  A sensitivity-based approach for computing over-approximations of reachable
sets, in the presence of constant parameter uncertainties and a single initial
state, is used to analyze a three-link planar robot modeling a Powered Lower
Limb Orthosis and its user. Given the nature of the mappings relating the state
and parameters of the system with the inputs, and outputs describing the
trajectories of its Center of Mass, reachable sets for their respective spaces
can be obtained relying on the sensitivities of the nonlinear closed-loop
dynamics in the state space. These over-approximations are used to evaluate the
worst-case performances of a finite time horizon linear-quadratic regulator
(LQR) for controlling the ascending phase of the Sit-To-Stand movement.
