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This paper presents a validation methodology of the dynamic behavior of an active viscous damper. The damper has two flexible metallic bellows connected to a rigid reservoir filled with fluid. When one of the bellows is connected to a vibrating structure a periodic flow passes through a variable internal orifice and the damping effect is produced. The size of the orifice is adjusted by a controlled linear piezoelectric actuator that positions the conical core into a conical cavity. The device finite element structural model consists of the valve body and its conical core that are assumed rigid and the flexible bellows are represented by two pistons with elastic suspensions. The flow developed inside the damper is modeled considering the fluid-structure interation, using the Lagrangean-Eulerian formulation. To validate the proposed model a prototype was constructed and experimental tests and numerical simulations are accomplished in the time domain, applying harmonic excitations. The results are compared using curves that relate the damping coefficient with the orifice size and with the input velocity applied at the bellows face. However, for the proper control design and system operation, the direct use of the finite element model becomes unviable due to its high computational time. Then, a reduced second order discrete dynamic model for the damper was developed. The model parameters are identified by analysis in the frequency domain, using impulsive excitation force, for constant and variable orifice sizes. At low excitation frequencies, the damper prototype behaves like a single degree of freedom system which damping factor changes with the orifice size A fuzzy controller was designed and it generates the orifice reference size associated to the desired damping factor. The active system presented better performance when compared to the passive one.

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This work proposes a methodology offirzzy controllers design. They are obtained by an optimization process that uses genetic algorithms. For this optimization procedure, the knowledge of the system dynamics is required. Therefore an artificial neural network is trained to model the dynamic behavior of the plant from the experimental inputs and outputs of the system. The rule base, the weights of the rules and the input membership firnctions are optimized. The proposed methodology is evaluoted experimentally on a steel cantilever beam confrolled by piezoelectric actuators. Those controllers are evaluated on time and fiequency domain. The obtained results confirm the eficiency $the proposed methodology.

This paper presents the numerical fuzzy control of an experimental active damper. The damper has two flexible metallic bellows connected to a rigid reservoir filled with fluid. When one of the bellows is connected to a vibrating structure, a periodic flow passes through a variable internal orifice and the damping effect is produced. The size of the orifice is adjusted by a control system that positions the conical core into a conical cavity. This paper presents the finite element model and an experimental reduced second order dynamic model of the damper prototype, which is suitable for applications where real time control is required. These simple model parameters are identified by an analysis on the frequency domain. Then using an impulsive excitation force for the constant orifice (passive system) as for the variable orifice (active system) the system is evaluated. A fuzzy controller was designed to simulate the operation of the active system. The obtained results show that the active damper has better efficiency compared to passive system.