In this paper, we are interested in deriving a non-intrusive numerical approach to construct nonlinear and linear parameter varying reduced order models from data. More specifically, based on data collected stable non-linear time-domain simulator or experimental bench, show how can infer either (quasi) dependent model. The proposed is very recent procedure called MII for Mixed Interpolation Inf...

Spatial variation in the importance of determinants of participation in the Aid to Families with Dependent Children program (AFDC) is investigated for the U.S. Casetti's Expansion Method is applied to the two-dimensional space domain by making the model's parameters a function of state x-y centroids. The spatially-varying parameter model suggests that the black populatioh's association with par...

This paper designs an Optimized Adaptive Combined Hierarchical Sliding Mode Controller (OACHSMC) for a time-varying crane model in presence of uncertainties. Uncertainties have always been one of the most important challenges in designing control systems, which include the unknown parameters or un-modeled dynamics in the systems. Sliding mode controller (SMC) is able to compensate the system in...

This paper presents case studies of robust algorithm of multi-parametric model predictive control (mpMPC). For discrete-time linear parameter-varying (LPV) systems, the robust algorithm is investigated based on the solution of the mpMPC problem for discrete-time linear time-invariant (LTI) systems. The algorithm provides a controller design method, adaptable to parameter changes of a LPV system...