Multi-Objective Optimization of Piezoelectric Actuator Placement for Shape Control of Plates Using Genetic Algorithms

Abstract

Shape control of adaptive structures using piezoelectric actuators has found a wide range of applications in recent years. In this paper, the problem of finding optimal distribution of piezoelectric actuators and corresponding actuation voltages for static shape control of a plate is formulated as a multi-objective optimization problem. The two conflicting objectives considered are minimization of input control energy and minimization of mean square deviation between the desired and actuated shapes with constraints on the maximum number of actuators and maximum induced stresses. A shear lag model of the smart plate structure is created, and the optimization problem is solved using an evolutionary multi-objective optimization algorithm: nondominated sorting genetic algorithm-II. Pareto-optimal solutions are obtained for different case studies. Further, the obtained solutions are verified by comparing them with the single-objective optimization solutions. Attainment surface based performance evaluation of the proposed optimization algorithm has been carried out.

Adaptive vibration control of piezoelectric cantilever beams with uncertainties

“…It is generally believed that the vibration energy of smart structure is mainly concentrated in the low frequency range. As long as the vibration energy of the first several vibration modes is consumed, the purpose of vibration suppression can be achieved [6]. Both the piezoelectric sensors and actuators work through the electromechanical coupling effect.…”

“…C. Qu . W. Liu 1 College of Mechanical and Electronical Engineering, Nanyang Normal University, Nanyang 473061, China E-mail: cuiminyue@sina.com material or embedding piezoelectric material is usually ignored, and a distributed moment is used to express the control effect of piezoelectric layer on the structure [4][5][6][7], which can not accurately reflect the intrinsic mechanical characteristics of the piezoelectric smart structure. The finite element model of piezoelectric structure usually has a high order, which can not be directly used in the design of controller.…”

Multi-objective structural robust optimization under stress criteria based on mixed plate super-elements and genetic algorithms

“…Even though often carried out manually, structural dynamic MO optimization methods are developed in the literature, such as gradient [1,25] and MO Evolutionary Algorithms(EA) methods [24,27]. MOEA permit to dispense with any criteria weighting.…”

Optimum piezoelectric patch positioning: A strain energy–based finite element approach

“…Several publications highlight the use of genetic algorithms to find optimum piezo configurations (Han and Lee, 1999;Kudikala et al, 2009;Sadri et al, 1999;Zhang et al, 2000). Genetic algorithms are well-suited for non-convex search spaces that commonly involve continuous and discrete optimization variables in a multi-objective optimization environment (Belloli and Ermanni, 2007;Dhuri and Seshu, 2009;Jha and Inman, 2003;Lee and Han, 1996;Sohn et al, 2011).…”