Summary: The problem of designing two feedback controllers for an unknown plant based on input-output measurements is discussed within a linear setting. Virtual reference feedback tuning is a direct method that aims at minimising a cost function of the 2-norm type by using a set of data, then no model identification is needed. When constructing the cost function, two model-matching problems are considered between closed loop transfer function and sensitivity function simultaneously. In model-matching procedures, we design the virtual reference input signal and virtual disturb signal respectively. When applied virtual reference feedback tuning to a closed loop system with two degrees of freedom controllers, two filters used to reprocess the input-output measurements are derived. To relax the strict probabilistic description on disturbance, zonotope parameter identification algorithm is proposed to calculates a set that contains the unknown parameters consistent with the measured output and the given bound of the disturbance. To guarantee our derived zonotope not growing unbounded with iterations, a sufficient condition for this requirement to hold may be formulated as one linear matrix inequality. An application of zonotope parameter identification to a flight simulation with two unknown PID controllers is studied to demonstrate the effectiveness of our algorithms.