The objective of this paper is to present an adaptive multi-level fuzzy controller to stabilize the deflection of an electrostatically actuated microplate beyond its pull-in range. Using a single mode approximation along with utilizing the Lagrange equations, the dynamic behavior of the microplate is described in modal space by an ordinary differential equation. By different static and dynamic simulations, the system and the dependence of the deflection to the input applied voltage is identified linguistically. Then, based on the linguistic description of the system, a fuzzy controller is designed to stabilize the microplate at the desired deflections. To improve the performance specifications of the closed-loop system, another fuzzy controller at a higher level is designed to adjust the parameters of the main controller in real time. The simulation results reveal that by using the proposed single level and adaptive two level controllers, the control objective is met effectively with good performance specifications. It is also observed that adding a supervisory level to the main controller can reduce the overshoot and the settling time in beyond pull-in stabilization of electrostatically actuated microplates. 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.
- Dynamic Systems and Control Division
A Two-Level Adaptive Fuzzy Control Algorithm for Beyond Pull-In Stabilization of Electrostatically Actuated Microplates
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Radgolchin, M, Moeenfard, H, & Ghasemi, AH. "A Two-Level Adaptive Fuzzy Control Algorithm for Beyond Pull-In Stabilization of Electrostatically Actuated Microplates." Proceedings of the ASME 2016 Dynamic Systems and Control Conference. Volume 2: Mechatronics; Mechatronics and Controls in Advanced Manufacturing; Modeling and Control of Automotive Systems and Combustion Engines; Modeling and Validation; Motion and Vibration Control Applications; Multi-Agent and Networked Systems; Path Planning and Motion Control; Robot Manipulators; Sensors and Actuators; Tracking Control Systems; Uncertain Systems and Robustness; Unmanned, Ground and Surface Robotics; Vehicle Dynamic Controls; Vehicle Dynamics and Traffic Control. Minneapolis, Minnesota, USA. October 12–14, 2016. V002T17A008. ASME. https://doi.org/10.1115/DSCC2016-9841
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