Explores the control challenge in soft robotic systems and the use of simplified models with nonlinear control theory for dynamic task execution.
Explores controlled stochastic processes, focusing on analysis, behavior, and optimization, using dynamic programming to solve real-world problems.
Introduces optimal control theory, covering models, discretization, measurements, Lagrangian, KKT conditions, and invertibility.
Explores the stability of Ordinary Differential Equations, focusing on solution dependence, critical data, linearization, and control of nonlinear systems.
