Reference : Composite Learning Control With Application to Inverted Pendulums
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Electrical & electronics engineering
Composite Learning Control With Application to Inverted Pendulums
Pan, Lin mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
IEEE Conference Publications
IEEE International Conference - Chinese Automation Congress (CAC), 2015
IEEE Conference Publications
Chinese Automation Congress (CAC), 2015
from 26-11-2015 to 30-11-2015
Chinese Automation Congress (CAC), 2015
[en] Adaptive Control, Composite Learning, ; Interval Excitation, ; Exponential Stability
[en] Composite adaptive control (CAC) that integrates direct and indirect adaptive control techniques can achieve smaller tracking errors and faster parameter convergence compared with direct and indirect adaptive control techniques. However, the condition of persistent excitation (PE) still has to be satisfied to guarantee parameter convergence in CAC. This paper proposes a novel model reference composite learning control (MRCLC) strategy for a class of affine nonlinear systems with parametric uncertainties to guarantee parameter convergence without the PE condition. In the composite learning, an integral during a movingtime window is utilized to construct a prediction error, a linear filter is applied to alleviate the derivation of plant states, and both the tracking error and the prediction error are applied to update parametric estimates. It is proven that the closed-loop system achieves global exponential-like stability under interval excitation rather than PE of regression functions. The effectiveness of the proposed MRCLC strategy has been verified by the application to an inverted pendulum control problem.
Fonds National de la Recherche - FnR

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