An improved fuzzy controller on electromechanical nano-tweezers

Abstract

This paper aims to develop an improved fuzzy controller for position controlling of nano-wire-based electromechanical nano-tweezers. The nonlinear governing equation is developed by incorporating the Euler–Bernoulli beam model and Hamilton’s principle. Also, the quantum vacuum fluctuations are assimilated in the developed model in terms of Casimir attraction. The nonlinear constitutive equation is transformed into a nonlinear state-space form by employing the Galerkin method. Based on the linguistic explanation of the system, an improved fuzzy controller is designed to control the nano-tweezers for manipulating desired objects. The Taguchi technique has been used to decrease the number of independent experiments and improve the structure of membership functions, consequently. The designed controller is employed for both controlling and path tracking of nano-tweezers. The outcomes indicate that the proposed improved fuzzy controller has excellent performance for stabilizing the nano-tweezers at any desired gap.

An adaptive hybrid control strategy for a class of nonlinear systems

“…The control of nonlinear systems has received a lot of attention in the last decade due to the nonlinear properties that occur in real-world systems. In the literature, a variety of advanced control strategies, including sliding mode control, backstepping control, fuzzy logic, and neural network control, have recently been suggested to be utilized in practical applications (Koochi et al 2022; Bui et al 2011; Wang et al 2018a, 2016; Ray et al 2018; Xiuxiang et al 2018; Zhao et al 2019; Nguyen et al 2017; Rebai and Guesmi 2020; Farahani and Ganjefar 2017; Baigzadehnoe et al 2017; Sadek et al 2017; Qiao et al 2018; Wu et al 2019; Jin et al 2018; De Jesús Rubio 2018; Sui et al 2019; Rebai et al 2015). To mention a few, the problem of fault-tolerant control for nonlinear systems with unknown control directions is addressed in Liu et al (2019).…”