Agent-Based Negotiation for Engineering Design

Title: ITR: An Agent-Based Negotiation Framework for the Robust Design of Active-Passive Hybrid Piezoelectric Vibration Control Networks

Sponsor: National Science Foundation

         The objective of the proposed research is to investigate novel information technology (IT) based approach for synthesizing electro-mechanically optimized smart-structures. Specifically, we will develop an Agent-based Negotiation framework for the robust design for large-scale active-passive hybrid piezoelectric networks (APPN) for structural vibration control. The goal of the education plan is to integrate the research with various educational programs at Penn State and achieve a broad range of impact on student learning.

         The underlying principle for APPN, which has recently attracted significant attention among engineers for vibration control applications, is to combine the active and passive control features of piezoelectric materials and circuits. It has been demonstrated that the hybrid network approach can outperform both the purely passive and active configurations. While vibration suppression using APPN is indeed a very attractive concept, it was also recognized that several critical issues need to be addressed before such a system can be realistically be optimized in a complex smart structure environment for a large-scale and distributed vibration control. These issues, difficult to resolve using conventional methods, include system uncertainties, tradeoff scenarios, and topology variations in design. Through combining the expertise (IT and engineering) of the two investigators and leveraging upon their ongoing research, the proposed effort can address these critical issues and greatly advance the state of the art.

         The new ideas are to formulate the smart structure design problem in making high-level design decisions (e.g., the selection of topology) and in analyzing the tradeoff among conflicting design objectives, which include the robustness requirement for dealing with model uncertainty. The agents will have reasoning capabilities derived from a fuzzy logic-based foundation for analyzing conflicting imprecise requirements.

         The principal investigators are Prof. John Yen from School of Information Sciences and Technology, and Dr. Kon-Well Wang from Department of Mechanical and Nuclear Engineering.