NDLI: Recurrent-Neural-Network-Based Multivariable Adaptive Control for a Class of Nonlinear Dynamic Systems With Time-Varying Delay

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Guest Editorial Special Issue on Neurodynamic Systems for Optimization and Applications

A Bi-Projection Neural Network for Solving Constrained Quadratic Optimization Problems

Taylor

$O(h^{3})$

Discretization of ZNN Models for Dynamic Equality-Constrained Quadratic Programming With Application to Manipulators

A Neurodynamic Approach for Real-Time Scheduling via Maximizing Piecewise Linear Utility

Optimization in Quaternion Dynamic Systems: Gradient, Hessian, and Learning Algorithms

A New Continuous-Time Equality-Constrained Optimization to Avoid Singularity

$L_{1}$

-Norm Low-Rank Matrix Decomposition by Neural Networks and Mollifiers

Zeroth-Order Method for Distributed Optimization With Approximate Projections

Nonsmooth Neural Network for Convex Time-Dependent Constraint Satisfaction Problems

A Generalized Hopfield Network for Nonsmooth Constrained Convex Optimization: Lie Derivative Approach

Optimal Formation of Multirobot Systems Based on a Recurrent Neural Network

The Kernel Adaptive Autoregressive-Moving-Average Algorithm

Brain Dynamics in Predicting Driving Fatigue Using a Recurrent Self-Evolving Fuzzy Neural Network

Bayesian Recurrent Neural Network for Language Modeling

Twin Neurons for Efficient Real-World Data Distribution in Networks of Neural Cliques: Applications in Power Management in Electronic Circuits

Recurrent-Neural-Network-Based Multivariable Adaptive Control for a Class of Nonlinear Dynamic Systems With Time-Varying Delay

Nonlinear Model Predictive Control Based on a Self-Organizing Recurrent Neural Network

A Combined Adaptive Neural Network and Nonlinear Model Predictive Control for Multirate Networked Industrial Process Control

Optimal Communication Network-Based

$H_infty $

Quantized Control With Packet Dropouts for a Class of Discrete-Time Neural Networks With Distributed Time Delay

QoS Differential Scheduling in Cognitive-Radio-Based Smart Grid Networks: An Adaptive Dynamic Programming Approach

Data-Driven Zero-Sum Neuro-Optimal Control for a Class of Continuous-Time Unknown Nonlinear Systems With Disturbance Using ADP

Synchronization and State Estimation of a Class of Hierarchical Hybrid Neural Networks With Time-Varying Delays

A Switching Approach to Designing Finite-Time Synchronization Controllers of Coupled Neural Networks

Stability of Analytic Neural Networks With Event-Triggered Synaptic Feedbacks

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Year : 2013 Volume : 24

Year : 2012 Volume : 23

Recurrent-Neural-Network-Based Multivariable Adaptive Control for a Class of Nonlinear Dynamic Systems With Time-Varying Delay

Content Provider	IEEE Xplore Digital Library
Author	Chih-Lyang Hwang Chau Jan
Copyright Year	2012
Abstract	At the beginning, an approximate nonlinear autoregressive moving average (NARMA) model is employed to represent a class of multivariable nonlinear dynamic systems with time-varying delay. It is known that the disadvantages of robust control for the NARMA model are as follows: 1) suitable control parameters for larger time delay are more sensitive to achieving desirable performance; 2) it only deals with bounded uncertainty; and 3) the nominal NARMA model must be learned in advance. Due to the dynamic feature of the NARMA model, a recurrent neural network (RNN) is online applied to learn it. However, the system performance becomes deteriorated due to the poor learning of the larger variation of system vector functions. In this situation, a simple network is employed to compensate the upper bound of the residue caused by the linear parameterization of the approximation error of RNN. An e-modification learning law with a projection for weight matrix is applied to guarantee its boundedness without persistent excitation. Under suitable conditions, the semiglobally ultimately bounded tracking with the boundedness of estimated weight matrix is obtained by the proposed RNN-based multivariable adaptive control. Finally, simulations are presented to verify the effectiveness and robustness of the proposed control.
Page Count	14
File Size	2778899
Starting Page	388
Ending Page	401
File Format	PDF
ISSN	2162237X
Volume Number	27
Issue Number	2
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2016-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Nonlinear dynamical systems Delays Autoregressive processes Recurrent neural networks Switches Time-varying systems Approximation methods recurrent neural network (RNN). Lyapunov stability theory multivariable sliding-mode control nonlinear autoregressive moving average (NARMA) recurrent neural network (RNN)
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Computer Networks and Communications Computer Science Applications Software

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RBF Neural Network Sliding Mode Control for Passification of Nonlinear Time-Varying Delay Systems with Application to Offshore Cranes

Adaptive Consensus Control for a Class of Nonlinear Multiagent Time-Delay Systems Using Neural Networks

Output-Feedback Adaptive Neural Control for Stochastic Nonlinear Time-Varying Delay Systems With Unknown Control Directions

Adaptive Neural Network Sliding Mode Control for a Class of SISO Nonlinear Systems

Neural Adaptive Sliding Mode Control for a Class of Nonlinear Neutral Delay Systems

Wavelet Neural Network-Based NARMA-L2 Internal Model Control Utilizing Micro-artificial Immune Techniques to Control Nonlinear Systems

Non-fragile sliding mode control of discrete switched singular systems with time-varying delays

Sliding mode observer for a class of globally Lipschitz non-linear systems with time-varying delay and noise in its output

Robust Sliding Mode Control for Nonlinear Discrete-Time Delayed Systems Based on Neural Network

Recurrent-Neural-Network-Based Multivariable Adaptive Control for a Class of Nonlinear Dynamic Systems With Time-Varying Delay

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