TY - GEN
T1 - Initialization of fractional order systems for the joint estimation of parameters and fractional differentiation orders
AU - Bahloul, Mohamed
AU - Belkhatir, Zehor
AU - Laleg-Kirati, Taous-Meriem
N1 - KAUST Repository Item: Exported on 2022-09-14
PY - 2022/9/5
Y1 - 2022/9/5
N2 - It has been recognized that the initialization of fractional-order systems requires time-varying functions. This factor is very intricate and affects the convergence properties of the parameters and fractional differentiation order estimation. For this reason, we propose a novel technique to simplify the pre-initialization process of fractional differential system by designing an appropriate initialization function that ensures the fast and precise convergence to the exact states of the systems. Subsequently, we present a joint estimation approach of the parameters and the fractional differentiation order for initialized fractional-order systems. The performance of the proposed method is illustrated through different numerical examples. Furthermore, a potential application of the algorithm is presented, which consists of joint estimation of parameters and fractional differentiation order of a fractional-order arterial Windkessel model.
AB - It has been recognized that the initialization of fractional-order systems requires time-varying functions. This factor is very intricate and affects the convergence properties of the parameters and fractional differentiation order estimation. For this reason, we propose a novel technique to simplify the pre-initialization process of fractional differential system by designing an appropriate initialization function that ensures the fast and precise convergence to the exact states of the systems. Subsequently, we present a joint estimation approach of the parameters and the fractional differentiation order for initialized fractional-order systems. The performance of the proposed method is illustrated through different numerical examples. Furthermore, a potential application of the algorithm is presented, which consists of joint estimation of parameters and fractional differentiation order of a fractional-order arterial Windkessel model.
UR - http://hdl.handle.net/10754/680991
UR - https://ieeexplore.ieee.org/document/9867456/
U2 - 10.23919/acc53348.2022.9867456
DO - 10.23919/acc53348.2022.9867456
M3 - Conference contribution
BT - 2022 American Control Conference (ACC)
PB - IEEE
ER -