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An adaptive control scheme using two multiple layered feedforward neural networks (FFNN) is proposed to control completely unknown dynamical systems. A critic ...
ABSTRACT -An adaptive control scheme using two multiple layered feedforward neural networks (FFNN) is proposed to control completely unknown dynamical ...
Reinforcement learning control of unknown dynamic systems
digital-library.theiet.org › ip-d.1993.0042
The work is focused on the design of a learning automaton using subsets of control actions to reduce the number of actions during a learning procedure. The ...
Abstract—In this paper we discuss discrete-time H2 control for unknown nonlinear system. We use recurrent neural networks to model the system identification ...
Abstract—This paper develops an intelligent control method based on reinforcement learning techniques for unknown nonlin- ear continuous-time systems in an ...
ABSTRACTAn adaptive control scheme using two multiple layered feedforward neural networks (FFNN) is proposed to control completely unknown dynamical systems ...
Reinforcement learning control of unknown dynamic systems
digital-library.theiet.org › ip-d.1993.0042
The paper is concerned with the application of reinforcement learning techniques to the stochastic control problem.
This paper develops an intelligent control method based on reinforcement learning techniques for unknown nonlinear continuous-time systems in an adversarial ...
Jan 3, 2024 · We introduce NODEC, a novel framework for controlling unknown dynamical systems, which combines dynamics modelling and controller training using a coupled ...
Sep 30, 2022 · This thesis intends to provide an in-depth introduction of Deep Learning using Neural Networks combined with Reinforce- ment Learning ...