Block recursive parallelotopic bounding in set membership identification
Automatica (Journal of IFAC)
Robustness in Identification and Control
Robustness in Identification and Control
A linear matrix inequality approach to robust H∞filtering
IEEE Transactions on Signal Processing
Brief paper: Recursive state bounding by parallelotopes
Automatica (Journal of IFAC)
Technical Communique: Nonlinear bounded-error state estimation of continuous-time systems
Automatica (Journal of IFAC)
Brief paper: A set-membership state estimation algorithm based on DC programming
Automatica (Journal of IFAC)
Improved state estimation of stochastic systems
MATH'07 Proceedings of the 12th WSEAS International Conference on Applied Mathematics
Improved estimation of state of stochastic systems via invariant embedding technique
WSEAS Transactions on Mathematics
Reliable Robust Path Planning with Application to Mobile Robots
International Journal of Applied Mathematics and Computer Science - Verified Methods: Applications in Medicine and Engineering
Brief paper: Interval observer design for consistency checks of nonlinear continuous-time systems
Automatica (Journal of IFAC)
Robust MPC of constrained discrete-time nonlinear systems based on approximated reachable sets
Automatica (Journal of IFAC)
International Journal of Applied Mathematics and Computer Science
Zonotopic guaranteed state estimation for uncertain systems
Automatica (Journal of IFAC)
Hi-index | 22.15 |
This paper presents a new approach to guaranteed state estimation for non-linear discrete-time systems with a bounded description of noise and parameters. The main result is an algorithm to compute a set that contains the states consistent with the measured output and the given noise and parameters. This set is represented by a zonotope. The size of the zonotope is minimized each sample time by an analytic expression or by solving a convex optimization problem. Interval arithmetic is used to calculate a guaranteed trajectory of the process state. Two examples have been provided to clarify the algorithm.