**2.1. Design procedure**

680 Smart Actuation and Sensing Systems – Recent Advances and Future Challenges

structures in aeronautical applications are also presented.

considered.

form for beam and plate like structures.

In the literature, there are published review articles discussing fundamental aspects of active vibration control. Rao and Sunar [4] published a review paper on the use of piezoelectric materials as sensors and actuators for control of flexible structures. In this review paper, they presented the general framework of structural control strategies and presented the applications in various fields. One of the most common application areas is aerospace industry, since the aerospace structures are flexible and have limited tolerance for vibration. In a different review study, Loewy [5] presented the key applications of smart structures in aeronautical applications with potential usages. In this work, smart materials are categorized in terms of their energy-exchange capabilities. The benefits of using smart

The active vibration control systems should be feasible and reliable to be used in marine, aerospace and automotive applications. The reliability and feasibility of the control systems are related to dynamics of piezoelectric actuators and implementation of controller algorithms. Thus, it is needed to predict performance of the piezoelectric sensor and actuators embedded in control systems before implementation and production. For this purpose, Chee et al. [6] presented the modeling approaches for performance investigation of piezoelectric materials. As discussed in their article, analytical and finite element modeling of piezoelectric materials with host structures can be built using the linear constitutive piezoelectric equations only for low actuation authority. In case of high actuation authority; the nonlinearities occurs and different methodologies should be

The choice of the controller type and optimal positioning of sensors and actuators are other important aspects of design and implementation of active vibration control systems. There are also published technical review papers discussing the controller algorithms and optimal placement of actuators and sensors. For instance, Alkhatib and Golnaraghi [7] reviewed the controller architectures and presented the general design procedures for the active vibration control systems. In this review paper, the advantages and disadvantages of different controller architectures with various application examples are presented. Specifically that review paper states that the active damping system is advantageous when the vibration suppression is aimed only around resonance frequencies. It is also noted that the active damping system ensures stability when collocated sensor and actuator pairs are used. In another review paper, Gupta et al. [8] concentrated on the optimal positioning of piezoelectric sensors and actuators. In this technical review, the optimization techniques are presented based upon six optimizing criteria, namely (i) maximizing modal forces/moments applied by piezoelectric actuators, (ii) maximizing deflection of the host structure, (iii) minimizing control effort/maximizing energy dissipated, (iv) maximizing degree of controllability, (v) maximizing degree of observability, and (vi) minimizing spill-over effects. Gupta et al. presented the optimal positioning results in the literature in a tabular

For robust and adaptive active vibration control systems, the structural modeling techniques and estimation of uncertainties are important. A comprehensive methodology for the design Undesired mechanical vibrations and noise can be avoided or minimized by active vibration and noise control systems. The design of such systems starts with the dynamic characterization of the target structure that is called host structure for embedding or bonding the smart materials. The dynamic characterization procedure can be carried out numerically and/or experimentally by investigating the vibration characteristics of the structure. By utilizing sensors and actuators, system identification methods can be applied for modeling the whole system. The next step is the reduction of the developed model such that the computations can be performed in a reasonable time. In fact, the model reduction techniques shall be applied while considering the controllability and observability properties of the system. The steps between the characterization of the host structure and the reduced order model are referred as "modeling stage". Having determined the reducedorder model, the controller is designed and configured until the performance objectives are met. This stage is called the controller stage where the aim is to design and implement the controller for the performance requirements. The design steps of modeling and controller stages are presented in flow chart by Preumont [12] and depicted in Fig. 1. In the next section, the controller architectures will be discussed in detail.
