Extremum Seeking-Based Obstacle Avoidance: Novel Analytical and Experimental Trajectory Optimization of a 7-DOF Baxter Robot Carried out by Mostafa Bagheri, PhD Candidate
Model-Based Adaptive Control of Baxter to Carry an Unknown Mass Avoiding Obstacle
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.
Predictor-Based Control for Destabilizing Time-Delay of a 7-DOF Robot
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.