## 1 Introduction
For a vibration mode, the frequency and damping of the underlying sinusoidal behavior are the basic parameters to be estimated. [PERSON] and [PERSON] [13] presented an algebraic derivative approach for online identification of the resonant frequencies of a flexible beam in the presence of noise and an offset. [PERSON] et al. [14] conducted an acceleration sensor based identification of modal frequencies for plate structures, including the first two bending and torsional modes. In order to estimate the model parameters of a flexible structure with collocated sensors/actuators, [PERSON] et al. [15] proposed a novel frequency domain subspace identification scheme using the negative imaginary approach. To obtain the experimental model of a flexible plate, several frequency domain subspace identification algorithms with the instrumental variable idea were addressed by [PERSON] et al. [16]. In addition, [PERSON] and [PERSON] [17] studied the application of the GA to identify the transfer function of a flexible manipulator system with collocated piezoelectric sensor/actuator. Due to the inherent distributed nature, flexible structures have an infinite number of modes. However, it is impossible to model and active control all these modes due to the computational and control limitations. In practice, the reduced order models of flexible structures are always developed by modal truncation, where only the dominant modes are considered [18]. Consequently, the problem of spillover associated with the un-modeled but often non-negligible modes is unavoidable, and the spillover effect will cause instability of the closed loop system [19]. Although great progress has been achieved in the field of modeling of smart flexible structures, the issue is still far from completely solved. Various studies have been conducted on the development and implementation of control algorithms for vibration suppression [20]. Classical feedback control strategies receive considerable attention as no adaptation time or reference signal is needed. Among those control methods, the poles placement method (PPM) is an effective approach for active vibration suppression despite its simplicity; it offersusers the possibility of placing the closed loop poles at some predetermined locations, which is desirable to set natural frequencies and damping ratios to specified values to achieve desired control performance [21]. [PERSON] and [PERSON] [22] applied the PPM for vibration control of the first dominant mode of flexible composite large I-beams, they further presented multi-mode vibration suppression of a cantilever beam using a poles placement controller with an observer [23]. [PERSON] et al. [24] proposed a robust poles placement controller for structural vibration control using receptance data. [PERSON] and [PERSON] [25] studied the use of the poles placement technique to achieve active vibration damping and positioning control of ball screw drives. [PERSON] et al. [26] developed a multi-input partial poles placement controller for vibration control of a glass-fiber beam using macro fiber composite (MFC) actuators. As the relocation of closed loop poles will alter the system stability characteristics and transient response, locations of the closed loop poles must be carefully determined. The remainder of this paper is organized as follows. In Section 2, the experimental setup of the smart flexible manipulator system is introduced. In Section 3, a reduced order transfer function model with relocated zeros compensating for the neglect of higher modes is proposed. A first-order inertia element is added to the model. The system identification procedure is described, and the identified results are presented. The proposed poles placement method is described in Section 4. A method where the move distance of the closed loop poles is the shortest is proposed. To achieve desired damping characteristics of the target modes, only the real part of the dominant poles is adjusted. Thus, the natural frequencies of the structure are not affected.