Literature DB >> 24808463

Adaptive dynamic output feedback neural network control of uncertain MIMO nonlinear systems with prescribed performance.

Artemis K Kostarigka, George A Rovithakis.   

Abstract

An adaptive dynamic output feedback neural network controller for a class of multi-input/multi-output affine in the control uncertain nonlinear systems is designed, capable of guaranteeing prescribed performance bounds on the system's output as well as boundedness of all other closed loop signals. It is proved that simply guaranteeing a boundedness property for the states of a specifically defined augmented closed loop system is necessary and sufficient to solve the problem under consideration. The proposed dynamic controller is of switching type. However, its continuity is guaranteed, thus alleviating any issues related to the existence and uniqueness of solutions. Simulations on a planar two-link articulated manipulator illustrate the approach.

Mesh:

Year:  2012        PMID: 24808463     DOI: 10.1109/TNNLS.2011.2178448

Source DB:  PubMed          Journal:  IEEE Trans Neural Netw Learn Syst        ISSN: 2162-237X            Impact factor:   10.451


  1 in total

Review 1.  Application of Reinforcement Learning and Deep Learning in Multiple-Input and Multiple-Output (MIMO) Systems.

Authors:  Muddasar Naeem; Giuseppe De Pietro; Antonio Coronato
Journal:  Sensors (Basel)       Date:  2021-12-31       Impact factor: 3.576

  1 in total

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