Stochastic wave finite element for random periodic media through first-order perturbation

https://hal.archives-ouvertes.fr/hal-02075618/document

Reliability assessment of complex mechatronic systems using a modified nonparametric belief propagation algorithm

This paper deals with the recurrent problem of spill-over that induces instability when the control strategy is based on uncollocated transducers. We first introduce the concept of modal control and the need to limit controllability and observability to a finite set of modes in order to avoid residual coupling effects which is the source of spill-over. Next, we establish the typical form of controllability and observability gramians when the distributed system is discretized on its modal components. An adequate norm is also introduced to optimize these operators. Finally, we show the obvious advantage of optimizing the piezoelectric density of sensors in order to achieve efficient control. An example is treated and shows some typical results obtained by our method.

Shape optimization of piezoelectric sensors dealing with spill-over instability

In this paper, a new smart structure optimal design strategy is introduced and applied to robust vibration control of a piezoelectric laminate beam. The optimization of the smart material layout and the control law are performed simultaneously to extract maximum performance from the system. A homogenization approach is used to allocate sensor material, while a linear quadratic regulator (LQR) is used for the control law. The method is applied to a pinned-pinned beam where two cost functions are considered, both focusing on increasing the stability margin of the closed-loop system. The first is based on the observability gramian and the second on the control weighting parameter of the LQR cost function. Both cost functions yield optimal sensor distributions that improve the closed-loop performance as compared with uniform density distributions. In addition to investigating the effect of the cost function on the design, two different sensor design domains are considered. The first consists of five isolated patches of sensor material (a discrete sensor domain), while the second assumes the five patches cover the entire beam, but are electrically isolated (segmented distributed sensor domain). In all cases considered, the cost function based on the LQR control weighting parameter generates smoother sensor distributions that are always positively polled, an important fabrication consideration. The segmented distributed sensor approach yields the overall best performance.

http://research.me.mtu.edu/abstracts/Parker-%20Optimal%20Sensor%20Design%20and%20Control%20of%20Piezoelectric%20Laminate%20Beams.pdf

Optimal sensor design and control of piezoelectric laminate beams

The interest of this paper is to develop a general and systematic robust control methodology for active vibration control of flexible structures For this purpose, first phase and gain control policies are proposed to impose qualitative frequency-dependent requirements on the controller to consider a complete set of control objectives Then the proposed control methodology is developed by employing phase and gain control policies in the dynamic output feedback H??control: according to the set of control objectives, phase and gain control policies incorporate necessary weighting functions and determine them in a rational and systematic way; on the other hand, with the appropriate weighting functions efficient H??control algorithms can automatically realize phase and gain control policies and generate a satisfactory H??controller The proposed control methodology can be used for both SISO and MIMO systems with collocated or non-collocated sensors and actuators In this paper, it is validated on a non-collocated piezoelectric cantilever beam Both numerical simulations and experimental results demonstrate the effectiveness of the proposed control methodology

/pdf/phase-and-gain-control-policies-for-robust-active-vibration-3xn6xo9h08.pdf

M. Noe

Papers

An assembled plate active control damping set-up : Optimization and control