Abstract
B ECAUSE the rotor of a helicopter operates in a periodic, asymmetric, unsteady aerodynamic environment, the helicopter fuselage produces a high level of vibration under the strong excitation of the rotor. The effective method for active vibration control of a helicopter fuselage by using the inertial actuators has been used in helicopters, but the inertia actuators have a considerable weight penalty for a better control effect. Meanwhile, the inertia actuators have a limited range of working frequency and a lag response to control signal. The piezoelectric stack actuator has a lot of advantages, such as light weight, large control force, wide range ofworking frequency, and fast response to control signal, and has been used as an actuation element for active control of structural vibration [1,2]. Hence, using the piezoelectric stack actuators is a newway to actively control the vibration of a helicopter fuselage. In an active vibration control system, the locations of actuators have a great influence on the effect of vibration suppression and the power requirement. Many approaches such as the controllability index [3], energy dissipation index [4],H2 norm index [5], and recent index composed of a multi-objective [6] have been developed to find the optimal actuator locations and control parameters. In the investigations of the helicopter fuselage, Hanagud and Babu [7] placed the piezoelectric actuator near the selected control location and investigated the vibration reduction of the helicopter fuselage by using H∞ control. Singhvi and Vennkatesan [8] addressed the piezoelectric stack actuator parallel with the supporting structure between the gearbox and fuselage for a simplified helicopter model. Heverly et al. [9] investigated the optimal placement of piezoelectric stack actuators in the fuselage by using the simulated annealing algorithm. The investigations indicated that the configuration of optimal distributed actuators was capable of greater vibration suppression with less control effort. However, in the existing investigations, the piezoelectric stack actuator was idealized as a force generator. In this case, the characteristic effect of the piezoelectric stack actuator was not included in the optimization process. The optimal locations of actuators may have a lot of selections at many possible positions in an actual structure. The optimal selection of actuator locations cannot uniquely be determined by using the conventional optimization techniques based on the gradient-descent methods. The genetic algorithm as a stochastic search technique has been effectively used to determine the optimal locations. Rao et al. [10] presented a modified binary-coded genetic algorithm to solve the optimal placement of discrete actuator locations in the framework of a zero–one optimization. Liu et al. [5] directly applied the binarycoded genetic algorithm to find optimal locations of actuators and sensors on plate structures. The real-coded genetic algorithm [4] was used to address the optimal locations of the piezoelectric actuators at a continuous spatial coordinate on a beam. Roy and Chakraborty [6] used the integer-coded genetic algorithm to optimize the placement of actuators and simultaneously real-coded genetic algorithm to determine the weighted matrices in the linear quadratic control. In this paper, the active control of a helicopter structural response by using piezoelectric stack actuators has been investigated. In the formulated dynamic model, the piezoelectric stack actuators and fuselage coupled composite structure was decomposed by using the substructure synthesis technique based on frequency response functions. The weighted quadratic of controlled accelerations in the frequency domain was chosen as the optimization index. An improved real-coded genetic algorithm was used to solve the optimization problem with discrete location variables and continuous weighted variables and to minimize the acceleration responses of the targeted locations. The vibration suppression of a simplified elastic helicopter fuselage model was analyzed. The numerical results show that the method proposed in this paper can effectively solve the optimal parameters and improve the control performance.
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