This paper presents a method to reduce the effect of uncertainties on dynamic systems by means of active control. In the proposed approach, pole placement is performed iteratively using an optimisation algorithm with an objective function that includes the variance of the real and imaginary part of each of the system's pole. The method is advantageous in that control gains are calculated using the method of receptances, which eliminates model form uncertainty since only measured receptance data is used. Moreover, variances are extracted through a polynomial chaos expansion, which requires fewer samples as opposed to other techniques. The method is demonstrated numerically on a simple multi-degree-of-freedom system. It is shown that active control can be used in a way that not only places the poles of the system but also reduces their spread. Furthermore, it is shown that it is possible to directly relate uncertainty in the poles to meaningful physical based uncertainty in the structural parameters.
展开▼
