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检索条件"主题词=Model Reference Adaptive Control"

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An improved method for MRAC system of indirectly designed

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2012 International Conference on Cybernetics and Informatics, ICCI 2012

作者： Han, Huishan Liu, Yan Cheng, Defang Gao, Xue Xingtai Polytechnic College Xingtai 054000 China Key Lab. of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao 066004 China

ISBN: (纸本)9781461438717

Based on Lyapunov stability theorem, a MRAC system was researched to solve that differential value of plant output is unknown. Meanwhile an improved design for MRAC system aimed on the factor of restricting convergence of system is given. The method not only solves the problem that makes the system cannot work well as a result of the adjustable parameters, but also improves the convergence of plant. The simulation graphs have shown that the plant can follow the output of the reference model quit well © 2013 Springer Science+Business Media.

关键词： MRAC system Lyapunov theory Convergence model reference adaptive control Converge design improvement adjustable parameter Lyapunov methods plants

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Dynamic Braking control for Accurate Train Braking Distance Estimation under Different Operating Conditions

Dynamic Braking Control for Accurate Train Braking Distance ...

引用

作者： Ahmad, Husain Abdulrahman Virginia Polytechnic Institute and State University

学位级别：Ph.D.

The application of model reference adaptive control (MRAC) for train dynamic braking is investigated in order to control dynamic braking forces while remaining within the allowable adhesion and coupler forces. This control method can accurately determine the train braking distance. One of the critical factors in Positive Train control (PTC) is accurately estimating train braking distance under different operating conditions. Accurate estimation of the braking distance will allow trains to be spaced closer together, with reasonable confidence that they will stop without causing a collision. This study develops a dynamic model of a train consist based on a multibody formulation of railcars, trucks (bogies), and suspensions. The study includes the derivation of the mathematical model and the results of a numerical study in Matlab. A three-railcar model is used for performing a parametric study to evaluate how various elements will affect the train stopping distance from an initial speed. Parameters that can be varied in the model include initial train speed, railcar weight, wheel-rail interface condition, and dynamic braking force. Other parameters included in the model are aerodynamic drag forces and air brake forces. An MRAC system is developed to control the amount of current through traction motors under various wheel/rail adhesion conditions while braking. Minimizing the braking distance of a train requires the dynamic braking forces to be maximized within the available wheel/rail adhesion. Excessively large dynamic braking can cause wheel lockup that can damage the wheels and rail. Excessive braking forces can also cause large buff loads at the couplers. For DC traction motors, an MRAC system is used to control the current supplied to the traction motors. This motor current is directly proportional to the dynamic braking force. In addition, the MRAC system is also used to control the train speed by controlling the synchronous speed of the AC traction motors. The

关键词： Dynamic Braking Traction Motors Wheel/Rail Adhesion Train Braking Distance Longitudinal Train Dynamics model reference adaptive control

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adaptive control for linear uncertain systems with unmodeled dynamics revisited via optimal control modification

Adaptive control for linear uncertain systems with unmodeled...

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AIAA Guidance, Navigation, and control (GNC) Conference

作者： Nguyen, Nhan NASA Ames Research Center Intelligent Systems Division Moffett Field CA 94035 United States

ISBN: (纸本)9781624102240

This paper presents the optimal control modification for linear uncertain plants. The Lyapunov analysis shows that the modification parameter has a limiting value depending on the nature of the uncertainty. The optimal control modification exhibits a linear asymptotic property that enables it to be analyzed in a linear time invariant framework for linear uncertain plants. The linear asymptotic property shows that the closedloop plants in the limit possess a scaled input-output mapping. Using this property, we can derive an analytical closed-loop transfer function in the limit as the adaptive gain tends to infinity. The paper revisits the Rohrs counterexample problem that illustrates the nature of non-robustness of model-reference adaptive control in the presence of unmodeled dynamics. An analytical approach is developed to compute exactly the modification parameter for the optimal control modification that stabilizes the plant in the Rohrs counterexample. The linear asymptotic property is also used to address output feedback adaptive control for non-minimum phase plants with a relative degree 1.

关键词： model reference adaptive control

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What is L1 adaptive control

What is L1 adaptive control

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AIAA Guidance, Navigation, and control (GNC) Conference

作者： Jafari, Saeid Ioannou, Petros A. Rudd, Lael University of Southern California Department of Electrical Engineering United States Northrop Grumman Systems Corporation United States

ISBN: (数字)9781624102240

ISBN: (纸本)9781624102240

Recently, a class of adaptive control schemes called L1 adaptive control (L1-AC) has been proposed and widely advertised in aerospace control for achieving fast and robust adaptation and better performance than the existing model reference adaptive control (MRAC) Schemes. The L1-AC scheme is designed mainly for plants with full state measurement even though the name L1-AC has been used as an umbrella name for more general classes of plants. In this paper, we show that the L1-AC for plants with measured states is simply a standard MRAC with a low pass filter inserted in front of the control input. The analysis of the scheme is almost identical to that of MRAC as the same Lyapunov function is used to establish stability. The motivation for using the filter is the fact that for this class of adaptive schemes i.e. MRAC for plants with full state measurement the tracking error can be made arbitrarily small during transient by increasing the adaptive gain. A high adaptive gain however makes the differential equation of the adaptive law or estimator very stiff and leads to numerical problems that cause high oscillations in the estimated parameters leading to loss of adaptivity and deviations from what the theoretical properties dictate. The L1-AC approach mistook these numerical oscillations as properties of the adaptive scheme and inserted an input low pass filter in order to filter them out. While the filter helps reduce the frequency of these oscillations in the control law the price paid is high. First the numerical instability does not go away and the estimated parameters continue to oscillate without converging to the true parameters even in the presence of suffciently rich signals. Second, due to the filter the tracking error is no longer guaranteed to converge to zero and the transient bounds for the tracking error also depend on the filter. As a result, the tracking properties of the L1-AC scheme are worse than what a simple MRAC scheme can generate with adaptive

关键词： model reference adaptive control

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Fault tolerant control for a second order LPV system using adaptive control methods

Fault tolerant control for a second order LPV system using a...

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5th IFAC Symposium on System Structure and control, SSSC 2013

作者： Vargas-Martínez, Adriana Garza-Castanón, Luis Puig, Vicenç Morales-Menendez, Ruben Tecnologico de Monterrey Campus Monterrey Av. Garza Sada 2501 64849 Mexico Mexico Universitat Politécnica de Catalunya C/ Llorens i Artigas 4-6 08034 Barcelona Spain

ISBN: (纸本)9783902823250

A Fault Tolerant control (FTC) reconfigurable structure for a second order nonlinear process is developed. This structure is based on a model reference adaptive control (MRAC) with a H∞, Gain Scheduling controller designed using an Linear Parameter-Varying (LPV) system: MRAC-H ∞GS-LPV. The MRAC-H∞GS-LPV was compared with a structure named MRAC-LPV that is based on an MRAC design using an LPV system. A coupled-tank system is used as testbed in which different types of faults (abrupt-additive fault, gradual-additive fault and multiplicative fault) with different magnitudes and different operating points were tested. Results showed that the use of an H∞, GS controller in combination with an MRAC improves the FTC performance because fault accommodation is faster. In addition, the structures based on Lyapunov theory were able to deal more efficiently with the faults and the changes in the operating points of the nonlinear model of the system. © 2013 IFAC.

关键词： model reference adaptive control

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model reference adaptive position controller with Smith predictor for a shaking-table in two axes

Model reference adaptive position controller with Smith pred...

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11th Mexican International Conference on Artificial Intelligence, MICAI 2012

作者： Esparza, Carlos Núñez, Rafael González, Fabio Unidades Tecnológicas de Santander - UTS Research Group on Advanced Control - GICAV Bucaramanga Santander Colombia

ISBN: (纸本)9783642377976

In structural behavior, the analysis of civil buildings by seismic tests has been generalized by the use of shaking tables. This method requires advanced control systems. In our research we show the implementation of a model reference adaptive control (MRAC) to control the position of a shaking table, modified by the introduction of a Smith predictor to compensate the error produced by the system delay. The mechanic is based on a Slider-crank device. The control system is implemented on a 32 bits platform by Microchip, and the control is done via a remote server using the RENATA network. The results of our adaptive control system were experimentally verified using the shaking table with a 24 kg mass as a load. © 2013 Springer-Verlag.

关键词： model reference adaptive control

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A digital RMRAC controller based on a modified RLS algorithm applied to the control of the output currents of an LCL-filter connected to the grid

A digital RMRAC controller based on a modified RLS algorithm...

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2013 15th European Conference on Power Electronics and Applications, EPE 2013

作者： Tambara, Rodrigo V. Massing, Jorge R. Pinheiro, Humberto Grundling, Hilton A. Grupo de Eletrônica de Potência e Controle Universidade Federal de Santa Maria Cidade Universitária Av. Roraima 1000 Camobi CEP 97105-900 Santa Maria RS Brazil

ISBN: (纸本)9781479901166

This paper proposes a digital Robust model reference adaptive control (RMRAC) applied to control the output current (by the grid side) of a three-phase LCL-filter to applications in static converters connected to electric grid. The proposed controller is based on a modified RLS algorithm applied to adaptation of the controller gains. Experimental results show the good performance of the proposed control system. © 2013 IEEE.

关键词： model reference adaptive control

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Concurrent Learning adaptive control of the aeroelastic generic transport model

Concurrent Learning Adaptive Control of the aeroelastic gene...

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AIAA Infotech at Aerospace (I at A) Conference

作者： Quindlen, John How, Jonathan Chowdhary, Girish Nguyen, Nhan Yucelen, Tansel Massachusetts Institute of Technology Department of Aeronautics and Astronautics Cambridge MA 02139 United States Oklahoma State University Stillwater OK 7407 United States NASA Ames Research Center Advanced Control and Evolvable Systems Group Moffett Field CA 9403 United States Missouri University of Science and Technology Mechanical and Aerospace Engineering Department Rolla MO 6540 United States

This paper presents a multiple-input Concurrent Learning model reference adaptive control (CL-MRAC) approach applied to longitudinal dynamics of the generic transport model (GTM) aircraft. A reduced order model of the short period flight dynamics coupled with structural bending and torsion is used. This aeroelastic model of the commercial passenger aircraft incorporates parametric uncertainties for mass and structural stiffness affecting both the structural dynamics and coupling. CL-MRAC with nonparametric Budgeted Kernel Restructuring (BKR) assigns centers and regressor vectors dynamically. The CL controller is used alongside an optimal tracking controller to enforce performance criteria on the rigid body dynamics. Results from this method demonstrate new insights into the application of large scale CL-MRAC implementations that arise from multiple-input multiple-output (MIMO) models.

关键词： model reference adaptive control

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Adjustable output voltage Zeta converter using neural network adaptive model reference control

Adjustable output voltage Zeta converter using neural networ...

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2011 2nd International Conference on control, Instrumentation and Automation, ICCIA 2011

作者： Moaveni, B. Abdollahzadeh, H. Mazoochi, M. Iran University of Science and Technology Iran Department of Electrical Engineering East Tehran Branch Islamic Azad University Iran Iran Telecommunications Research Centre Iran

ISBN: (纸本)9781467316903

Zeta converters are the fourth-order DC-DC converters capable of operating in both step-up and step-down modes and do not suffer from the polarity reversal problem. There are many applications which require a variable output voltage commanded by an external reference signal. So, the Zeta converters can be particularly useful for such applications. To achieve a Zeta converter with adjustable output voltage capable of following an external reference signal smoothly and accurately, there will be a need for a suitable control system. Since the Zeta converter model that is used in this paper is nonlinear, we propose a combination scheme of model reference adaptive control (MRAC) with neural networks (NN). In this paper, we propose and design a neural network adaptive model reference controller to control the output voltage of Zeta converter. Simulation results show the effectiveness of the proposed scheme for the Zeta converters with adjustable output voltage. © 2011 IEEE.

关键词： model reference adaptive control

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model reference adaptive fault tolerant control of a quadrotor UAV

Model reference adaptive fault tolerant control of a quadrot...

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AIAA Infotech at Aerospace Conference and Exhibit 2011

作者： Chamseddine, Abbas Zhang, Youmin Rabbath, Camille-Alain Fulford, Cameron Apkarian, Jacob Concordia University Montreal QC H3G 1M8 Canada Defence Research and Development Canada Valcartier QC G3J 1X5 Canada Quanser Consulting Inc Markham ON L3R 5H6 Canada Department of Mechanical and Industrial Engineering 1515 St. Catherine West United States Department of National Defense 2459 Boul. Pie XI North United States

ISBN: (纸本)9781600869440

This paper presents some experimental results on actuator fault-tolerant control (FTC) for a quadrotor Unmanned Aerial Vehicle (UAV) system. The strategy is based on model reference adaptive control (MRAC) where three different MRAC techniques are implemented and compared with a Linear Quadratic Regulator (LQR) baseline controller, namely the MIT rule MRAC, the Conventional MRAC (C-MRAC) and the Modified MRAC (M-MRAC). The main advantage of the MRAC strategy is that it does not require an explicit information about the fault location and/or amplitude and thus, a fault detection and diagnosis module is not needed to detect, isolate and identify the occurred faults. The performance of this MRAC-based FTC is tested in the presence of three types of actuator faults: loss of effectiveness in the total thrust, loss of effectiveness in one of the rotors and partial damage of one propeller. © 2011 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

关键词： model reference adaptive control

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