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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.

A design process for system architecture design using multicriteria optimization is described using a case study of an aero engine health management (EHM) system. The EHM system functional operations need to be deployed in order to satisfy their operational attribute requirements within the constraints of resource limitations. Considering the large discrete search space of decision variables and many-objective functions and constraints, an evolutionary multi-objective genetic algorithm along with a progressive preference articulation (PPA) technique, is used for solving the optimization problem. Using the PPA technique, the industrial decision maker is able to identify the most significant design constraints ("hot spots") and experiment with changing goals for objectives, in order to arrive at a satisfactory non-dominated solutions that takes account of domain knowledge.

No 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. Two conflicting objectives: minimization of input control energy and minimization of mean square deviation between the desired and actuated shapes are considered with constraints on 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 (EMO) algorithm NSGA-II. Pareto-optimal solutions are obtained for different case studies. Further, the obtained solutions are verified by comparing with single-objective optimization solutions.