DocumentCode :
3221372
Title :
Application of local deformations in adaptive control — A comparative survey
Author :
Tar, József K.
Author_Institution :
Inst. of Intell. Eng. Syst., Budapest Tech Polytech. Instn., Budapest, Hungary
fYear :
2009
fDate :
26-29 Jan. 2009
Firstpage :
25
Lastpage :
38
Abstract :
In this paper a brief survey is provided on a novel approach to adaptive nonlinear control developed at Budapest Te c h in the past few years. The most popular branches of the classical and novel adaptive approaches are analyzed in comparison with methods needing complete, accurate, and permanent models or applying only partial, incomplete, temporal, and situation-dependent ones that require continuous refreshment via observing the behavior of the controlled system in the actual situation. It will be shown how simple geometric considerations can be used for developing iterative learning control. It will also be shown that in the case of the novel approach the conditions of convergence normally can be satisfied by choosing very primitive initial system models and roughly chosen control parameters on the basis of simple geometric considerations. It will be pointed out that while the traditional adaptive approaches are applicable only for learning linearly separable dynamical system parameters and fail for the permanent presence of unknown external disturbances and linearly non-separable (e.g. friction model) parameters, the novel approach can well compensate the simultaneous effects of imprecise and linearly non-separable model parameters and external perturbations, too. Since in contrast to the traditional solutions that normally guarantee global (asymptotic) stability by using Lyapunov functions, the novel approach can assure only local region of stability that in principle can be left by the system´s state, a real time simulation tool has been developed to study the robustness of the novel control versus the variation of the adaptive control parameters. It will also be stressed that the traditional approaches have a huge number of adaptive control parameters that generally cannot optimally be set, the novel approach have only a few control parameters that can easily be tuned by observing the behavior of the controlled system. The already achieved results will be e- xemplified by simulation studies using the same paradigm.
Keywords :
adaptive control; iterative methods; learning systems; nonlinear control systems; Lyapunov functions; adaptive control; iterative learning control; nonlinear control; Adaptive control; Asymptotic stability; Control system synthesis; Control systems; Convergence; Optimal control; Programmable control; Robust stability; Stress control; Tellurium;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Cybernetics, 2009. ICCC 2009. IEEE International Conference on
Conference_Location :
Palma de Mallorca
Print_ISBN :
978-1-4244-5310-8
Electronic_ISBN :
978-1-4244-5311-5
Type :
conf
DOI :
10.1109/ICCCYB.2009.5393937
Filename :
5393937
Link To Document :
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