those obtained for mode 2. The best results were obtained when the signal from SG3 was used in the feedback loop, as in case of CL2 and CL3, cone rming the initial predictions. Note that CL1 was in the case of FC1 limited in gain to guarantee the controller stability. The mostsevere, FC6 was the last to be tested. Because of the accumulative fatigue of the hardware (piezoelectricelements ),several attempts to close the loop with the MIMO controller were unsuccessful. During each attempt, an actuator on the upper group failed, resulting in a system automatic shutdown. The apparent reason was the proximity of these actuators to the most stressed region of the e n,nearthe loadcell.Therefore,a single input /singleoutput (SISO) controller was designed for commanding only the lower group of actuatorstoreducebuffetinginthee rstbendingmodeofthetailduring a closed-loop run at FC6. When feedback from accelerometer A2 and a nominal gain setting to increase chances of success were used, this SISO controller reduced the rms strain at SG3 by approximately 3% in the frequency range of 10 ‐20 Hz. Between 0 and 100 Hz, the rms strain at SG3 was reduced by approximately 2.5%. Conclusions A full-scale aircraft instrumented to reduce buffet loads was tested. The test represents an important step in the development of adaptive smart structures systems. Two groups of actuators consisting of piezoelectric elements distributed over the structure were designed to achieve authority over the e rst and second modes of the vertical e n. Very promising results were obtained in parametric studies using differentsensors in a two input/two output controllerusing the standard time-invariant linear quadratic Gaussian control law design. Based on the most important performance metric, the strain gauge located at the critical point for fatigue, vertical e n buffet attenuation of 57.5% (mode 2) and 33.3% (modes 1 and 2) for the nominal FC were observedduring thetests.Also,attenuationof18.3% (mode2) and 8.7% (modes 1 and 2) were verie ed for the next most severe buffeting case. In general, the CL that included at least one strain gauge in the feedback loop revealed better performance. This is an indication that strain gauges can be better correlated to the control objective, which is to reduce the structural strain generated by buffeting.