Robust multiple model adaptive control (RMMAC): a case study

Abstract

We evaluate the performance of the robust multiple model adaptive control (RMMAC) methodology by considering a mass-spring-dashpot (MSD) system subject to high-frequency disturbances that strongly excite all its lightly damped oscillatory modes. The results demonstrate the superior performance of the RMMAC and its variant RMMAC/XI architecture for a much more difficult adaptive control problem than that designed and analysed in Reference (Int. J. Adaptive Control Signal Processing, in press).

Multiple‐Model Adaptive Estimation with A New Weighting Algorithm

“…It is not difficult to see that algorithms (13), (14), (15), (16), (17), and (18) together with (A.8) guarantee with probability one that…”

“…Consider the weighting algorithm (13), (14), (15), (16), (17), and (18). Suppose there is a model, say M j ∈ M, which is closest to the true plant in the following sense with probability one where d is an unknown limited time instant.…”

“…Suppose there is a model, say M j ∈ M, which is closest to the true plant in the following sense with probability one where d is an unknown limited time instant. Then, the weighting algorithm (13), (14), (15), (16), (17), and (18) guarantees…”

A Set-Valued Approach to FDI and FTC of Wind Turbines

“…In this methodology, the selection of the dynamic weights is key to ensure proper disturbance rejection at the desired frequencies, as well as to avoid high-frequency command signals to be sent to the control inputs. Thus, the approach adopted in this paper is fully described in [61], and consists in optimizing a given performance criterion. In this particular case, the design diagram used is shown in Fig.…”

Damping of Low-Frequency Oscillations in Power Systems by Large-Scale PV Farms: A Comprehensive Review of Control Methods

“…One separate controller is designed, a priori, based on each model from the model bank. At each simulation phase, the actual response is compared with the response of the linearized models which are driven by the same control input [87]. The differences in the response of each model concerning the actual system response are used to generate individual model residuals.…”