Data-driven and autonomous climate control in buildings:
I currently work on adaptive and data-driven climate control of smart, next-generation buildings where I employ distributed measurements to design decentralized, coordinated, and autonomous control algorithms to concurrently improve occupants’ comfort and energy cost. In this project, I study developing controllers that can learn effective policies based on real experience, and with no prior knowledge of the building models.
Nonlinear dynamics and structural instabilities for vibration energy harvesting:
My doctoral work focuses on fundamental power limits and robustness issues in nonlinear vibratory energy harvesters (VEHs). I developed a general framework for calculation of these limits for arbitrary excitation and constraints . As a byproduct of this analysis, I characterized a universal, nonlinear optimal law (buy-low-sell-high strategy) that maximizes the harvested power and proposed practical implementation methods by employing intentional nonlinearities. This strategy is able to explain the high effectiveness of the extensively-studied bistable as well as other multi-stable harvesters. To address the robustness issues of VEHs, I proposed a new optimization philosophy for passive harvesters and a novel sliding mode controller for active variants that could successfully move the harvester to any desired attractor in the presence of uncertainties. More recently, I postulated the idea of using large-strain structural instabilities such as wrinkling for effective energy harvesting.