Time: 9:30 am - 10:30 am
Location: 409 Dougherty Engineering Building
Dr. Sandipan Mishra
Associate Professor Mechanical, Aerospace, and Nuclear Engineering Rensselaer Polytechnic Institute
This seminar will present a snapshot of research activity in the Intelligent Systems, Automation & Control Laboratory at Rensselaer Polytechnic Institute, ranging from intelligent building systems to additive manufacturing and adaptive optics. We will then track the trajectory of how a typical advanced manufacturing process is conceived, designed, modeled, and ultimately controlled in a reliable manner. The first half of the seminar will focus on the instrumentation and design of a 3D printer for fiber-polymer composites. The motivation for the design of such a system stems from printing “synthetic organs” for surgeons to practice patient-specific procedures. The latter half will investigate control-oriented modeling and the design of feedback control algorithms for inkjet 3D printing for enhancing accuracy and repeatability. I will present a layer-to-layer model of a typical (droplet-based) 3D printing process and a model-based predictive control algorithm that utilizes in-situ height measurements as feedback. Finally, experimental validation and demonstration of this system and its capabilities will be presented along with future directions and challenges to wrap up the discussion.
Sandipan Mishra received his B.Tech. from the Indian Institute of Technology Madras in 2002 and his Ph.D. from the University of California at Berkeley in 2008, both in Mechanical Engineering. Dr. Mishra joined RPI’s faculty in 2010, where he is currently an Associate Professor in Mechanical, Aerospace and Nuclear Engineering with joint appointment in the Electrical and Computer Systems Engineering department. He was a member of the 2010 Japan NXT-NSF Young investigator exchange program for nanomanufacturing and the recipient of the NSF Early CAREER award in 2013 on additive manufacturing. His research interests are in the general area of systems and control theory, iterative learning control, optimal control, and precision mechatronics, as applied to autonomous aerial vehicles, additive manufacturing, and smart building systems. He is the PI of the ISAaC laboratory at RPI, which is supported by grants from government agencies including NSF, the DoD, and DoE, along with industrial partners including General Electric Co., Hewlett Packard Labs, Sikorsky Inc., Mathworks Inc., National Instruments, Simmetrix, and Vivonics Inc.