A new polynomial-time algorithm for linear programming
Combinatorica
Polytopes, graphs and optimisation
Polytopes, graphs and optimisation
A polynomial-time algorithm, based on Newton's method, for linear programming
Mathematical Programming: Series A and B
A compact algorithm for the intersection and approximation of N-dimensional polytopes
Mathematics and Computers in Simulation - Parameter identifications with error bound
Fast and robust algorithm to compute exact polytope parameter bounds
Mathematics and Computers in Simulation - Parameter identifications with error bound
An OL(n3) primal interior point algorithm for convex quadratic programming
Mathematical Programming: Series A and B
Optimal estimation theory for dynamic systems with set membership uncertainty: an overview
Automatica (Journal of IFAC)
Exact and efficient construction of Minkowski sums of convex polyhedra with applications
Computer-Aided Design
Brief paper: The minimal disturbance invariant set: Outer approximations via its partial sums
Automatica (Journal of IFAC)
Brief paper: Risk-sensitive filtering for jump Markov linear systems
Automatica (Journal of IFAC)
Brief paper: A set-membership state estimation algorithm based on DC programming
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Brief paper: Robust set-membership state estimation; application to underwater robotics
Automatica (Journal of IFAC)
Contributing vertices-based Minkowski sum computation of convex polyhedra
Computer-Aided Design
Robust filtering design for stochastic system with mode-dependent output quantization
IEEE Transactions on Signal Processing
Automatica (Journal of IFAC)
Monte Carlo Statistical Methods
Monte Carlo Statistical Methods
Efficient particle filtering for jump Markov systems. Application to time-varying autoregressions
IEEE Transactions on Signal Processing
Mathematical Foundations for Signal Processing, Communications, and Networking
Mathematical Foundations for Signal Processing, Communications, and Networking
State estimation for networked systems: an extended IMM algorithm
International Journal of Systems Science - Probability-constrained analysis, filtering and control
| Hi-index | 22.14 |
In this paper, we investigate the state estimation problem for a class of Markovian Jump Linear Systems (MJLSs) in the presence of bounded polyhedral disturbances. A set-membership estimation algorithm is first proposed to find the smallest consistent set of all possible states, which is shown to be expressed by a union of multiple polytopes. The posterior probabilities of the system jumping modes are then estimated by introducing the Lebesgue measure, based on which the optimal point estimate is further provided. Moreover, a similarity relationship for polytopes is defined and an approximate method is presented to calculate the Minkowski sum of polytopes, which can help reduce the computational complexity of the overall estimation algorithm.