Active Vibration Control on a Smart Composite Structure using Modal-Shaped Sliding Mode Control

This paper proposes an active modal vibration control method based on a modal sliding mode controller applied to a smart material composite structure with integrated piezoelectric transducers as actuators and sensors. First, the electromechanical coupled system is identified using a modal reduced-order model. The sliding surface is based on the modal-filtered states and designed using a general formulation allowing the control of multiple vibration modes with multiple piezoelectric sensors and actuators. The performance and stability of the nonlinear controller are addressed and confirmed with the experimental results on a composite smart spoiler-shaped structure. The nonlinear switching control signal, based on the modal-shaped sliding surface improves the performances of the linear part of the control while maintaining not only stability but also robustness. The attenuation level achieved on the target modes on all piezoelectric sensors starts from -14dB up to -22dB, illustrating the strong potential of nonlinear switching control methods in active vibration control.

Neural-Network Based Modeling of I/O Buffer Predriver under Power/Ground Supply Voltage Variations

This paper presents a neural-network based nonlinear behavioral modelling of I/O buffer that accounts for timing distortion introduced by nonlinear switching behavior of the predriver electrical circuit under power and ground supply voltage (PGSV) variations. Model structure and I/O device characterization along with extraction procedure were described. The last stage of the I/O buffer is modelled as nonlinear current-voltage (I-V) and capacitance voltage (C-V) functions capturing the nonlinear dynamic impedances of the pull-up and pull-down transistors. The mathematical model structure of the predriver was derived from the analysis of the large-signal electrical circuit switching behavior. Accordingly, a generic and surrogate multilayer neural network (NN) structure was considered in this work. Timing series data which reflects the nonlinear switching behavior of the multistage predriver’s circuit PGSV variations, were used to train the NN model. The proposed model was implemented in the time-domain solver and validated against the reference transistor level (TL) model and the state-of-the-art input-output buffer information specification (IBIS) behavioral model under different scenarios. The analysis of jitter was performed using the eye diagrams plotted at different metrics values.

Analysis of the Vibration Suppression of Double-Beam System via Nonlinear Switching Piezoelectric Network

In this paper, a method to suppress the vibration of a double-beam system with nonlinear synchronized switch damping on the inductor via a network (SSDI-net) is proposed. Unlike the classical linear piezoelectric shunt damping, SSDI-net is a nonlinear piezoelectric damping. A double-beam system with SSDI-net was simplified to a lumped parameter electromechanical coupling model and analyzed by using the multi-harmonic balance method, at first with alternating frequency–time techniques (MHBM/AFT). Then, a new lower-power autonomous switching control circuit board was designed, based on SSD technique, and vibration control experiments using a double-beam system with an SSDI network are conducted, to verify the validity of the proposed analysis method and its calculation results. The nonlinear switching piezoelectric network proposed in this article can increase the voltage inversion factor. Furthermore, future applications of this switching piezoelectric network technology in the vibration suppression of bladed-disk structures in aero engines can reduce the number of switches by at least half and obtain almost the same damping effect.