In this paper, an approach using observability and controllability grammian matrices is proposed to determine if structural damage has occurred together with an estimate of its location. The theory is outlined and simulations are carried out on a simple structure to demonstrate the method. Experimental tests were also carried out to demonstrate the validity of the approach using real signals. The dynamic properties of the structure are identified using the eigensystem realization algorithm (ERA) and a reduced order state-space model of the system subsequently constructed. Either the observability or controllability grammians can then be used depending on the number of sensors available. It is shown that these are sensitive to both the degree and location of the damage and offer promise for structural health monitoring applications.

The objective of this paper is to describe a new method for modeling aeroelastic system in time domain based on a modification of the Laguerre Polynomials to represent complex quantities. These polynomials are used to approximate the unsteady aerodynamics forces which are defined in the frequency domain using the Doublet Lattice Method (DLM). In this approach, the size of the matrices representing the aeroelastic system remains the same as the matrices representing the structural dynamics behavior. It is an important point since classical state space aeroelastic models include lag states increasing the size of the matrices used to represent the system. The applicability of the method is demonstrated by numerical simulation performed on the benchmark wing structure. The approach offers promise mainly for complex systems such as real aircraft. Recent works involving the use of control theory for aeroelasticity stability analysis, include the work of Silva et al. (2006) which an aeroservoelastic plant for HILDA (High Lift-to-Drag Active) wing was identified using experimental data. The impulse response (IR) method was applied in order to identify the state-space model and the generalized predictive control (GPC) method was used to

This paper deals with the study of algorithms for robust active vibration control in flexible structures considering uncertainties in system parameters. It became an area of enormous interest, mainly due to the countless demands of optimal performance in mechanical systems as aircraft, aerospace, and automotive structures. An important and difficult problem for designing active vibration control is to get a representative dynamic model. Generally, this model can be obtained using finite element method (FEM) or an identification method using experimental data. Actuators and sensors may affect the dynamics properties of the structure, for instance, electromechanical coupling of piezoelectric material must be considered in FEM formulation for flexible and lightly damping structure. The nonlinearities and uncertainties involved in these structures make it a difficult task, mainly for complex structures as spatial truss structures. On the other hand, by using an identification method, it is possible to obtain the dynamic model represented through a state space realization considering this coupling. This paper proposes an experimental methodology for vibration control in a 3D truss structure using PZT wafer stacks and a robust control algorithm solved by linear matrix inequalities.

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Most of the established procedures for analysis of aeroelastic flutter in the development of aircraft are based on frequency domain methods. Proposing new methodologies in this field is always a challenge, because the new methods need to be validated by many experimental procedures. With the interest for new flight control systems and nonlinear behavior of aeroelastic structures, other strategies may be necessary to complete the analysis of such systems. If the aeroelastic model can be written in time domain, using state-space formulation, for instance, then many of the tools used in stability analysis of dynamic systems may be used to help providing an insight into the aeroelastic phenomenon. In this respect, this paper presents a discussion on the use of Gramian matrices to determine conditions of aeroelastic flutter. The main goal of this work is to introduce how observability gramian matrix can be used to identify the system instability. To explain the approach, the theory is outlined and simulations are carried out on two benchmark problems. Results are compared with classical methods to validate the approach and a reduction of computational time is obtained for the second example.