Self-triggered control, a well-documented technique for reducing the communication overhead while ensuring desired system performance, is gaining increasing popularity. However, majority of existing self-triggered control methods require explicit models. An end-to-end paradigm known as data-driven designs laws directly from data and offers competing alternative to routine identification-then-co...

Abstract Differential dynamic programming (DDP) is a direct single shooting method for trajectory optimization. Its efficiency derives from the exploitation of temporal structure (inherent to optimal control problems) and explicit roll-out/integration system dynamics. However, it suffers numerical instability and, when compared multiple methods, has limited initialization options (allows contro...

In this paper we examine a control variate estimator for quantity that can be expressed as the expectation of functional random process, is itself solution differential equation driven by fast mean-reverting ergodic forces. The same limit diffusion process approximates original when mean-reversion time goes to zero. To get an efficient estimator, propose coupling method build and process. We sh...

Control barrier functions (CBFs) are a powerful tool to guarantee safety of autonomous systems, yet they rely on the computation control invariant sets, which is notoriously difficult. A backup strategy employs an implicit set computed by forward integrating system dynamics. However, this integration prohibitively expensive for high dimensional and inaccurate in presence unmodelled We propose l...