Our unique time-delay control effort was publicized on NPR (KPBS) News!
Autonomous Deep Learning-Based Obstacle Avoidance 3D Path Planning Using Baxter.
Welcome to Dynamic Systems and Control Laboratory (DSCL)! The lab focus is on a wide range of research efforts which include, but are not limited to, Nonlinear Modeling, Dynamic Analysis, Optimization (design, operation, and control), and Centralized/Decentralized Control of Multi-Robot Systems, Smart Flow Distribution Network, Magnetic Bearings, and Large-Scale Systems. Multidisciplinary systems have received much attention with respect to their complex physics leading us to develop efficient numerical and analytical tools along with experimental work to translate the ambiguous behaviors of these systems to understandable mathematical language.
My former PhD student, Dr. Mostafa Bagheri, implemented Nonzero-Sum Cooperative Controller of Game Theory for a 7-DOF Baxter robot at our Dynamic Systems and Control Laboratory (DSCL).
Model-Based Adaptive Control of Baxter to Carry an Unknown Mass Avoiding an Obstacle.
Decentralized Vs. Centralized Adaptive Control of Hyperchaotic Smart Valves Network (Two Agents):
An advanced practice we utilize in analyzing any complex system. Several powerful tools we use in deriving Nonlinear, Scalable, and Coupled dynamic models of electromechanical networks. Comprehensive stability analysis is then carried out to guarantee the stable performance of each agent and subsequently the whole system. Any theoretical approach needs an experimental validation to refine the model developed to be used in the dynamic analysis, and optimization/control schemes.