109 citations · 955 across the 60 of their papers we have counts for
7 papers · 2 filters
On the connections between PCTL and Dynamic Programming
Federico Ramponi, Debasish Chatterjee, Sean Summers +1
Probabilistic Computation Tree Logic (PCTL) is a well-known modal logic which has become a standard for expressing temporal properties of finite-state Markov chains in the context…
Attaining mean square boundedness of a marginally stable noisy linear system with a bounded control input
Federico Ramponi, Debasish Chatterjee, Andreas Milias-Argeitis +2
We construct control policies that ensure bounded variance of a noisy marginally stable linear system in closed-loop. It is assumed that the noise sequence is a mutually independen…
On convex problems in chance-constrained stochastic model predictive control
Eugenio Cinquemani, Mayank Agarwal, Debasish Chatterjee +1
We investigate constrained optimal control problems for linear stochastic dynamical systems evolving in discrete time. We consider minimization of an expected value cost over a fin…
Maximizing the probability of attaining a target prior to extinction
Debasish Chatterjee, Eugenio Cinquemani, John Lygeros
We present a dynamic programming-based solution to the problem of maximizing the probability of attaining a target set before hitting a cemetery set for a discrete-time Markov cont…
Stochastic model predictive control with bounded control inputs: a vector space approach
Debasish Chatterjee, Peter Hokayem, John Lygeros
We design receding horizon control strategies for stochastic discrete-time linear systems with additive (possibly) unbounded disturbances, while obeying hard bounds on the control…
On Stochastic Model Predictive Control with Bounded Control Inputs
Peter Hokayem, Debasish Chatterjee, John Lygeros
This paper is concerned with the problem of Model Predictive Control and Rolling Horizon Control of discrete-time systems subject to possibly unbounded random noise inputs, while s…