Decentralized neural identification and control for uncertain nonlinear systems: Application to planar robot

2010 ◽  
Vol 347 (6) ◽  
pp. 1015-1034 ◽  
Author(s):  
Fernando Ornelas Tellez ◽  
Alexander G. Loukianov ◽  
Edgar N. Sanchez ◽  
Eduardo Jose Bayro Corrochano
Keyword(s):  
Nonlinear Systems ◽  
Uncertain Nonlinear Systems ◽  
Planar Robot ◽  
And Control

Control of Uncertain Nonlinear Systems

1993 ◽  
Vol 115 (2B) ◽  
pp. 362-372 ◽  
Author(s):  
Martin Corless
Keyword(s):  
Nonlinear Systems ◽  
Theoretical Approach ◽  
Uncertain Systems ◽  
Lyapunov Theory ◽  
Uncertain Nonlinear Systems ◽  
Aerospace Systems ◽  
Nonlinear Uncertain Systems ◽  
And Control

This paper describes some of my research in the analysis and control of nonlinear uncertain systems in which the uncertainties are modeled deterministically rather than stochastically. The main applications are to mechanical/aerospace systems, such as robots and spacecraft; the underlying theoretical approach is based on Lyapunov theory.

scholarly journals LMI–Based Robust Control of Uncertain Nonlinear Systems via Polytopes of Polynomials

2019 ◽  
Vol 29 (2) ◽  
pp. 275-283 ◽  
Author(s):  
Marcelino Sánchez ◽  
Miguel Bernal
Keyword(s):  
Nonlinear Systems ◽  
Space Representation ◽  
Linear Matrix ◽  
Uncertain Nonlinear Systems ◽  
Linear Parameter Varying ◽  
Analysis And Design ◽  
Linear Parameter Varying Systems ◽  
State Space Representation ◽  
The Subject ◽  
And Control

Abstract This investigation is concerned with robust analysis and control of uncertain nonlinear systems with parametric uncertainties. In contrast to the methodologies from the field of linear parameter varying systems, which employ convex structures of the state space representation in order to perform analysis and design, the proposed approach makes use of a polytopic form of a generalisation of the characteristic polynomial, which proves to outperform former results on the subject. Moreover, the derived conditions have the advantage of being cast as linear matrix inequalities under mild assumptions.

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