zero tracking error in the steady state is guaranteed by the proposed distributed adaptive control in the presence of disturbances and uncertainties. An explicit error bound related to H-infinity tracking is also established.

关键词： distributed control model reference adaptive control H-infinity tracking interconnected uncertain dynamical systems

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Fraction-order MRAC Method Based Fault Tolerant control for Plant Protection UAV With Actuator Failure and Uncertainty

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INTERNATIONAL JOURNAL OF control AUTOMATION AND SYSTEMS 2023年第8期21卷 2623-2633页

作者： Yang, Xiaofei Hu, Xiangbing Ye, Hui Liu, Wei Shen, Hao Jiangsu Univ Sci & Technol Sch Elect & Informat Zhenjiang Jiangsu Peoples R China Anhui Univ Technol Sch Elect & Informat Engn Maanshan 243032 Peoples R China

Due to high efficiency operation capability and no special site requirement for landing and taking off, plant protection unmanned aerial vehicle (UAV) has been widely used in precision agriculture. However, there are also some factors affecting flight operation safety, such as partial failure of actuator and uncertainty caused by change of the mass with time, which mainly lead to altitude and attitude control failure problem. In view of the operation characteristics of the spray tank and actuator with partial failure, a hybrid control model of plant protection UAV with actuator failure and uncertainty is established. In order to design control law to improve fault tolerant capability of the flight control system, a fractional-order model reference adaptive control method (FO-MRAC) is proposed. Based on our FO-MRAC algorithm, altitude and attitude control laws of plant protection UAV are devised. Popov hyper-stability theorem is also used to prove the system's stability. Finally, numerical simulation is carried out to verify the effectiveness of our method. Compared with conventional proportional-integral-differential (PID) control and model reference adaptive control (MRAC) methods, our method has advantages in improving the convergence speed, reducing overshoot, and robustness of the system.

关键词： Fault tolerance fractional order model reference adaptive control plant protection UAV Popov hyper-stability

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adaptive Finite Time Intercept Guidance

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JOURNAL OF GUIDANCE control AND DYNAMICS 2023年第10期46卷 1975-1980页

作者： Calise, Anthony J. Georgia Inst Technol Sch Aerosp Engn Atlanta GA 30332 USA

This paper summarizes several key issues of importance related to intercept of high-speed maneuvering targets under stratospheric altitude conditions, where it is unlikely that the interceptor will have a significant speed and/or maneuverability advantage. It explains why one cannot rely on traditional proportional navigation guidance and presents simulation results for a recently developed finite time method of guidance. A simplified version of finite time intercept guidance is derived, and a modification required to allow it to be practically implemented is described. Simulation results are presented to illustrate the advantages of the simplified version.

关键词： Guidance Navigation and control Systems model reference adaptive control Guided Missiles Missile Guidance and control

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Rigid-Body Noncertainty Equivalence adaptive control on the Tangent Bundle of SE(3)

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JOURNAL OF GUIDANCE control AND DYNAMICS 2023年第10期46卷 1892-1900页

作者： Seo, Dongeun Nazari, Morad Arabi, Ehsan Embry Riddle Aeronaut Univ Daytona Beach Florida FL 32114 USA Ford Motor Co Dearborn MI 48126 USA

This paper addresses an adaptive rigid-body pose-tracking control problem with unknown system parameters. The proposed control is based on a noncertainty equivalence (NCE) adaptive principle applied to the configuration manifold of rigid-body motion, i.e., special Euclidean group SE(3), and its tangent bundle TSE(3). The controller drives the system to follow an arbitrary reference trajectory with bounded time derivatives. The system states are composed of the elements of SE(3), consisting of rotations and translations, and the six-dimensional vector of angular and translational velocities in Euclidean space. Almost-global-asymptotic stability of the system is demonstrated using a Morse-Lyapunov stability analysis. Then, the performance of the proposed controller is verified and is compared to the results obtained by a certainty-equivalence (CE) adaptive control applied to exponential coordinates associated with the linear space of the Lie algebra se(3). It is shown that the TSE(3)-based NCE adaptive control design can eliminate the performance degradation due to the cancellation of uncertain parameter effects that would otherwise appear when the CE adaptive controller is used. As a result, the proposed NCE-based adaptive pose-tracking controller recovers the closed-loop pose-tracking controller performance with the system parameters fully known to the controller.

关键词： model reference adaptive control Numerical Simulation Attitude Dynamics adaptive control Algorithm Spacecraft Guidance and control Feedback control Nonlinear control Theory

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Necessary and Sufficient Conditions for Data-driven model reference control

arXiv

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arXiv 2023年

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

The objective of model reference control is to design a controller that regulates the system's behavior so as to match a specified reference model. This paper investigates necessary and sufficient conditions for model reference control from a data-driven perspective, when only a set of data generated by the system is utilized to directly accomplish the matching. Noiseless and noisy data settings are both considered. Notably, all methods we propose build on the concept of data informativity and do not rely on persistently exciting data. Copyright © 2023, The Authors. All rights reserved.

关键词： model reference adaptive control

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control of a jet engine using predictor-based adaptive strategy in different flight modes

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND control ENGINEERING 2023年第8期237卷 1349-1364页

作者： Ranjbar, Abedin Khosravi, Alireza Ahmadian, Narjes Babol Noshirvani Univ Technol Dept Elect & Comp Engn Babul Iran

In this article, a predictor-based model reference adaptive control method is proposed for a JetCat SPT5 turboshaft engine in full thrust, cruise, and idle modes. In the predictor-based model reference adaptive control method, in addition to the tracking error, the predictor error is also utilized in adaptive laws to achieve the desired control objectives, such as improving the tracking performance and control signals, and reducing the tracking error. The proposed method is implemented on a turboshaft engine system with actual dynamic values. First, three properly separated equilibrium points are selected on the nominal plant equilibrium manifold to linearize the plant model at the equilibrium points. Then, the predictor-based model reference adaptive control controller is designed and investigated for the three equilibrium points generating three operating modes of the engine, that is, full thrust, cruise, and idle. The stability of the control system is proved by the Lyapunov method. To evaluate the efficiency of the state predictor method in the simulation scenarios, the proposed method is compared with the classic model reference adaptive control method. The simulation results illustrate the superiority of the predictor-based model reference method due to the reduction of unwanted fluctuations in tracking performance, faster convergence of the tracking error to zero, and smoother control signals for all the equilibrium points.

关键词： model reference adaptive control predictor-based model reference adaptive control gas turbine JetCat SPT5 turboshaft engine Lyapunov stability

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