This paper deals with stabilization of unknown nonlinear systems using a nonlinear controller made with a backpropagation neural network.
The controllability and stabilization of an unknown system have been considered. Though it is initiated using local rank conditions, the range of validity ...
This paper deals with stabilization of unknown nonlinear systems using a nonlinear controller made with a backpropagation neural network.
This paper presents an online modeling and control strategy for a class of linearizable nonlinear systems with unknown parameters and nonlinearities.
Jun 4, 2022 · This paper proposes a learning framework to simultaneously stabilize an unknown nonlinear system with a neural controller and learn a neural Lyapunov function.
Discover how to stabilize unknown nonlinear discrete-time fixed state delay systems using Chebyshev neural networks. Learn about the weight update law and ...
Abstract. This contribution considers an adaptive control method based on a cognition-based framework to stabilize unknown nonlinear systems in real time.
A neural-network-based direct control architecture is presented that achieves output tracking for a class of continuous-time nonlinear plants.
Missing: Stabilization | Show results with:Stabilization
An adaptive output feedback stabilizing control law is derived for unknown nonlinear systems, using their equivalent DNN model, with guaranteed closed-loop ...
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In this paper we provide a neural-based semi-global stabilization design for unknown nonlinear state-feedback stabilizable systems.