Results 131 to 140 of about 406 (166)
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IEEE Transactions on Automatic Control, 1990
A globally asymptotically stable VS-MRAC for the general case of plants with arbitrary relative degree is presented. It is shown that the VS approach leads to general adaptive controllers with outstanding performance. The controllers use only I/O measurements and are free of differentiators.
Liu Hsu
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A globally asymptotically stable VS-MRAC for the general case of plants with arbitrary relative degree is presented. It is shown that the VS approach leads to general adaptive controllers with outstanding performance. The controllers use only I/O measurements and are free of differentiators.
Liu Hsu
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7. DUAL MODEL REFERENCE ADAPTIVE CONTROL (MRAC)
Lecture Notes in Control and Information Sciences, 2004Nikolai M. Filatov, Heinz Unbehauen
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Model Reference Adaptive Control (MRAC) for dual-axis solar tracker applied in CPV
Solar Energy Materials and Solar CellsS.I. Palomino-Resendiz +4 more
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B-MRAC: A New Model Reference Adaptive Controller Based on Binary Control Theory
IFAC Proceedings Volumes, 1991Abstract This paper reviews and extends earlier results on input/output based variable structure adaptive control algorithms and its binary (in the sense of Emelyanov) version The latter was formulated only for the case of plants with relative degree one. Here a new controller is proposed for the general case of arbitrary relative degree.
Liu Hsu, R.R. Costa
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Model Reference Adaptive Controller (MRAC) for a Double Line-Sensors Mobile Robot
2024 International Conference on Connected Innovation and Technology (ICCITX)Nhu Thanh Vo +4 more
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Model reference adaptive control (MRAC) of heat processes with simultaneous plant indentification
Proceedings of 1995 34th IEEE Conference on Decision and Control, 2002This work presents a control law for heat processes which on one hand does not require second spacial derivatives for its on-line computation (unlike that of Hong and Bentsman, 1994) and on the other hand permits on-line plant parameter estimation (unlike that of Orlov, 1993).
Y. Orlov, J. Bentsman
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Model reference adaptive control (MRAC) implementation for an industrial pilot stirrer process
2017 IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI), 2017Modeling of flow process in various tanks and vessels is one of the most common problems in the process industry. In this paper adaptive control is implemented for the CSTR process. The CSTR process is a classic example of a highly nonlinear system. Inflow rate is taken as the input data and process level is taken as the output for CSTR. The input flow
Ajith B. Singh +2 more
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Analysis of memristor based model reference adaptive controller (MRACs)
2014 International Conference on Control, Instrumentation, Communication and Computational Technologies (ICCICCT), 2014In this paper, for the first time, we propose an adaptive controller based on a new electrical element “Memristor” which will not only improve the system stability and performance, but also maintain that stability for a longer time, irrespective of different perturbation factors.
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BPD computation and model reference adaptive control (MRAC) of Hammerstein plants
IEE Proceedings - Control Theory and Applications, 1995Summary: A large class of control strategies relies on computation of the output gradient vector. Recently the concept of block partial derivatives (BPD) and the associated algebra have been introduced to facilitate the computation of the gradient vector in nonlinear systems. We propose a simpler procedure for BPD computation.
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2-DOF Planar Motion Control System Using Model Reference Adaptive Control (MRAC) Algorithm
Volume 9: Micro- and Nano-Systems Engineering and Packaging, Parts A and B, 2012This paper reports the application of Model Reference Adaptive Control (MRAC) to an X-Y planar motion mechanism. A flexure-based 2-DOF planar motion platform is first developed for the wafer probing purpose and a planar Voice Coil Motor (VCM) is used for driving the mechanism and the flexural bearings. The dynamics of the motion platform is governed by
Andrew M. Y. Luk +2 more
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