Adaptive control of A class of nonlinear systems with guaranteed parameter estimation: A concurrent learning based approach
[ X ]
Tarih
2024
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Wiley
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Recent advances in concurrent learning based adaptive controllers have relaxed the persistency of excitation condition required to achieve exponential tracking and parameter estimation error convergence. This was made possible via the use of additional concurrent learning stacks in the parameter estimation algorithm. However, the proposed concurrent learning components, that is, the history stacks, needed to be filled with selected values dependent on the actual system states. Therefore, the previously proposed concurrent learning adaptive controllers required the system to be stable initially for a finite time so that the corresponding history stacks can be filled (finite excitation condition). In this work, motivated to remove the finite excitation condition, a novel desired system state based concurrent learning adaptive controller is proposed. In order to remove the system state dependencies in the controller and estimation algorithms, a filtered version of the dynamics and a novel prediction error formulation have been designed. The overall exponential stability, parameter error convergence and boundedness of the system states during closed loop operations are ensured via Lyapunov based arguments. The main advantages of the proposed method are its dependence on the desired system states and the overall stability results that paved the way in removing the need for finite excitation condition. Numerical studies performed on a two link robotic device are also presented to illustrate the feasibility of the proposed method. Significant research is achieved by ensuring output tracking along with accurate identification of uncertain parametric uncertainties. In a novel departure from the existing literature, the need for persistency of excitation condition is eliminated. image
Açıklama
Anahtar Kelimeler
adaptive control, adaptive estimation, identification, Lyapunov methods
Kaynak
Iet Control Theory and Applications
WoS Q Değeri
Q2
Scopus Q Değeri
Q1
Cilt
18
Sayı
10
