Adaptation of homotopy-perturbation method for numeric–analytic solution of system of ODEs by Chowdhury, Md. Sazzad Hossien, Hashim, Ishak

“…The HPM is treated,for the first time, as an algorithm in a sequence of intervals (i.e., time step) for finding accurate approximate solutions of linear and nonlinear systems of ODEs. Numerical comparisons between the multistage Homotopy-Perturbation Method (MHPM) and the available exact solution and the classical fourth-order Runge–Kutta (RK4) method reveal that the new technique is a promising tool for linear and nonlinear systems of ODEs.…”
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The use of a partially simulated exothermic reactor to test nonlinear algorithms by Hussain, Mohd Azlan, Kittisupakorn, Paisan, Kershenbaum, L.

“…Two nonlinear control algorithms for controlling nonlinear systems include the receding horizon method and the nonlinear neural network inverse model methods. …”

Implementation of neural-network-based inverse-model control strategies on an exothermic reactor by Hussain, Mohd Azlan, Kittisupakorn, Paisan, Daosu, Wachira

“…This method is however highly dependent on the availability of the inverse of the system model under control, which are normally difficult to obtain analytically for nonlinear systems. Since neural networks have the ability to model many nonlinear systems including their inverses, their use in this control scheme is highly promising. …”
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Analytical treatment of system of linear and nonlinear PDEs by Homotopy-Perturbation method by Chowdhury, Md. Sazzad Hossien, Hashim, Ishak, Ismail, Ahmad Faris

“…In this paper, the homotopy-perturbation method (HPM) is employed to obtain approximate analytical solution to the linear and nonlinear systems of partial di®erential equations (PDEs). …”
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The multistage homotopy-perturbation method: A powerful scheme for handling the Chaotic Lorenz system by Chowdhury, Md. Sazzad Hossien

“…Numerical comparisons between the multistage homotopy-perturbation method (MHPM) and the classical fourth-order Runge-Kutta (RK4) method reveals that the new technique is a promising tool for the nonlinear systems of ODEs. …”
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The multistage homotopy-perturbation method: a powerful scheme for handling the Lorenz system by Chowdhury, Md. Sazzad Hossien, Hashim, Ishak, Momani, Shaher Mohammad

“…Numerical comparisons between the multistage homotopy-perturbation method (MHPM) and the classical fourth-order Runge–Kutta (RK4) method reveal that the new technique is a promising tool for the nonlinear systems of ODEs…”
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Robust control of underactuated systems: higher order integral sliding mode approach by ud Din, Sami, Khan, Qudrat, Rehman, Fazal ur, Akmeliawati, Rini

“…This paper presents a robust control design for the class of underactuated uncertain nonlinear systems. Either the nonlinearmodel of the underactuated systems is transformed into an input output formand then an integral manifold is devised for the control design purpose or an integral manifold is defined directly for the concerned class. …”
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Numerical Solutions of Radiation Effect on Magnetohydrodynamic Free Convection Boundary Layer Flow about a Solid Sphere with Newtonian Heating by Alkasasbeh, Hamzeh Taha, Mohd Zuki, Salleh

“…The basic equations of boundary layer are transformed into a non-dimensional form and reduced to nonlinear systems of partial differential equations are solved numerically using an implicit finite difference scheme known as the Keller-box method. …”
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Numerical Solutions of Free Convection Boundary Layer Flow on a Solid Sphere with Convective Boundary Conditions by Mohd Zuki, Salleh, Alkasasbeh, Hamzeh Taha, Razman, Mat Tahar, Roslinda, Nazar

“…The basic equations of boundary layer are transformed into a non-dimensional form and reduced to nonlinear systems of partial differential equations are solved numerically using an implicit finite difference scheme known as the Keller-box method. …”
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Computational Intelligence based techniques for islanding detection of distributed generation in distribution network: A review by Laghari, J.A., Mokhlis, Hazlie, Karimi, M., Bakar, Ab Halim Abu, Mohamad, H.

“…Computational intelligence based techniques, due to their robustness and flexibility in dealing with complex nonlinear systems, is an option that might solve this problem. …”

A Spherical Simplex Unscented Rauch-Tung Striebel Smoother for a Vehicle Localization Problem by Z., Zolkafli, Saifudin, Razali

“…It uses a deterministic sampling approach known as sigma points to propagate nonlinear systems and has been discussed in many literature. …”
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Effect of Radiation and Magnetohydrodynamic Free Convection Boundary Layer Flow on a Solid Sphere with Convective Boundary Conditions by Hamzeh Taha, Alkasasbeh, Mohd Zuki, Salleh, Razman, Mat Tahar, Roslinda, Nazar

“…The basic equations of the boundary layer are transformed into a non-dimensional form and reduced to nonlinear systems of partial differential equations and solved numerically using an implicit finite difference scheme known as the Keller-box method. …”
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ANFIS modelling of a twin rotor system using particle swarm optimisation and RLS by Toha, Siti Fauziah, Tokhi, M. O.

“…Artificial intelligence techniques, such as neural networks and fuzzy logic have shown promising results for modelling of nonlinear systems whilst traditional approaches are rather insufficient due to difficulty in modelling of highly nonlinear components in the system. …”
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Quantum dynamics of nonlinear excitations in the Ablowitz-Ladik model by Umarov, Bakhram

“…The investigation of the dynamics of nonlinear systems becomes a hot topic in modern science and engineering. …”
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Application of the generalized likelihood uncertainty estimation (GLUE) approach for assessing uncertainty in hydrological models: A review by Mirzaei, M., Huang, Y.F., El-Shafie, A., Shatirah, A.

“…GLUE's popularity can be attributed to its simplicity and its applicability to nonlinear systems, including those for which a unique calibration is not apparent. …”
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Metaheuristics algorithms to identify nonlinear Hammerstein model: A decade survey by Jui, Julakha Jahan, Mohd Ashraf, Ahmad, Muhammad Ikram, Mohd Rashid

“…This paper presents a survey for the years 2011-2021 on multiple metaheuristics algorithms, particularly swarm and evolutionary algorithms, to identify a nonlinear block-oriented model called the Hammerstein model, mainly because such model has garnered much interest amidst researchers to identify nonlinear systems. Besides introducing a complete survey on the various population-based algorithms to identify the Hammerstein model, this paper also investigated some empirically verified actual process plants results. …”
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Adaptive neuro-fuzzy model with fuzzy clustering for nonlinear prediction and control by Al-Himyari, Bayadir Abbas, Yasin, Azman, Gitano, Horizon

“…Nonlinear systems have more complex manner and profoundness than linear systems.Thus, their analyses are much more difficult.This paper presents the use of neuro-fuzzy networks as means of implementing algorithms suitable for nonlinear black-box prediction and control.In engineering applications, two attractive tools have emerged recently.These two attractive tools are: the artificial neural networks and the fuzzy logic system. …”
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Intelligent control for self-erecting inverted pendulum via adaptive neuro-fuzzy inference system by Saifizul, A.A., Zainon, Z., Abu Osman, Noor Azuan, Azlan, C.A., Ibrahim, U.F.S.U.

“…A self-erecting single inverted pendulum (SESIP) is one of typical nonlinear systems. The control scheme running the SESIP consists of two main control loops. …”
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Multilinear-model predictive control of a tubular solid oxide fuel cell system by Hajimolana, S., Hussain, Mohd Azlan, Soroush, M., Wan Daud, W.A., Chakrabarti, M.H.

“…As solid oxide fuel cells (SOFCs) are highly nonlinear systems, a single linear controller cannot perform satisfactorily over a wide range of operating conditions of the processes. …”

Fuzzy logic controller design for inverted pendulum system by Ismail, Nurfakhirah

“…Besides that, Fuzzy logic control system (FLC) was chosen as the control technique because of its ability to deal with nonlinear systems, as well as its intuitive nature. One special feature of fuzzy logic control is that it utilizes the expertise of humans to control the physical system, so that complex system can be controlled without extensive modeling of the relationship between the input and output of the system.…”
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