Results 231 to 240 of about 13,098 (275)

Adaptation rates for MRAC systems

International Journal of Control, 1989
Abstract A method for predicting the adaptation rate of a single-input, hyperstability-based, MRAC system is developed. Assuming a slowly changing input and output, this rate follows well-defined root loci. A straightforward method for choosing adaptation gains results. The derived theory was applied to a laboratory experiment which involved a DC motor
JACOB S. GLOWER, ROBERT E. FENTON
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Robustness of MRAC schemes

Proceedings of the 1997 American Control Conference (Cat. No.97CH36041), 1997
A standard model reference adaptive control (MRAC) scheme is inherently robust with respect to L/sup /spl infin///spl cap/L/sup 2/ disturbances in the sense that all closed-loop signals are bounded and the tracking error is in L/sup /spl infin///spl cap/L/sup 2/. A MRAC scheme with a new adaptive law is inherently robust with respect to disturbances in
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Model updating improves MRAC performance

IEEE Transactions on Automatic Control, 1984
The performance of an MRAC design can be improved by using the model- updating concept, which places the state of the system into the reference model at regular time intervals. This paper discusses criteria for determining this updating and a proof is given to show that model updating does not influence the stability properties of an MRAC design.
van den Bosch, P. P. J., Tjahjadi, P. I.
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MRAC with reduced state information

IFAC Proceedings Volumes, 2004
Abstract Direct adaptive control algorithms using state variables in control structure are known for their good adaptation capability and tracking performances that result from the fact that they use plant state variables in control law as well as in adaptation law.
Michal Gonos, Ján Murgaš, Eva Miklovičová   +2 more
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Chromidotilapia mrac

2003
Published as part of Anton Lamboj, 2003, Chromidotilapia melaniae and C. nana, two new cichlid species (Perciformes, Cichlidae) from Gabon, Central Africa., pp.
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Global adaptive output feedback MRAC

Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference, 2009
A robust adaptive output feedback (OFB) dynamic inversion control strategy is presented that achieves global asymptotic tracking of a reference model. The considered system contains linearly parameterizable uncertainty in the state and input matrices. The dynamic model also includes an unknown, nonlinear disturbance, which does not satisfy the linear ...
W. MacKunis, Z. D. Wilcox, M. K. Kaiser, W. E. Dixon   +3 more
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Experimental Comparison of Two Composite MRAC Methods for UUV Operations With Low Adaptation Gains

IEEE Journal of Oceanic Engineering, 2020
In today's underwater environment, complex missions, such as underwater repair and docking operations, require precise control to maneuver unmanned underwater vehicles (UUVs) in extremely demanding operating conditions.
C. D. Makavita, S. Jayasinghe, H. Nguyen, D. Ranmuthugala   +3 more
semanticscholar   +1 more source

MRAC ALGORITHM FOR HIGH RELATIVE DEGREE PLANTS

IFAC Proceedings Volumes, 1995
Abstract The principal aim of this paper is to present a new algorithm for the control of continuous time linear systems with a large relative degree and unknown parameters. If the standard approach is used for these systems, the controller structure is very complicated and implementation is problematic.
J. Murgaš, M. Matejovič, V. Červenka
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Experiments Toward MRAC Design for Linkage System

IFAC Proceedings Volumes, 1996
In most machine design, a planar linkage is synthesized to achieve a specific trajectory of motion. However, the dynamics of the planar linkage is shown to be highly nonlinear due to the asymmetry of the geometrical structure and external loads are often present in the output link; thus, the tracking of the prescribed trajectory is difficult to achieve
Ming-chang Lin, Jian-Shiang Chen
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Gain margins of multivariable MRAC systems

2008 47th IEEE Conference on Decision and Control, 2008
This paper studies the gain margins (GM) of multivariable model reference adaptive control (MRAC) systems: the parameter range of a control gain matrix in a designed MRAC system for maintaining the desired closed-loop signal boundedness and asymptotic output tracking.
null Qian Sang, null Gang Tao
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