Acting optimally in partially observable stochastic domains
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
COCOLOG: A Conditional Observer and Controller Logic for Finite Machines
SIAM Journal on Control and Optimization
On the Observability and Detectability of Continuous-Time Markov Jump Linear Systems
SIAM Journal on Control and Optimization
Design of Luenberger Observers for a Class of Hybrid Linear Systems
HSCC '01 Proceedings of the 4th International Workshop on Hybrid Systems: Computation and Control
Design of Observers for Hybrid Systems
HSCC '02 Proceedings of the 5th International Workshop on Hybrid Systems: Computation and Control
State estimation in multi-agent decision and control systems
State estimation in multi-agent decision and control systems
Distributed Algorithms for Cooperative Control
IEEE Pervasive Computing
Observability of linear hybrid systems
HSCC'03 Proceedings of the 6th international conference on Hybrid systems: computation and control
Existence of cascade discrete-continuous state estimators for systems on a partial order
HSCC'05 Proceedings of the 8th international conference on Hybrid Systems: computation and control
A separation principle for a class of hybrid automata on a partial order
ACC'09 Proceedings of the 2009 conference on American Control Conference
A partial order approach to discrete dynamic feedback in a class of hybrid systems
HSCC'07 Proceedings of the 10th international conference on Hybrid systems: computation and control
Automatica (Journal of IFAC)
Asynchronous H∞ filtering of discrete-time switched systems
Signal Processing
SIAM Journal on Control and Optimization
| Hi-index | 22.15 |
We address the problem of estimating discrete variables in a class of deterministic transition systems in which the continuous variables are available for measurement. We propose a novel approach to the estimation of discrete variables using lattice theory that overcomes some of the severe complexity issues encountered in previous work. The methodology proposed for the estimation of discrete variables is general as it is applicable to any observable system. Extensions generalize the approach to nondeterministic transition systems. The proposed estimator is finally constructed for a multi-robot system involving two teams competing against each other.