Fault Sensitivity Analysis of Data Feedback Control Design Based on Multiobjective Optimization Available to Purchase

This paper analyzes the fault sensitivity of data feedback control which is synthesized with H_∞/H_ optimization technique. With I/O data, a closed-loop output predictor is parameterized by stochastically uncertain Markov parameters which are estimated by least squares. The estimation error due to bias and noise are rejected over infinite horizon and guarantees mean square stability in the sense of worst case. The measured I/O data is setup as state which makes the stability analysis and data feedback control synthesis possible. In order to improve fault sensitivity, the H_ index method is applied. Then, the controller design problem based on multiobjective optimization approach is solved in a numerically efficient way such as Linear Matrix Inequality (LMI). The fault sensitivity is analyzed in the full frequency range and its effect on the pre-defined performance is described with a simulation example.