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Page 7531 of Mathematical Reviews Vol. , Issue 2000j [page]

2000 Mathematical Reviews  
, CA) An optimal control theory for discrete event systems.  ...  They develop polynomial- time controller synthesis algorithms for discrete event systems that can be modeled by finite state machines.  ... 

Functional Differential and Difference Equations with Applications

Josef Diblík, Elena Braverman, István Györi, Yuriy Rogovchenko, Miroslava Růžičková, Ağacık Zafer
2012 Abstract and Applied Analysis  
delays, mean square exponential stability of stochasticswitched systems with interval time-varying delays, global exponential stability of periodic solutions to neural networks and impulsive neural networks  ...  with time-varying delays, and stability of impulsive stochastic functional differential systems.  ...  delays, mean square exponential stability of stochasticswitched systems with interval time-varying delays, global exponential stability of periodic solutions to neural networks and impulsive neural networks  ... 
doi:10.1155/2012/986585 fatcat:ssexk5oiybgpxcjqmer7w7tsoe

Optimal Operation for Reduced Energy Consumption of an Air Conditioning System Using Neural Inverse Optimal Control

Flavio Muñoz, Ramon Garcia-Hernandez, Jose Ruelas, Juan E. Palomares-Ruiz, Carlos Álvarez-Macías
2022 Mathematics  
In this paper, a discrete-time neural inverse optimal control scheme for trajectories tracking and reduced energy consumption of a DX A/C system is presented.  ...  The dynamic model of the plant is approximated by a recurrent high-order neural network (RHONN) identifier. Using this model, a discrete-time neural inverse optimal controller is designed.  ...  Applications of this complete control scheme are illustrated in: [33], where an optimal inverse neural control for discrete-time impulsive systems is determined.  ... 
doi:10.3390/math10050695 fatcat:eby7ohe6srbbbfke63ub5ku4vi

A multiresolution tracking control design for non-minimum phase systems

Zongxuan Sun, Tsu-Chin Tsao
2000 Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334)  
This paper investigates inversion of non-minimum phase systems using multiresolution analysis for tracking control.  ...  Impulse response of non-minimum phase systems is first decomposed into wavelet basis functions.  ...  Yang et. al. (1997) presented a multiresolution neural network to identify impulse response of linear time invariant systems using input and output data.  ... 
doi:10.1109/acc.2000.878946 fatcat:anmx266dzvc67ktfx3mslug5ai

2020 Index IEEE Transactions on Neural Networks and Learning Systems Vol. 31

2020 IEEE Transactions on Neural Networks and Learning Systems  
The Author Index contains the primary entry for each item, listed under the first author's name.  ...  ., +, TNNLS Aug. 2020 2930-2941 Discrete time systems H 3 Static Output-Feedback Control Design for Discrete-Time Systems Using Reinforcement Learning.  ...  ., +, TNNLS June 2020 2140-2152 Adaptive Neural Networks Finite-Time Optimal Control for a Class of Nonlinear Systems.  ... 
doi:10.1109/tnnls.2020.3045307 fatcat:34qoykdtarewhdscxqj5jvovqy

Nonlinear Autoregressive Moving Average-L2 Model Based Adaptive Control of Nonlinear Arm Nerve Simulator System

2020 Journal of Information Engineering and Applications  
This paper considers the trouble of the usage of approximate strategies for realizing the neural controllers for nonlinear SISO systems.  ...  The nonlinear autoregressive moving average (NARMA-L2) model is an precise illustration of the input-output behavior of finite-dimensional nonlinear discrete time dynamical systems in a neighborhood of  ...  The controller then calculates the control input that will optimize plant performance over a targeted destiny time horizon.  ... 
doi:10.7176/jiea/10-3-03 fatcat:sv5pefxe45hehmgbzyu4nqahp4

Nonlinear Autoregressive Moving Average-L2 Model Based Adaptive Control of Nonlinear Arm Nerve Simulator System

2020 Innovative Systems Design and Engineering  
This paper considers the trouble of the usage of approximate strategies for realizing the neural controllers for nonlinear SISO systems.  ...  The nonlinear autoregressive moving average (NARMA-L2) model is an precise illustration of the input-output behavior of finite-dimensional nonlinear discrete time dynamical systems in a neighborhood of  ...  The controller then calculates the control input that will optimize plant performance over a targeted destiny time horizon.  ... 
doi:10.7176/isde/11-2-02 fatcat:u4uo6ltcbvedxpauyzyhqkkrda

Adaptive Inverse Model of Nonlinear Systems

Prachee Patnaik, Debi Prasad Das, Santosh Kumar Mishra
2015 International Journal of Intelligent Systems and Applications  
Inverse modeling has been an important component for sensor linearization, adaptive control, channel equalization in communication system and active noise control.  ...  This paper proposes nonlinear adaptive filter-bank (NAFB) based algorithm for inverse modeling of nonlinear systems.  ...  This adaptive filter is adapted to model the inverse system. Neural network based inverse model of nonlinear plants have been proposed for control applications [12] [13] .  ... 
doi:10.5815/ijisa.2015.05.06 fatcat:qxu5iyksenbr3hag2y54jqwpua

Learning Impulsive Pinning Control of Complex Networks

Alma Y. Alanis, Daniel Ríos-Rivera, Edgar N. Sanchez, Oscar D. Sanchez
2021 Mathematics  
In this paper, we present an impulsive pinning control algorithm for discrete-time complex networks with different node dynamics, using a linear algebra approach and a neural network as an identifier,  ...  The learning part of the control is done with a discrete-time recurrent high order neural network used for identification of the pinned nodes, which is trained using an extended Kalman filter algorithm  ...  Acknowledgments: The authors also thank Universidad de Guadalajara and CINVESTAV, Unidad Guadalajara for the support in this research.  ... 
doi:10.3390/math9192436 fatcat:77a3m4epxfgtper3eyc3pcnm2m

Subject Index 1993

1993 Journal of Guidance Control and Dynamics  
Discretization Formulas for Real-Time Simulation G93-085 Control System Design Optimal Control System Design with Prescribed Damping and Stability Characteristics G93-185 Inversion-Based Nonlinear Control  ...  Discretization Formulas for Real-Time Simulation G93-085 Saturating and Time-Optimal Feedback Con- trols G93-083 Optimal Discrete-Time Dynamic Output-Feed- back Design: A w-Domain Approach G93-082 Active  ... 
doi:10.2514/3.56621 fatcat:76b2r2m4bndvvmomgfwrajx7gm

Nonlinear Analysis of Dynamical Complex Networks 2014

Zidong Wang, Bo Shen, Hongli Dong, Jun Hu, Xiao He, Derui Ding
2014 Abstract and Applied Analysis  
For networked control systems (NCSs), especially largescale systems such as multiagent systems and systems over sensor networks, the complexities are inevitably enhanced in terms of their degrees or intensities  ...  Subsequently, in the paper entitled "Timeand event-driven communication process for networked control systems: a survey" by L.  ...  We would like to acknowledge all authors for their efforts in submitting high-quality papers. We are also very grateful to the reviewers for their thorough and on time reviews of the papers.  ... 
doi:10.1155/2014/976231 fatcat:4pf2zd4h35gazgo2vyhoawgyka

2019 Index IEEE Transactions on Systems, Man, and Cybernetics: Systems Vol. 49

2019 IEEE Transactions on Systems, Man & Cybernetics. Systems  
., +, TSMC Feb. 2019 333-345 Discrete time systems Consensus of Linear Discrete-Time Multi-Agent Systems: A Low-Gain Distributed Impulsive Strategy.  ...  ., +, TSMC July 2019 1408- 1418 Control systems Decentralized Adaptive Neural Approximated Inverse Control for a Class of Large-Scale Nonlinear Hysteretic Systems With Time Delays.  ...  Open loop systems  ... 
doi:10.1109/tsmc.2019.2956665 fatcat:xhplbanlyne7nl7gp2pbrd62oi

Nonlinear dynamical model based control of in vitro hippocampal output

Min-Chi Hsiao, Dong Song, Theodore W. Berger
2013 Frontiers in Neural Circuits  
This paper describes a modeling-control paradigm to control the hippocampal output (CA1 response) for the development of hippocampal prostheses.  ...  Laguerre-Volterra kernel models for random-interval, graded-input, contemporaneous-graded-output system are formulated and applied to build the DG-CA1 trajectory model and the CA1 plant model.  ...  ACKNOWLEDGMENTS This work was supported in part by the NSF (BMES ERC and BITS Program), DARPA (HAND Project), ONR (Adaptive Neural System Program), NIBIB, and the Brain Restoration Foundation.  ... 
doi:10.3389/fncir.2013.00020 pmid:23429994 pmcid:PMC3576714 fatcat:fgztltw7gjhqrewatlawaabwoa

Feedforward Control Based on Neural Networks for Hard Disk Drives

Xuemei Ren, F.L. Lewis, Jingliang Zhang, S.S. Ge
2009 IEEE transactions on magnetics  
Our feedforward control can be regarded as a nonlinear finite impulse response (FIR) that corresponds to linear FIR when the basis function of the neural network is linear.  ...  Index Terms-Feedforward control, hard disk drives, neural networks.  ...  It should be noted that the model for the hard disk drive is expressed in continuous-time domain, but the practical control algorithm is generally implemented in discrete-time domain.  ... 
doi:10.1109/tmag.2009.2015660 fatcat:lshuqtlflncxvo7tc2ou6lq7qa

Neural network approach to reduce dynamic measurement errors

Andrei Sergeevich Volosnikov, Aleksandr L. Shestakov
2016 ACTA IMEKO  
<p>The neural network inverse model of a sensor with filtration of the sequentially recovered signal is considered.  ...  The result of the experimental data processing of a dynamic temperature measurement validates the efficiency of the proposed neural network approach to reduce dynamic measurement errors.</p>  ...  However, the analysis of measuring systems can be made in terms of the control theory [4] , as well as of the theory of automatic control systems sensitivity [5] , [6] .  ... 
doi:10.21014/acta_imeko.v5i3.294 fatcat:2i3s7uclwjan7mrps3c5tsfgem
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