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The model identification loop is complemented with an optimal experimental design step.
Our aim was to determine the origin of the problem and to use the model identification loop presented here to improve the quality of the parameter estimates.
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This paper introduces a new robust-control-oriented system identification method, which consists of the following three steps: 1. High-order ARX model identification; 2. Loop shaping weighting functions design based on the high-order ARX model; 3. Control-oriented model reduction by minimizing the weighted L2-gap between the high-order ARX model and the low-order model.
The methodology for plant model identification in closed loop will be briefly surveyed and illustrated by experimental results.
A nonlinear boiler model is simulated as OPC server and OPC client is used for closed loop model identification, and to design a Model Predictive Controller.
The focus of this paper is on finding tuning rules based on model identification from a closed-loop step test.
This paper presents a generalized predictive control (GPC) strategy with closed-loop model identification for burn-through point (BTP) control in the sintering process.
Closed-loop identifications such as Closed-loop subspace model identification method (CL-MOESP) have been proposed recently and validated through simulations.
A dynamic model is derived for hovering flight conditions from closed-loop system identification experiments with the MOESP-type closed-loop subspace model identification method (CL-MOESP).
An adaptive damping controller design method by integrating online recursive closed-loop subspace model identification (SMI) with model predictive control theory is proposed in this paper.
Using the well-known lifting technique, the relation of a stack of the succeeding input samples to the output, i.e., the lifted model, is estimated using CL-MOESP, which is a closed-loop subspace model identification method.
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