The adaptive iterative learning algorithm for boundary control scheme includes a proportional-derivative (PD) feedback structure and an iterative term.
The proposed control schemes are based upon the use of a proportional-derivative (PD) feedback structure, for which an iterative term is added to cope with the unknown parameters and disturbances.
Here, we introduce a new norm ∥ ⋅ ∥ β and give another direct way to deal with the iterative term in the nonlinear term, which can be regarded as the main novelty in this paper.
For the existence results of solutions for problem (3), we emphasize that the main difficulty from the fractional order derivative D 0, t q c x and iterative term x ( λ x in f.
Compared with the results and methods in [9, 18], one can find that: (i) we introduce a new norm ∥ ⋅ ∥ β and give another direct way to deal with the iterative term x ( λ x in f, which can be regarded as the main novelty in this paper; (ii) we derive new existence and uniqueness results for a general class of fractional order differential equations.
The primitive iterative method (termed base method) has convergence-order (CO) five and then we describe a matrix polynomial of degree two to design a multi-step method.
In a second step, this model was extended by an iterative long term wear model to analyze the changes in radius deviations over a long operating period.
For semi-global disparity estimation, the aim of this disparity space model is first to find the position of minimum disparity cost in horizontal direction from x = 1 to x = W by using horizontal iterative smooth term.
In [11], the optimization problem of the irregular LDPC degree profiles on AWGN channels was formulated as a duality-based convex optimization problem, and an iterative method termed density evolution was proposed to solve the problem.
Note Another iterative method termed HAAR (Haugazeau-like Averaged Alternating Reflections) for finding the projection onto intersection of finitely many closed convex sets in a Hilbert space can be found in [[20], Remark 3.4 iii)].
In an iterative manner, termed a sifting process, EMD extracts the highest frequency oscillation (finest temporal scale) from the underlying time-series, referred to as an intrinsic mode function.
