Multistage Adomian Decomposition Method Research Articles

Theoretical and Experimental Investigation of Thermal Dynamics of Steinhart–Hart Negative Temperature Coefficient Thermistors

The temperature-dependent dynamics of a negative temperature coefficient (NTC) thermistor conducting variable electric current is modeled using the differential approach. The thermistor is assumed to follow the Steinhart–Hart resistance-temperature equation. The developed mathematical model consists of a nonlinear differential-algebraic equations system, and it was analyzed by the Adomian decomposition method (ADM) and its time-marching version known as the multistage Adomian decomposition method (MADM) as well as the Dormand–Prince (DP) numerical method. Five sets of experiments were conducted on five different NTC thermistors and the laboratory measurements were compared with the model predictions. It is demonstrated that the proposed model, when combined with the MADM, can accurately simulate the thermal behavior of the NTC thermistors. The MADM reproduces the experimental temperature dynamics of the five NTC thermistors with an average absolute relative error of about 2.601% while the corresponding errors for the DP method and the classic ADM are 8.122% and 51.255%, respectively. Also, it is shown that the MADM is highly efficient in terms of computational efficiency and it is approximately 6.5 times faster than the classic DP method, when tuned appropriately.

Application of Multi-Stage Homotopy Analysis Method for Power System Dynamic Simulations

Homotopy analysis method (HAM) is a popular semi-analytical method used widely in applied sciences. It stands out from the rest of the semi-analytical methods as it provides a family of solutions to nonlinear equations, including ordinary differential equations (ODEs), partial differential equations, etc. The convergence characteristics of the solutions can be varied by changing an auxiliary parameter ( $\hbar$ ) in HAM. The convergence region of solution of ODEs using HAM can be improved by applying it over multiple intervals of time, which is referred to as multi-stage HAM (MHAM). In this paper, MHAM models for the IEEE Model 2.2 synchronous machine, IEEE Type-1 excitation system, first-order governor and first-order turbine models have been developed. The applicability of MHAM for power system dynamic simulations has been investigated in this paper using seven widely used test systems ranging from 10 generators 39 bus systems to 4092 generators 13 659 bus systems. The effect of number of terms, $\hbar$ and the time step on the accuracy and stability of the solution has been studied. The effectiveness of MHAM has been compared with the modified Euler (ME) and midpoint Trapezoidal (TrapZ) methods. The accuracy of MHAM has been found to be comparable with ME and TrapZ methods for the values of $\hbar$ between $-$ 1.05 and $-$ 0.95. The best accuracy is obtained for $\hbar$ = $-$ 1.0, which is a special case of MHAM called multi-stage homotopy perturbation method (MHPM). In this paper, it is also shown that MHPM is equivalent to multi-stage adomian decomposition method, which has been recently explored for large power system simulations.

Large Multi-Machine Power System Simulations Using Multi-Stage Adomian Decomposition

Multi-stage Adomian decomposition method (MADM) is a proven semi-analytical approximation solution technique for ordinary differential equations (ODEs), which provides a rapidly convergent series by integrating over multiple time intervals. Applicability of MADM for large nonlinear differential algebraic systems (DAEs) is established for the first time in this paper using the partitioned solution approach. Detailed models of power system components are approximated using MADM models. MADM applicability is verified on 7 widely used test systems ranging from 10 generators, 39 buses to 4092 generators, 13659 buses. Impact of the step size and the number of terms is investigated on the stability and accuracy of the method. An average speed up of 42% and 26% is observed in the solution time of ODEs alone using the MADM when compared to the midpoint-trapezoidal (TrapZ) method and the modified-Euler (ME) method, respectively. MADM accuracy is found to be similar to the ME and comparable to the TrapZ method. MADM stability properties are found to be better than the ME and weaker than the TrapZ method. An average speed up of 13% and 5.85% is observed in the overall solution time using MADM w.r.t. TrapZ and ME methods, respectively.

Chaos control in the cerium-catalyzed Belousov–Zhabotinsky reaction using recurrence quantification analysis measures

Chaos control in the Belousov–Zhabotinsky-CSTR system was investigated theoretically and experimentally by reconstructing the phase space of the cerium (IV) ions concentration time series and then optimizing recurrence quantification analysis measures. The devised feedback loop acting on the reactor inlet flow rate was able to experimentally suppress chaos and drive the system to an almost predictable state with approximately 93% determinism. Similar theoretical results have also been demonstrated in numerical simulations using the four-variable Montanator model as solved by the multistage Adomian decomposition method.

Analytical approximate solutions for a general nonlinear resistor–nonlinear capacitor circuit model

In this paper, the analytical approximate solutions of a general RC circuit comprised of a nonlinear resistor in series with a nonlinear capacitor are addressed. In the studied circuit, the capacitor is characterized by a quintic polynomial voltage–charge dependence and the resistor obeys a cubic polynomial voltage–current relation. An efficient and easy-to-implement algorithm based on a hybrid analytical–numerical mathematical technique, namely the multistage Adomian decomposition method (MADM) is applied for solving the nonlinear differential equation governing the circuit performance. It is shown that the classic Adomian decomposition method fails to provide accurate convergent solutions for the posed problem over the whole semi-infinite time domain; however, the MADM can easily achieve convenient solutions with any desired degree of accuracy for both the transient and steady state time zones by exploiting its two embedded precision adjustment parameters. For the sake of illustration, two relevant numerical examples are solved by the MADM and simulated by the MATLAB–Simulink, as well. The results by the MADM are evaluated as highly accurate, based on comparison. In addition to the circuit theory aspects, the present work might be of particular interest from a practical point of view as the quintic nonlinear capacitor typically represents the widely used ferroelectric ceramic capacitors.

A reliable algorithm for positive solutions of nonlinear boundary value problems by the multistage Adomian decomposition method

AbstractIn this paper, we present a reliable algorithm to calculate positive solutions of homogeneous nonlinear boundary value problems (BVPs). The algorithm converts the nonlinear BVP to an equivalent nonlinear Fredholm– Volterra integral equation.We employ the multistage Adomian decomposition method for BVPs on two or more subintervals of the domain of validity, and then solve the matching equation for the flux at the interior point, or interior points, to determine the solution. Several numerical examples are used to highlight the effectiveness of the proposed scheme to interpolate the interior values of the solution between boundary points. Furthermore we demonstrate two novel techniques to accelerate the rate of convergence of our decomposition series solutions by increasing the number of subintervals and adjusting the lengths of subintervals in the multistage Adomian decomposition method for BVPs.

Comments on the Adomian Decomposition Methods Applied to the KdV Equation

Based on previous works, especially [1] and [2], we try in the present contribution to study some new aspects of the numerical solution of the KdV equation through the standard Adomian Decomposition Method. The use of the multistage Adomian Decomposition Method, applied to this equation, will be presented and discussed.

Multistage Adomian Decomposition Method for Solving NLP Problems Over a Nonlinear Fractional Dynamical System

This paper deals with implementation of the multistage Adomian decomposition method (MADM) to solve a class of nonlinear programming (NLP) problems, which are reformulated with a nonlinear system of fractional differential equations. The multistage strategy is used to investigate the relation between an equilibrium point of the fractional order dynamical system and an optimal solution of the NLP problem. The preference of the method lies in the fact that the multistage strategy gives this relation in an arbitrary longtime interval, while the Adomian decomposition method (ADM) gives the optimal solution just only in the neighborhood of the initial time. The numerical results taken by the fractional order MADM show that these results are compatible with the solution of NLP problem rather than the ADM. Furthermore, in some cases the fractional order MADM can perform more rapid convergency to the optimal solution of optimization problem than the integer order ones.

Piecewise finite series solutions of seasonal diseases models using multistage Adomian method

The aim of this paper is to apply the multistage Adomian Decomposition Method MADM to solve systems of nonautonomous nonlinear differential equations that describe several epidemic models with periodic behavior. Here the concept of the MADM is introduced and then it is employed to obtain a piecewise finite series solution. The MADM is used here as a hybrid analytical–numerical technique for approximating the solutions of the epidemic models. In order to show the efficiency of the method, the obtained numerical results are compared with the fourth-order Runge–Kutta method solutions. Numerical comparisons show that the MADM is accurate, easy to apply and the calculated solutions preserve the periodic behavior of the continuous models. Moreover, the method has the advantage of giving a functional form of the solution for any time interval. Furthermore, it is shown that if the truncation order and the time step size are not properly chosen large computational work is required and inaccurate solutions may be obtained.

Solution of prey–predator problem by numeric–analytic technique

In this paper, an analytical expression for the solution of the prey–predator problem by an adaptation of the classical Adomian decomposition method (ADM). The ADM is treated as an algorithm for approximating the solution of the problem in a sequence of time intervals, i.e. the classical ADM is converted into a hybrid numeric–analytic method called the multistage ADM (MADM). Numerical comparisons with the classical ADM, and the classical fourth-order Rungge–Kutta (RK4) methods are presented.

Solving Riccati differential equation using Adomian's decomposition method

In this paper, we suggest a method to solve the matrix Riccati differential equation. The suggested method, which we called multistage Adomian's decomposition method (MADM), can be considered as an extension of the Adomian's decomposition method (ADM) which is very efficient in solving a variety of differential and algebraic equations. The solution is introduced in a recursive form which can be used to obtain the solution for the whole time horizon. Comparisons are made between MADM and the exact solution and further between MADM and different numerical methods.