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Neural Network for Complex Systems: Theory and Applications

Chenguang Yang, Jing Na, Guang Li, Yanan Li, Junpei Zhong
2018 Complexity  
Yu presented an adaptive neural output feedback control scheme for uncertain robot manipulators with input saturation using the radial basis function neural network (RBFNN) and disturbance observer.  ...  Wang et al. focused on neural learning from the adaptive neural control (ANC) for a class of flexible joint manipulator with unknown dynamics under the output tracking error constraint. X.  ...  Acknowledgments The guest editors would like to acknowledge and appreciate the authors and the reviewers for their contribution towards the success of this special issue.  ... 
doi:10.1155/2018/3141805 fatcat:sow2l3fzhvecjaolirojt4cbjm

Normalized Neural Network for Energy Efficient Bipedal Walking Using Nonlinear Inverted Pendulum Model

Ruobing Wang, Samuel J. Hudson, Yao Li, Hongtao Wu, Chengxu Zhou
2019 2019 IEEE International Conference on Robotics and Biomimetics (ROBIO)  
To obviate the need of solving non-linear dynamics on-line, a deep neural network is adopted for fast non-linear mapping from desired states to control variables.  ...  Normalized dimensionless data is generated to train the neural network, therefore, the trained neural network can be applied to bipedal robots of any size, without any specific modification.  ...  NEURAL NETWORK DESIGN WITH IPM A.  ... 
doi:10.1109/robio49542.2019.8961646 dblp:conf/robio/WangHL0Z19 fatcat:gw33hs3hbzfhzcyfnzjfu54ll4

Exponential stability of discrete‐time delayed neural networks with saturated impulsive control

Zhilong He, Chuandong Li, Zhengran Cao, Hongfei Li
2021 IET Control Theory & Applications  
This paper examines the problem of the locally exponentially stability for impulsive discrete-time delayed neural networks (IDDNNs) with actuator saturation.  ...  Moreover, when saturation constraints are not considered in the impulsive controller, the stability of the system is also discussed.  ...  ACKNOWLEDGEMENTS This work was supported by National Key Research and Development Project (2018AAA0100101), and National Natural Science Foundation of China (61633011, 61873213).  ... 
doi:10.1049/cth2.12147 fatcat:mxumm52hsnhtthgix2bnr2rcnq

Special Issue "Complex Dynamic System Modelling, Identification and Control"

Quanmin Zhu, Giuseppe Fusco, Jing Na, Weicun Zhang, Ahmad Taher Azar
2022 Entropy  
Systems are naturally or purposely formed with functional components and connection structures [...]  ...  Conflicts of Interest: The authors declare no conflict of interest.  ...  As always, the research topics associated with this SI are quite widely demanded, from academic research to real applications, particularly in those manmade systems (e.g., engineering products).  ... 
doi:10.3390/e24030380 pmid:35327891 pmcid:PMC8947381 fatcat:ujmscwlup5a4feuo2kl7wivr44

Time-delayed impulsive control for discrete-time nonlinear systems with actuator saturation

Liangliang Li, Chuandong Li, Wei Zhang
2019 Nonlinear Analysis: Modelling and Control  
This paper focuses on the problem of time-delayed impulsive control with actuator saturation for discrete-time dynamical systems.  ...  dynamical systems via time-delayed impulsive controller with actuator saturation.  ...  While in some other models arising from digital communication, neural networks and ecological models, delayed impulses also have potential applications [4] .  ... 
doi:10.15388/na.2019.5.7 fatcat:vlp74luqtjbjjcsiqkziuk65ce

Neural Network Based Central Heating System Load Prediction and Constrained Control

Hongwei Wang, Fangwen Tu, Baofeng Tu, Guohui Feng, Guangming Yuan, Hao Ren, Jiarong Dong
2018 Mathematical Problems in Engineering  
A neural network (NN) based heating system load prediction and control scheme are proposed.  ...  The excellent performance of the novelly proposed control over traditional PID is demonstrated via extensive simulation study.  ...  Acknowledgments This work is supported by Natural Science Guide Foundation of Liaoning Province under Project no. 20170540747.  ... 
doi:10.1155/2018/2908608 fatcat:rjq3qbzcgfa7hfgmgfmska4n5q

Neural network models of velocity storage in the horizontal vestibulo-ocular reflex

Thomas J. Anastasio
1991 Biological cybernetics  
The neural network models demonstrate how commissural inhibition may be organized along the VOR pathway.  ...  The networks exhibit some of the nonlinear properties of the actual VOR, such as dependency of decay rate and phase lag upon input magnitude, and skewing of the response to higher magnitude sinusoidal  ...  Williams for helpful conversations on the implementation of the learning algorithm. This work was supported by the Faculty Research and Innovation Fund of the University of Southern California.  ... 
doi:10.1007/bf00201979 pmid:2004129 fatcat:imgajetc5ndilkhkshhgwips3e

Multiresolution GPC-Structured Control of a Single-Loop Cold-Flow Chemical Looping Testbed

Shu Zhang, Joseph Bentsman, Xinsheng Lou, Carl Neuschaefer, Yongseok Lee, Hamza El-Kebir
2020 Energies  
The rate constraint on the control signal in the temporal control law is then imposed and the control topology is augmented by an additional control loop with self-tuning deadbeat controller which uses  ...  This process complexity is addressed in the present work through the temporal and the spatiotemporal multiresolution modeling along with the corresponding model-based control laws.  ...  MRA has become one of the major tools in neural networks [7,8,9,10] and nonlinear system modeling [11,12,13,14,15,16,17,18].  ... 
doi:10.3390/en13071759 pmid:32582408 pmcid:PMC7314368 fatcat:fvolzxak4bfrpfct5jdw23amyu

Editorial Biologically Learned/Inspired Methods for Sensing, Control, and Decision

Yongduan Song, Jennie Si, Sonya Coleman, Dermot Kerr
2022 IEEE Transactions on Neural Networks and Learning Systems  
[A6] present a diversified multiclustered echo state network and apply it to deal with modeling uncertainties and coupling nonlinearities in the control systems.  ...  constraint.  ... 
doi:10.1109/tnnls.2022.3161003 fatcat:4e6v2kclcbb5pgkqqsyyaiwzjy

Modelling event-related responses in the brain

Olivier David, Lee Harrison, Karl J. Friston
2005 NeuroImage  
This generative model was a neural mass model of hierarchically arranged areas using three kinds of inter-area connections (forward, backward and lateral).  ...  We investigated how responses, at each level of a cortical hierarchy, depended on the strength of connections or coupling.  ...  canonical networks in terms of their impulse response functions.  ... 
doi:10.1016/j.neuroimage.2004.12.030 pmid:15808977 fatcat:ombkdmtf6vb7joyiy3h37mjbb4

Mathematical models for pain: a systematic review [article]

Victoria Ashley Lang, Torbjörn Lundh, Max Ortiz-Catalan
2020 arXiv   pre-print
After screening for inclusion of mathematical or computational models of pain, 31 articles were deemed relevant.  ...  Although understudied, the development of mathematical models may augment the current understanding of pain by providing directions for testable hypotheses of its underlying mechanisms.  ...  Conflict of Interest: The first and second authors report no conflict of interest. The last author served as a consultant for Integrum AB.  ... 
arXiv:2006.01745v1 fatcat:tgniiuadxjfqfiuipgux3j5t6e

A survey on anti-disturbance control of switched systems with input saturation

Yunliang Wei, Shengsen Jia, Kunming Liu
2020 Systems Science & Control Engineering  
of anti-disturbance control of switched systems with input saturation.  ...  Then it introduces the research status and development of dynamic analysis at home and abroad, including the research status of system control under input saturation constraints and the research status  ...  , which is in combination with disturbance observer based control, adaptive neural network control and robust H ∞ control in .  ... 
doi:10.1080/21642583.2020.1740113 fatcat:2hnboji3ufdzjhi7pntn5fzttu

Development of artificial neural network classifier to identify military impulse noise

Brian A. Bucci, Jeffrey S. Vipperman
2006 Journal of the Acoustical Society of America  
In this thesis, classifiers based on artificial neural networks were developed to improve the accuracy of military impulse noise identification.  ...  A separate effort attempted to identify military impulse noise by the shape of the recorded waveform.  ...  Department of Defense, through the Strategic Environmental Research and Development Program (SERDP). x  ... 
doi:10.1121/1.4786620 fatcat:3b44xdopfvbqloivspkhmjkq5a

Review: CPG as a controller for biomimetic floating robots [article]

A. I. Zharinov, Y. A. Tsybina, S. Y. Gordleeva
2021 arXiv   pre-print
The organization of such a system in living organisms is responsible for networks of interconnected populations of neurons capable of forming rhythmic activity - CPG.  ...  Each separate section deals with a certain kind. At the same time, the works are arranged in the chronological order of their publication.  ...  The presented CPG model consists of three functional layers, namely the input saturation functions, coupled neural oscillators and the output transient function.  ... 
arXiv:2112.07295v1 fatcat:hfpj3xe56jhvvaefmurywg4jxy

Synchronization in complex networks and its application – A survey of recent advances and challenges

Yang Tang, Feng Qian, Huijun Gao, Jürgen Kurths
2014 Annual Reviews in Control  
We focus on robustness of synchronization, controllability and observability of complex networks and synchronization of multiplex networks.  ...  This paper attempts to present an overview of recent progress of synchronization of complex dynamical networks and its applications.  ...  This research is supported by the National 973 Project (2012CB720500), the National Natural Science Foundation of China (61203235, 61333012, 61333010, 61273201), the Key Laboratory of Integrated Automation  ... 
doi:10.1016/j.arcontrol.2014.09.003 fatcat:w74pynfdojekpgaqgfhd32guqq
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