In this study, a data-driven technique is proposed to deal with multivariable fixed-order controller design. The method is based on the virtual reference feedback tuning (VRFT) philosophy and thus does not require any...
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In this study, a data-driven technique is proposed to deal with multivariable fixed-order controller design. The method is based on the virtual reference feedback tuning (VRFT) philosophy and thus does not require any model of the plant. Unlike standard VRFT for SISO systems, extended instrumental variables and variance weighting are used to counteract the effect of noise and achieve consistent controller estimate with a single set of input-output data. The proposed strategy is numerically compared to other existing direct and indirect techniques on a benchmark simulation example. The effectiveness of the method is finally tested on the airpath control of a real diesel engine.
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