Locally recurrent globally feedforward networks: a critical review of architectures
In this paper, we will consider a number of local-recurrent-global-feedforward (LRGF)
networks that have been introduced by a number of research groups in the past few years …
networks that have been introduced by a number of research groups in the past few years …
Learning to adapt in dynamic, real-world environments through meta-reinforcement learning
Although reinforcement learning methods can achieve impressive results in simulation, the
real world presents two major challenges: generating samples is exceedingly expensive …
real world presents two major challenges: generating samples is exceedingly expensive …
Feedback stabilization of nonlinear systems
ED Sontag - Robust Control of Linear Systems and Nonlinear …, 1990 - Springer
1 Introduction Page 1 FEEDBACK STABILIZATION OF NONLINEAR SYSTEMS Eduardo D.
Sontag Abstract This paper surveys some well-known facts as well as some recent …
Sontag Abstract This paper surveys some well-known facts as well as some recent …
A low-complexity global approximation-free control scheme with prescribed performance for unknown pure feedback systems
CP Bechlioulis, GA Rovithakis - Automatica, 2014 - Elsevier
A universal, approximation-free state feedback control scheme is designed for unknown
pure feedback systems, capable of guaranteeing, for any initial system condition, output …
pure feedback systems, capable of guaranteeing, for any initial system condition, output …
High-order fully actuated system approaches: Part IV. Adaptive control and high-order backstepping
G Duan - International Journal of Systems Science, 2021 - Taylor & Francis
Three types of high-order system models with parametric uncertainties are introduced,
namely, the high-order fully actuated (HOFA) models, and the second-and high-order strict …
namely, the high-order fully actuated (HOFA) models, and the second-and high-order strict …
[PDF][PDF] Identification and control of dynamical systems using neural networks
SN Kumpati, P Kannan - IEEE Transactions on neural …, 1990 - maxim.ece.illinois.edu
The paper demonstrates that neural networks can be used effectively for the identification
and control of nonlinear dynamical systems. The emphasis of the paper is on models for …
and control of nonlinear dynamical systems. The emphasis of the paper is on models for …
Robust adaptive control of feedback linearizable MIMO nonlinear systems with prescribed performance
CP Bechlioulis, GA Rovithakis - IEEE Transactions on …, 2008 - ieeexplore.ieee.org
A novel robust adaptive controller for multi-input multi-output (MIMO) feedback linearizable
nonlinear systems possessing unknown nonlinearities, capable of guaranteeing a …
nonlinear systems possessing unknown nonlinearities, capable of guaranteeing a …
[图书][B] Adaptive fuzzy systems and control: design and stability analysis
LX Wang - 1994 - dl.acm.org
Adaptive fuzzy systems and control | Guide books skip to main content ACM Digital Library
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Provably safe and robust learning-based model predictive control
Controller design faces a trade-off between robustness and performance, and the reliability
of linear controllers has caused many practitioners to focus on the former. However, there is …
of linear controllers has caused many practitioners to focus on the former. However, there is …
Dynamic surface control for a class of nonlinear systems
D Swaroop, JK Hedrick, PP Yip… - IEEE transactions on …, 2000 - ieeexplore.ieee.org
A method is proposed for designing controllers with arbitrarily small tracking error for
uncertain, mismatched nonlinear systems in the strict feedback form. This method is another" …
uncertain, mismatched nonlinear systems in the strict feedback form. This method is another" …