Name
Title | ||
|---|---|---|
Optimal control of partially observable discrete time stochastic hybrid systems for safety specifications |
Abstract | ||
|---|---|---|
This paper describes a theoretical framework for the design of controllers to satisfy probabilistic safety specifications for partially observable discrete time stochastic hybrid systems. We formulate the problem as a partial information stochastic optimal control problem, in which the objective is to maximize the probability that the state trajectory remains within a given safe set in the hybrid state space, using observations of the history of inputs and outputs. It is shown that this optimal control problem, which has a multiplicative payoff structure, is equivalent to a terminal payoff problem when the state space is augmented with a binary random variable capturing the safety of past state evolution. This allows us to derive a sufficient statistic for the probabilistic safety problem as a set of Bayesian filtering equations updating a conditional distribution on the augmented state space, as well as an abstract dynamic programming algorithm for computing the maximal probability of safety and an optimal control policy. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ACC.2013.6580815 | American Control Conference |
Keywords | Field | DocType |
Bayes methods,control system synthesis,discrete time systems,dynamic programming,observability,optimal control,state-space methods,statistical distributions,stochastic systems,Bayesian filtering equations,abstract dynamic programming algorithm,augmented state space,binary random variable,conditional distribution,controller design,hybrid state space,input history observation,maximal safety probability,multiplicative payoff structure,output history observation,partial information stochastic optimal control problem,partially-observable discrete time stochastic hybrid systems,probabilistic safety specifications,state trajectory,sufficient statistics,terminal payoff problem | Random variable,Mathematical optimization,Optimal control,Discrete-time stochastic process,Control theory,Computer science,Probability distribution,Hybrid system,State space,Stochastic control,Stochastic game | Conference |
ISSN | ISBN | Citations |
0743-1619 | 978-1-4799-0177-7 | 10 |
PageRank | References | Authors |
0.59 | 13 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jerry Ding | 1 | 141 | 9.61 |
| Alessandro Abate | 2 | 1098 | 94.52 |
| Claire J. Tomlin | 3 | 1491 | 158.05 |