When models are inaccurate, the performance of model-based control will degrade. For linear quadratic control, an event-triggered learning framework is proposed that automatically detects inaccurate and triggers a new process model when needed. This achieved by analyzing probability distribution cost designing trigger leverages Chernoff bounds. In particular, whenever empirically observed signa...

Abstract We consider the controllability problem for finite-dimensional linear autonomous control systems with nonnegative controls. Despite Kalman condition, unilateral nonnegativity constraint may cause a positive minimal time. When this happens, we prove that, if matrix of system has real eigenvalue, then there is time in space Radon measures, which consists finite sum Dirac impulses. all ei...