Linear structures in nonlinear optimal control

Abstract: We investigate optimal control of dynamical systems which are affine, i.e., linear in control, but nonlinear in state. The control task is to enforce the system state to follow a prescribed desired trajectory as closely as possible, a task also known as optimal trajectory tracking. To obtain well-behaved solutions to optimal control, a regularization term with coefficient $\varepsilon$ must be included in the cost functional. Assuming $\varepsilon$ to be small, we reinterpret affine optimal control problems as singularly perturbed differential equations. Performing a singular perturbation expansion, approximations for the optimal tracking of arbitrary desired trajectories are derived. For $\varepsilon=0$, the state trajectory may become discontinuous, and the control may diverge. On the other hand, the analytical treatment becomes exact. We identify the conditions leading to linear evolution equations. These result in exact analytical solutions for an entire class of nonlinear trajectory tracking problems. The class comprises, among others, mechanical control systems in one spatial dimension and the FitzHugh-Nagumo model with a control acting on the activator.