Dr. Peiman Naseradinmousavi and his team lead two pioneering and challenging research efforts of ‘’Smart Valves Network’’ and ‘’Soft Robotics’’ in his Dynamic Systems and Control Laboratory (DSCL); Multidisciplinary electromechanical-fluid systems have been widely used in many megascale networks. Municipal piping systems, oil and gas fields, petrochemical plants, and more critically, the U.S. Navy are the immediate ones which need to utilize a reliable, safe, and efficient flow distribution network.
It has repeatedly been malfunctions of the flow distribution network resulting in the flow interruption of various megascale systems. Although, remarkable cost and energy are needed to be spent in order to restore the whole system. Economical and even social impact of these malfunctions have been dramatic in recent decades and consequently, an autonomous flow distribution network is needed to be efficiently designed and centrally controlled. The focus of this foundational research effort is on interconnected modeling and centralized self-healing control of Smart Autonomous Flow Distribution Network. A comprehensive network based approach is thoroughly addressed, for the first time, while the lack of nonlinear interconnected analysis of such systems has revealed inaccurate results and often caused catastrophic behaviors. Since joining SDSU, Dr. Naseradinmousavi published 9 articles, including 5 journal and 4 conference papers, in the most prestigious venues to address such a challenging research field. The research team of DSCL has also focused on robotics including soft robotics and bipedal robots. The lab has been equipped with a high-tech 14 DOFs Baxter Rethink Manipulator in addition to three NAO bipedal robots and unmanned Aerial/Ground vehicles to be used in the network-based operation. The DSCL team is developing the Model Predictive Control (MPC)/Adaptive schemes to control the robots efficiently. Note that both the autonomous and nonautonomous methods, which utilize online and offline/blind optimization and control schemes, respectively, have revealed some advantages and disadvantages. The research team currently focuses on the nonautonomous energy-efficient operation of the Baxter manipulator which would subsequently be used in nonlinear control schemes as desirable trajectories. The offline optimization/control of the robot will be gradually examined with respect to the autonomous practice to yield the most reliable and optimal configuration.
For more information, visit Dr. Naseradinmousavi’s laboratory website at: http://www-rohan.sdsu.edu/~mezzolo/index.html