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This paper deals with the fractional closed-loop system identification. A comparison between the direct and the indirect approach is processed. The fractional order bias eliminated least squares method is used to identify the fractional closed-loop transfer function. This method is founded on the ordinary least squares method and the state variable filter. A numerical example is treated to show the...
In this paper, the fractional closed-loop system identification using the indirect approach is presented. A bias correction method is developed to deal with the bias problem in the continuous-time fractional closed-loop system identification. This method is based on the least squares estimator combined with the state variable filter approach. The basic idea is to eliminate the estimation bias by adding...
The paper deals with the continuous-time fractional closed-loop system identification in a noisy output context. Both coefficients and fractional orders of the process are estimated using the direct approach. The proposed method is based on the least squares technique and the state variable filter. It is an extension of the bias eliminated least squares method to the fractional systems. It is combined...
This paper deals with continuous-time fractional closed-loop system identification in a noisy output context. A bias correction method called the bias-eliminated least squares is extended for indirect approach identification of closed-loop system with fractional models. This method is based on the least squares method combined with the state variable filter and assumes that the regulator order can...
This paper presents a new ellipsoidal set-membership method for the identification of linear fractional orders systems. It use the Optimal Bounding Ellipsoid (OBE) algorithm. When the probability distribution of the disturbances is unknown but bounded and when the differentiation orders are known, the proposed method can estimate all the feasible parameters. A numerical example shows the effectiveness...
A global optimization technique for identifying an output-error fractional order model is proposed. The proposed technique use a modified version of Hansen algorithm. It is capable of estimating the fractional orders and the parameters, with guaranteed convergence. The technique is applied to identify a fractional order system in deterministic and stochastic context.
Fractional differentiation systems are characterized by the presence of non-exponential aperiodic multimodes. Although rational orthogonal bases can be used to model any L2[0,∞[ system, they fail to quickly capture the aperiodic multimode behavior with a limited number of terms. Hence, fractional orthogonal bases are expected to better approximate fractional models with fewer parameters. Intuitive...
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