Abstract. Gaussian process models provide a probabilistic non-parametric modelling approach for black-box identification of nonlinear dynamic systems. The Gaussian processes can h...
- This paper presents a unique approach for a model-based admission control algorithm for the IEEE 802.11e Enhanced Distributed Channel Access (EDCA) standard. The analytical model...
Nonlinear model predictive control (MPC) of a simulated chaotic cutting process is presented. The nonlinear MPC combines a neural-network model and a genetic-algorithm-based optim...
The dater equalities constitute a well-known tool which allows the description of Timed Event Graphs in the field of (max, +) algebra. This paper gives an equivalent model in the...
Abdelhak Guezzi, Philippe Declerck, Jean-Louis Boi...
In this paper we consider discrete-time nonlinear systems that are affected, possibly simultaneously, by parametric uncertainties and disturbance inputs. The min-max Model Predict...