Development of a multi-level adaptive fuzzy controller for beyond pull-in stabilization of electrostatically actuated microplates

Abstract

The objective of this paper is to present a supervised multi-level fuzzy controller to control the deflection of an electrostatically actuated microplate within and beyond its pull-in range. The mode shapes of the microplate are derived using Extended Kantorovich Method (EKM) which are shown to be in great agreement with finite element results. Using open loop simulations, it is shown that the first mode shape is effectively the dominant one. Then by utilizing a single mode approximation along with employing the Lagrange equation, the dynamic behavior of the microplate is described in modal space by an ordinary differential equation. By static and dynamic simulations, dependence of the plate deflection on the applied voltage is identified linguistically. Then based on the linguistic description of the system, a fuzzy controller is designed to stabilize the microplate at desired deflections. To improve the performance specifications of the closedloop system, another fuzzy controller at a higher level is proposed to adjust the parameters of the main controller in real time. To guarantee the stability of the closed-loop system, a non-fuzzy supervisory unit is attached to the control architecture. The simulations results reveal that by using the presented single level and supervised adaptive controllers, the control objective is met effectively with good performance specifications. It is also observed that adding a second level and a supervisory unit to the main controller can reduce the overshoot and the settling time for within and beyond pull-in stabilization of electrostatically actuated microplates in following the step commands. Excellent performance of the system in the presence of the proposed controller is further demonstrated using multiple step and also sinusoidal commands. The qualitative knowledge resulting from this research can be generalized and used for development of efficient controllers for N/MEMS actuators and electrostatically actuated nano/micro positioning systems.

Design and Hardware Implementation Based on Hybrid Structure for MPPT of PV System Using an Interval Type-2 TSK Fuzzy Logic Controller

“…Fuzzy logic control (FLC) is a widely-used method to perform MPPT for the PV system. Numerous studies [17][18][19][20][21][22][23][24] in the existing literature have demonstrated that Type-1 FLC (T1FLC) does not succeed in highly uncertain situations in the system, while a Type-2 FLC using Type-2 fuzzy set display better performance. In the present paper, a hybrid control structure called AIC-IT2-TSK-FLC was developed for MPPT of the PV system with a combination of the AIC MPPT algorithm and Type-2 FLC [25].…”

A New Sampled-Data Output-Feedback Controller Design of Nonlinear Systems via Fuzzy Affine Models

“…It has been proved that T-S fuzzy model can serve as a technically efficient tool to approximate smooth nonlinear systems to arbitrary degrees of accuracy within any convex compact set [16]. As a consequence, plenty of efforts have been devoted to T-S fuzzy systems aiming at industrial applications [17], [18] and theoretical study [19], [20].…”

Adaptive fractional-order backstepping sliding mode controller design for an electrostatically actuated size-dependent microplate

“…Based on the conducted research works, nonlinearities play an important role in the failure of dynamic systems (Alsaleem and Younis, 2010). Hence, studying the control behaviors and enhancing the efficiency, accuracy, and stability of electrostatic MEMS have been a matter of interest of many researchers (Gu and Zhu, 2014; Radgolchin and Moeenfard, 2018). Several control methods such as sliding mode control (SMC) (Dastaviz and Binazadeh, 2019; Vahidi-Moghaddam et al, 2018), fuzzy control (Tooranjipour et al, 2019; Zou et al, 2019), and backstepping control (Meng et al, 2019) have been vastly used to control the nonlinear mechanical systems.…”