A New Intelligent Dynamic Control Method for a Class of Stochastic Nonlinear Systems

Haifeng Huang, Mohammadamin Shirkhani, Jafar Tavoosi and Omar Mahmoud
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Haifeng Huang: School of Electrical and Information Technology, Zhenjiang College, Zhenjiang 212028, China
Mohammadamin Shirkhani: Department of Electrical Engineering, Ilam University, Ilam 69315-516, Iran
Jafar Tavoosi: Department of Electrical Engineering, Ilam University, Ilam 69315-516, Iran
Omar Mahmoud: Faculty of Engineering and Technology, Future University in Egypt, New Cairo 11835, Egypt

Mathematics, 2022, vol. 10, issue 9, 1-15

Abstract: This paper presents a new method for a comprehensive stabilization and backstepping control system design for a class of stochastic nonlinear systems. These types of systems are so abundant in practice that the control system designer must assume that random noise with a definite probability distribution affects the dynamics and observations of state variables. Stochastic control is intended to determine the time course of control variables so that the control target is achievable even with minimal cost. Since the mathematical equations of stochastic nonlinear systems are not always constant, not every model-based controller can be accurate. Therefore, in this paper, a type-3 fuzzy neural network is used to estimate the parameters of the backstepping control method. In the simulation, the proposed method is compared with the Type-1 fuzzy and RBFN methods. Results clearly show that the proposed method has a very good performance and can be used for any system in this class.

Keywords: parameter estimation; stochastic systems; type-3 fuzzy neural network; backstepping control method (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (15)

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