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Simulation and experimental tests on active mass damper control system based on model reference adaptive control algorithm

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JOURNAL OF SOUND AND VIBRATION 2014年第20期333卷 4826-4842页

作者： Tu, Jianwei Lin, Xiaofeng Tu, Bo Xu, Jiayun Tan, Dongmei Wuhan Univ Technol Hubei Key Lab Roadway Bridge & Struct Engn Wuhan 430070 Peoples R China Guangzhou Huasen Architectural & Engn Designing C Guangzhou 510045 Guangdong Peoples R China

In the process of sudden natural disasters (such as earthquake or typhoon), the active mass damper (AMD) system can reduce the structural vibration response optimally, which serves as a frequently applied but less mature vibration-reducing technology in wind and earthquake resistance of high-rise buildings. As the core of this technology, the selection of control algorithm is extremely challenging due to the uncertainty of structural parameters and the randomness of external loads. It is not necessary for the model reference adaptive control (MRAC) based on the Minimal controller Synthesis (MCS) algorithm to know in advance the structural parameters, which produces special advantages in conditions of real-time change of system parameters, uncertain external disturbance, and the nonlinear dynamic system. This paper studies the application of the MRAC into the AMD active control system. The principle of MRAC algorithm is recommended and the dynamic model and the motion differential equation of AMD system based on MRAC is established under seismic excitation. The simulation analysis for linear and nonlinear structures when the structural stiffness is degenerated is performed under AMD system controlled by MRAC algorithm. To verify the validity of the MRAC over the AMD system, experimental tests are carried out on a linear structure and a structure with variable stiffness with the AMD system under seismic excitation on the shake table, and the experimental results are compared with those of the traditional pole assignment control algorithm. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Variable stiffness Earthquake resistance model reference adaptive control lineation damper control external load SHAKING TABLE structural rigidity Computer algorithms Earthquakes

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Ultimate Boundedness Theorem for model reference adaptive control Systems

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JOURNAL OF GUIDANCE control AND DYNAMICS 2014年第5期37卷 1595-1603页

作者： Hoecht, L. Bierling, T. Holzapfel, F. Tech Univ Munich Inst Flight Syst Dynam D-85748 Garching Germany

This paper presents a novel formulation of the Lyapunov-based ultimate boundedness theorem with explicit specification of transient and ultimate bounds, time to the ultimate bound, and the set of admissible initial conditions. The formulation is tailored to the structure of model reference adaptive control systems accounting for a partitioning of the state vector into a tracking error and a parameter estimation error. It allows for a computation of separate bounds for the single state vector partitions in favor of a single bound on the compound state, consisting of both partitions. This is of great practical importance because tracking error and parameter estimation error are of different magnitudes in general. Regarding model reference adaptive control systems, it is the state of the technology so far that the ultimate boundedness theorem is tailored to the structure of the considered system each time, again and again. It is hence manifest to formulate once a generic version of the theorem, tailored to model reference adaptive control systems, but not to reinvent the wheel for each case.

关键词： model reference adaptive control Elevator Deflection Flight control System adaptive control Systems Aviation Unmanned Aircraft System Second Order Differential Equations Attitude Stabilization Handling Qualities control Algorithm

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Application of a Robust model reference adaptive control Algorithm to a Nonlinear Automotive Actuator

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International Journal of Automation and computing 2014年第4期11卷 377-391页

作者： Alessandro di Gaeta Umberto Montanaro Istituto Motori National Research Council Naples Italy

model reference adaptive control is a viable control method to impose the demanded dynamics on plants whose parameters are affected by large uncertainty. In this paper, we show by means of experiments that robust adaptive methods can effectively face nonlinearities that are common to many automotive electromechanical devices. We consider here, as a representative case study, the control of a strongly nonlinear automotive actuator. The experimental results confirm the effectiveness of the method to cope with unmodeled nonlinear terms and unknown parameters. In addition, the engineering performance indexes computed on experimental data clearly show that the robust adaptive strategy provides better performance compared with those given by a classical model-based control solution with fixed gains.

关键词： model reference adaptive control robust adaptive control nonlinear systems automotive control electronic throttle body electromechanical actuators

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Supporting load frequency control process by using adaptive model reference virtual inertia controller when connecting renewable energy plants

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COMPUTERS & ELECTRICAL ENGINEERING 2024年 117卷

作者： Ragab, Ahmed Allam, Dalia Attia, Hazem Ali Fayoum Univ Fac Engn Engn Math & Phys Dept Faiyum Egypt Fayoum Univ Fac Engn Elect Engn Dept Faiyum Egypt

Virtual inertia control can be used in combination with conventional load frequency controllers to support the system's inertia against the attenuation caused by renewables. As fractional-order controllers add more degrees of freedom, leading to a better response and improved controller robustness, this work proposes the implementation of a developed fractional-order model reference adaptive virtual inertia controller when integrating renewables in combination with fractional-order ID-P with filter controller as secondary controllers. To validate the introduced controllers, their results have been compared to those of using integer and fractional-order PID controllers as secondary controllers, in combination with adaptive and fixed parameters virtual inertia controllers. The Artificial Rabbits heuristic algorithm is used for the purpose of tuning secondary controllers and fixed parameters virtual inertia controllers. The proposed combination of adaptive model reference virtual inertia control with fractional-order ID-P with a filter achieves the best response among all the studied combinations. Using the proposed combination shows a relative percentage improvement in the cost function value of 26% to 160% compared to all the studied combinations. Additionally, the proposed combination shows a maximum frequency overshoot value of 0.04 Hz and a minimum undershoot value of -0.06 Hz.

关键词： Load frequency control Fractional calculus model reference adaptive control Renewable energy

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Direct model reference adaptive control with Actuator Failures and Sensor Bias

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JOURNAL OF GUIDANCE control AND DYNAMICS 2014年第1期37卷 312-U14页

作者： Joshi, Suresh M. Patre, Parag NASA Langley Res Ctr Hampton VA 23681 USA Siemens Corp Corp Technol Princeton NJ 08540 USA

Actuator and sensor faults have been implicated in several aircraft loss-of-control accidents and incidents. Direct model reference adaptive control (MRAC) methods have been suggested as a promising approach for maintaining stability and controllability in the presence of uncertainties and actuator failures without requiring explicit fault detection, identification, and controller reconfiguration (e.g., [1,2]). (An extensive amount of literature is available on adaptive control in the presence of actuator failures, but could not be listed in this brief Note due to space limitations; however, a detailed reference list is available in [2]). In addition to actuator faults, sensor faults may also compromise safety [3-5]. A common type of sensor fault is unknown sensor bias, which can develop during operation in one or more sensors, such as rate gyros, accelerometers, altimeter, etc. If used directly in an MRAC law, such offsets in sensor measurements can have detrimental effects on closed-loop stability, which can no longer be theoretically guaranteed. Accommodation of sensor faults in an MRAC setting has been addressed (e.g., [6-8]). However, adaptive control of systems with simultaneous actuator and sensor faults has not been adequately addressed. Toward that goal, MRAC control laws using state feedback for state tracking were developed in [9] for the case with simultaneous sensor bias and actuator failures, and signal boundedness as well as bounded or asymptotic tracking were obtained. This Note elaborates on the results of [9] and presents numerical examples to illustrate the methods.

关键词： Sensors model reference adaptive control Actuators control Surfaces True Airspeed Elevator Deflection adaptive control Systems Aircraft Flight control Gaussian White Noise Feedback control

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model reference adaptive control of Glucose in Type 1 Diabetics: A Simulation Study

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IFAC Proceedings Volumes 2014年第3期47卷 5055-5060页

作者： Marián Tárník Eva Miklovičová Ján Murgaš Ivan Ottinger Tomáš Ludwig Institute of Robotics and Cybernetics Faculty of Electrical Engineering and Information Technology Slovak University of Technology in Bratislava Ilkovicova 3 812 19 Bratislava Slovakia

Paper presents the model reference adaptive control applied for the glucose concentration control in Type 1 diabetes mellitus (T1DM) subject. The adaptive controller structure allows to present the commanded insulin infusion by means of the basal infusion rate and the bolus insulin doses. T1DM simulation model is adjusted so that the simulated output corresponds to the particular data logged in a diabetic diary. These facts have allowed to compare the obtained results with the data logged in the diary.

关键词： model reference adaptive control type one diabetes mellitus diabetic diary

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Optimised model reference adaptive control for an interacting two tank system

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INTERNATIONAL JOURNAL OF ENGINEERING SYSTEMS modelLING AND SIMULATION 2014年第1-2期6卷 80-85页

作者： Sreelatha, Preethi Gandhi, Sanjeevi Karunya Univ Dept Elect & Instrumentat Coimbatore 641114 Tamil Nadu India

In this paper, a method for controlling multivariable process is presented. The system under investigation is a two tank interacting process. A decoupler is designed in order to minimise the interaction effects. The model reference adaptive controller is then designed for the process with decoupler block. The tuning parameter gamma is optimised using genetic algorithm. GA optimised model reference adaptive controller was then compared with conventional controllers. The performance comparisons have been made in terms of rise time, settling time and performance criteria.

关键词： multi input multi output model reference adaptive control MRAC two inputs two outputs proportional-integral controller genetic algorithm

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adaptive velocity control of an autonomous vehicle using input-error model reference approach

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JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS 2024年第6期361卷

作者： Simorgh, Abolfazl Razminia, Abolhassan Marashian, Arash Univ Carlos III Madrid Dept Bioengn & Aerosp Engn Ave Univ 30 Madrid 28911 Spain Abo Akad Univ Fac Nat Sci & Engn Proc Control Lab Turku Finland

The input error model reference adaptive control (IE-MRAC) is employed to regulate the longitudinal velocity of an autonomous vehicle to desired values by controlling both the throttle and the braking system. The proposed method deals with matching the unknown longitudinal model of the vehicle with a predefined model in the presence of various disturbances, including road conditions and aerodynamic effects. Moreover, it is shown that the saturation on the throttle and the brake pedals are successfully handled due to the properties of the derived error equation. Besides analyzing the natural properties of IE-MRAC, a novel stability proof of the closed -loop system is presented, and a robust modification of the adaptive control law is given as well. By using the proposed control technique, higher -order tracking is captured, and the effects on enhancing the vehicle responses are investigated. The applicability of the presented theoretical results is validated via the CarSim simulator.

关键词： Velocity control model reference adaptive control Input error Robustness analysis Higher-order tracking

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Wavelet Neural Network model reference adaptive control Trained by a Modified Artificial Immune Algorithm to control Nonlinear Systems

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ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2014年第6期39卷 4737-4751页

作者： Lutfy, Omar Farouq Univ Technol Baghdad Control & Syst Engn Dept Baghdad Iraq

This paper presents a wavelet neural network (WNN)-based model reference adaptive control (WNNMRAC) scheme to control arbitrary complex nonlinear systems. As the training method for the WNN, a newly developed optimization technique, called the micro artificial immune system (Micro-AIS), is employed to find the optimal values for the WNN parameters. Two modifications were suggested to enhance the performance of the original Micro-AIS, resulting in a more powerful optimization algorithm. Utilizing the proposed control approach, it is not necessary to construct a pseudo-plant, which was a prerequisite in other works, for controlling the nonlinear systems. To demonstrate the effectiveness of the proposed direct WNNMRAC, three single-input single-output complex nonlinear systems are selected, including a non-minimum phase system, a time-delay system, and a minimum phase system. From several performance evaluation tests, the WNNMRAC has shown its effectiveness in terms of accurate control performance, applicability to different types of nonlinear systems, robustness to external disturbances, and good generalization ability. In addition, a simulation test to control nonlinear multi-input multi-output (MIMO) system has shown that the WNNMRAC can be extended to control nonlinear MIMO systems. Finally, from a comparative study, the WNNMRAC has confirmed its superiority over a conventional neural network model reference adaptive control.

关键词： Wavelet neural network model reference adaptive control Artificial immune system Micro artificial immune system Artificial neural network

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model reference adaptive control Based on Lyapunov Stability Theory

Model Reference Adaptive Control Based on Lyapunov Stability...

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26th Chinese control and Decision Conference (CCDC)

作者： Tang Minan Cao Jie Yang Xiaoxiao Wang Xiaoming Gu Baohui Lanzhou Univ Technol Sch Mech & Elect Engn Lanzhou 730050 Peoples R China

ISBN: (纸本)9781479937066

For the obvious characteristics of time-varying nonlinear controlled object, in order to improve the control performance, the appropriate adaptive control strategy could be used. Based on the research object system of a certain amount of input to control variables, according to Lyapunov stability theory, the research object system input/output variable a model reference adaptive control system was designed. And after analyzing the method of improving the system starting stage characteristics, dynamic process performance and system anti-interference and resistance to process parameters is presented. Simulation and research results show that the proposed control method is effective.

关键词： Intelligence control model reference adaptive control Lyapunov Stability theory

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