Sponsor: National Science Foundation (ENG/CMMI Division)
Collaborator: Prof. Hassan K. Khalil (Co-PI, Electrical and Computer Engineering)
Smart materials, such as piezoelectric materials and shape memory alloys (SMAs), exhibit strong coupling of complex hysteretic behavior with the nonlinear dynamics of structures and fluids that are driven by smart material actuators, especially at medium-to-high drive levels. The latter, together with the uncertainties in both hysteresis and dynamics, makes it challenging to precisely control smart material-actuated systems.
In this project we are developing a novel multi-time-scale nonlinear and adaptive control framework for hysteretic systems, with a goal to enable robust, precision, and high-bandwidth control of smart material-actuated systems. The focus of our effort is a multi-time-scale averaging theory for hysteretic systems, which is expected to provide a framework for merging adaptive hysteresis compensation with a plethora of nonlinear and adaptive control methods for hysteresis-free systems through time-scale separation. In addition, we are developing a general, parallel paradigm for hysteresis inversion and adaptation based on reconfigurable computing hardware, to enable efficient implementation of the theory.
We are also validating our theory and algorithms experimentally in smart material-actuated systems. The picture below shows one experimental platform – a piezoelectric actuator-driven nanopositioning system (stage shown in the left). We are also interested in transferring the developed technology to the nanopositioning and scanning probe microscopy (SPM) industry.
