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In this project, an observer in the form of a stable neural network is proposed for any nonlinear MIMO system. As a result of experience, this observer utilizes a nonlinear in parameter neural network (NLPNN) which unlike LPNN, supports systems with higher degree of nonlinearity with no pre-knowledge of its dynamics. The learning rule for this n…
A Generalized H-infinity Mixed Sensitivity Convex Approach to Multivariable Control Design Subject to Simultaneous Output and Input Loop-Breaking Specifications
This repository contains some of the codes developed during the course on Model Predictive Control (MPC) (2022.1) - Master's Program in Electrical Engineering - Federal University of Ceara.
Implementation of a recurrent neural network based Observer/Identifier for highly Non-Linear Dynamical Systems, using the Lorenz Attractor as a test case.