Consequently, two versatile, computationally efficient and self-adaptive multi-resolution utilities namely, complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and the ensemble empirical mode decomposition (EEMD) algorithms are utilized to address these data non-stationarity issues, which if not resolved can lead to model prediction inaccuracies.
Based on the refinery time series data obtained by monitoring production status, a complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) is used to decompose the complex nonlinear time series.
Using real G data from Queensland, Australia's second largest state, and employing the support vector regression (SVR) model integrated with an improved version of empirical mode decomposition with adaptive noise (ICEEMDAN) tool, this study aims to propose a novel hybrid model: ICEEMDAN-PSO-SVR.
As to the dynamics, both exact dynamics and inexact dynamics with modeling error as well as bounded unknown disturbance are taken into account, based on which a proportional-derivative (PD) controller and a sliding mode controller with adaptive parameters are proposed respectively.
The proposed dynamic scheme shows better ASE performance than the static MIMO mode switching scheme with adaptive modulation.
In this scheme, adaptive output integral-type sliding mode is incorporated with adaptive unknown input observer to cope with aforementioned systems using only input and output information.
This paper develops a higher-order sliding mode (HOSM) differentiator with adaptive gains to address the exact tracking control problem using only input-output information of a wider class of nonlinear systems with disturbances and parametric uncertainties.
The dynamic MIMO mode switching scheme combined with adaptive modulation is then proposed in the section of rate-adaptive MIMO mode switching.
The mode switching scheme combined with adaptive modulation was proposed in[9, 10], but the analysis was focused on the static mode switching which depends only on the average SNR.
Figure 1 Block diagram of MIMO mode switching scheme combined with adaptive modulation.
