Results 251 to 260 of about 1,034,955 (303)

Hierarchical model reference adaptive control systems

Proceedings of 1995 34th IEEE Conference on Decision and Control, 2002
This paper presents a hierarchical model reference adaptive control algorithm for a class of complex nonlinear systems. The complex system concerned is represented by a family of local transfer function models, which are smoothly combined together by characteristic basis functions.
G. Feng, S.G. Cao, N.W. Rees
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Neural network-based model reference adaptive control system

IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), 2000
In this paper, an approach to model reference adaptive control based on neural networks is proposed and analyzed for a class of first-order continuous-time nonlinear dynamical systems. The controller structure can employ either a radial basis function network or a feedforward neural network to compensate adaptively the nonlinearities in the plant.
H D, Patino, D, Liu
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Model Reference Adaptive Control of Large Structural Systems

Journal of Guidance, Control, and Dynamics, 1983
Summary: Model reference adaptive control procedures that do not require explicit parameter identification are considered for large structural systems. Although such applications have been shown to be feasible for multivariable systems, provided there exists a feedback gain matrix which makes the resulting input/output transfer function strictly ...
Bar-Kana, I., Kaufman, H., Balas, M.
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Closed-loop Reference Model based Distributed Model Reference Adaptive Control for Multi-agent Systems

2021 American Control Conference (ACC), 2021
This paper confluences ideas from distributed model reference adaptive control (MRAC) architecture for multi-agent systems and closed-loop reference model (CRM) based MRAC algorithm. The concept of CRM is recently proposed in literature for single-agent MRAC problems, where the reference model (leader) gets feedback from the plant (agent/follower) to ...
Raghavv Goel, Sayan Basu Roy
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Discrete model reference adaptive control systems

International Journal of Control, 1978
Abstract A synthesis technique is presented for stable discrete model reference adaptive control systems. In the adaptive system the process parameters are adjusted indirectly according to a discrete gradient law. The stability of the adaptive scheme is demonstrated by Liapunov's second method.
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Adaptive stabilization systems with several reference models

Optoelectronics, Instrumentation and Data Processing, 2008
Properties of SISO adaptive stabilization systems with different types of reference model for prescribing dynamic and static characteristics are discussed. The influence of the model structure that forms the input action on the control signal is considered.
O. Ya. Shpilevaya, E. V. Ivanenko
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Model reference adaptive control system hyperstability analysis

1993 (25th) Southeastern Symposium on System Theory, 2002
The stability of the model reference adaptive control system with external disturbance and unmodeling is discussed. Instead of Lyapunov's method, more general results have been acquired for the analysis of hyperstability. It is shown that if only the linear forward block can be made strictly positive real, then the globally asymptotical hyperstability ...
Z. Chuan, J.E. Fagan
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Bifurcation in model reference adaptive control systems

Systems & Control Letters, 1988
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Golden, Melinda P., Ydstie, B. Erik
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MODEL REFERENCE ADAPTIVE SYSTEM ESTIMATES FOR COUNTING PROCESSES

Statistica Neerlandica, 1986
AbstractThe adaptive estimation procedure of the model reference adaptive system is modified and applied to counting process models. Maximum likelihood estimates constitute a subclass of the adaptive estimators considered. The adaptive estimator is shown to be strongly consistent and to converge in law to a normal variate.
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Model reference adaptive control of advertising systems

2017 American Control Conference (ACC), 2017
Internet advertising is a relatively new area where feedback control has become critically important for scalable optimization. But using feedback control in this space is challenging due to nonlinear, time-varying, and uncertain plants. In this paper we propose a high-fidelity model reference adaptive controller for reference tracking of budget ...
Jiaxing Guo, Niklas Karlsson
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