Adaptive observers for unknown general nonlinear systems
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Summary
This paper addresses the nonlinear adaptive observer design for unknown general nonlinear systems with linearly parameterized neural networks whose weights are adaptively adjusted, and Lyapunov theory is used in order to guarantee stability for state estimation and NN weight errors.
- Type
- article
- Published
- 2001-10-01
- Cited by
- 24
- References
- 23
- OpenAlex
- https://openalex.org/W18244833
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:10870586
Keywords
Headaches, Monetary economics, Business, Economics, Medicine
References
- Neuro-Control Systems: Theory and Applications
- Adaptive Observer for Active Automotive Suspensions
- Stable Adaptive Systems
- Robust neural adaptive observer for MIMO nonlinear systems
- Neural networks for control and system identification
- A systematic approach to adaptive observer synthesis for nonlinear systems
- On the approximate realization of continuous mappings by neural networks
- Stable adaptive observers for nonlinear time-varying systems
- Adaptive observers with arbitrary exponential rate of convergence for nonlinear systems
- A dynamic recurrent neural-network-based adaptive observer for a class of nonlinear systems
- Original Contribution: Approximation of dynamical systems by continuous time recurrent neural networks
- Structurally dynamic wavelet networks for the adaptive control of uncertain robotic systems
- A simple observer for nonlinear systems applications to bioreactors
- Adaptive observers for single output nonlinear systems
- Identification and control of dynamical systems using neural networks
- Neural adaptive regulation of unknown nonlinear dynamical systems
- Tracking control of multi-input affine nonlinear dynamical systems with unknown nonlinearities using dynamical neural networks
- Systematic design of stable neural observers for a class of nonlinear systems
- High-order neural network structures for identification of dynamical systems
- Adaptive observers for active automotive suspensions: theory and experiment
Cited by
- Distributed Fuzzy and Stochastic Observers for Nonlinear Systems
- Self-organizing radial basis function networks for adaptive flight control and aircraft engine state estimation
- Adaptive observer for a large class of nonlinear systems with exponential convergence of parameter estimation
- A Neural-Network-Based Nonlinear Adaptive State-Observer for Pressurized Water Reactors
- Adaptive observers for TS fuzzy systems with unknown polynomial inputs
- Locally-accurate identification of nonlinear systems using output measurements
- Robust adaptive £ ∞ -gain neural filtering for non-linear systems in the presence of bounded disturbances
- Adaptive Estimation for a Class of Nonlinearly Parameterized Dynamical Systems
- Robust adaptive neural observer design for a class of nonlinear parabolic PDE systems
- Neural-network-based observer for turbine engine parameter estimation
- Design of a unified adaptive fuzzy observer for uncertain nonlinear systems
- Real-time implementation of Chebyshev neural network observer for twin rotor control system
- Dynamic neural network-based robust observers for uncertain nonlinear systems
- New natural observer applied to speed-sensorless DC servo and induction motors
- Adaptive SMC Design for Nonlinear Systems Based on Wavelet Observers
- Real-time implementation of state observers for twin rotor MIMO system: an experimental evaluation
- An RBFN-based observer for nonlinear systems via deterministic learning
- Controle Neural Robusto de Sistemas No-Lineares Gerais
- Modeling human skills to control dynamic systems
- Distributed Adaptive Observer for Discrete-Time LTI SISO System with Completely Unknown Periodic Input
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