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Boundary layer function is introduced to construct an auxiliary error variable, which relaxes the identical initial condition assumption of iterative learning control.
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The system of three coupled equations of motion is transformed into two uncoupled equations introducing a boundary layer function.
The nonlinear governing equations are reformulated using a stress function and a boundary layer function, and solved by employing a multi-parameter perturbation technique and Fourier series method.
Based on the boundary layer function method, a class of generalized high-dimensional delayed systems in the critical case is studied.
In this paper, using the boundary layer function method, we consider the asymptotic behavior of solution for the problem, and the formal asymptotic solution is also constructed.
The formal asymptotic solution is constructed by using the method of boundary layer functions.
In Fuzzy SMC, variable boundary layer (( varphi )) is a function of S and ( dot{S}(t) ) [13].
The thickness of the low latitude boundary layer (LLBL) is studied as a function of interplanetary magnetic field (IMF) using the data of THEMIS mission.
It also arises in the study of the mixed convection in porous media [2], where η is the similarity boundary layer ordinate, f is the similarity stream function, f ′ and f ″ are the velocity and the shear stress functions, respectively.
The model and its dependence on the dimensionless parameters describing the system are derived from first principles except for the compressible boundary layer, which is described by a simple function whose magnitude is empirically determined by fitting experimental data.
Thickness of the momentum boundary layer is an increasing function of Re < 0. Figure 3 demonstrates quite the opposite trend for the injection case.
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