Parameter sets for bounded-error data
Mathematics and Computers in Simulation
Set inversion via interval analysis for nonlinear bounded-error estimation
Automatica (Journal of IFAC) - Special section on fault detection, supervision and safety for technical processes
A survey of extreme point results for robustness of control systems
Automatica (Journal of IFAC) - Special issue on robust control
Robust Control: The Parametric Approach
Robust Control: The Parametric Approach
Methods and Applications of Interval Analysis (SIAM Studies in Applied and Numerical Mathematics) (Siam Studies in Applied Mathematics, 2.)
Brief paper: Guaranteed tuning, with application to robust control and motion planning
Automatica (Journal of IFAC)
C++ Toolbox for Verified Computing I: Basic Numerical Problems Theory, Algorithms, and Programs
C++ Toolbox for Verified Computing I: Basic Numerical Problems Theory, Algorithms, and Programs
| Hi-index | 22.14 |
Proving that an uncertain parametric model is stable amounts to prove the inclusion of two sets: the set A of all feasible parameters and the set B of all parameters for which the model is stable. In this paper, a new algorithm, able to decide whether or not A is included in B, is presented. The method is based on interval analysis which is a numerical tool able to deal with inequalities in a global and guaranteed way. Convergence properties of the algorithm are provided. The algorithm is then applied to the robust stability of a discrete-time model where the information on the parameters is given through bounded-error data. The behavior of the algorithm with respect to the number of parameters is illustrated on a continuous-time model.