Data-driven design of damping controllers for a MEMS force sensor with uncertain dynamics

This paper presents the design process and compares three damping controllers for an uncertain microelectromechanical system (MEMS) force sensor to mitigate its resonant mode. The damping methods include resonant controller (RC), integral resonant controller (IRC), and robust resonant controller (RRC). A frequency domain-based convex optimization is proposed to find the parameters of the resonant controller to obtain a desired closed-loop response. In addition to the conventional IRC, we formulate a second-order robust resonant controller. To validate the effectiveness of the proposed controllers, we conduct comparative experiments under uncertainty where system dynamics are perturbed, resulting in a decrease in the system’s DC-gain and an increase in the resonance frequency over a relatively wide bandwidth. The findings reveal that the RC exhibits superior damping characteristics and the shortest settling time. In contrast, the IRC shows minimal overshoot in step response (30%), and the RRC demonstrates enhanced robustness under uncertain conditions.