This talk focuses on the autonomous control of of small-scale photovoltaic powered reverse osmosis (PVRO) desalination systems. Such systems can provide fresh water to remote communities that do not have sufficient clean water, a growing problem of international importance.
Producing clean drinkable water from seawater or brackish ground water by desalination is a power hungry process. Hence powering desalination with solar energy is attractive. Photovoltaic-powered reverse osmosis systems have been shown to be both technically feasible and economically viable for cases where the water demand is relatively small - 1,000 to 10,000 liters per day.
However, current PVRO has important technical limitations to be practical for small communities. First, its performance is a function of input water chemistry, solar insolation, the temperature of its environment and input water. To be practical, its behavior must be constantly regulated to compensate for changes in these factors. In the field it is not feasible to do this manually. The work reported on here, mechatronic (robotic) technology is used to develop systems that can self-adapt to optimize their performance. In this research, models of the complex nonlinear performance of PVRO systems have been developed and experimentally validated. These models are used to develop algorithms to permit these systems to autonomously optimize their performance. These algorithms have been implemented at MIT in an experimental PVRO system using embedded microcomputer controllers. Experimental results are presented that show the effectiveness of the MIT algorithms. When tested in a remote Mayan village located in the Yucatan Peninsula, the effectiveness of this technology has been successfully demonstrated.
About the Speaker:
Steven Dubowsky received his BS from Rensselaer Polytechnic Institute and his MS and PhD from Columbia University under the mentorship of Prof. Ferdinand Freudenstein. He currently holds joint faculty positions in the Department of Mechanical Engineering and the Department of Aeronautics and Astronautics at MIT. He is also the Director of of the MIT Field and Space Robotics Laboratory. Dr. Dubowsky's research has included the development of optimal and self learning adaptive control methods for robotics systems, including space robots. He has authored and co-authored over 350 papers. Currently, his research focuses on fuel cell power for field robotic systems, sensor networks and photovoltaic powered clean water systems for challenging field environments. He has served as an advisor to the National Science Foundation, the National Academy of Science/Engineering, the Department of Energy, and the US Army. He is a Fellow of both ASME and IEEE, and a member of Sigma Xi and Tau Beta Pi honor societies.
Register for this Event