Vibration suppression of smart composite beam using model predictive controller

Author:

Alsahlani Assaad1,Alsabery Ammar I.2,Al-Khateeb Amjed1,Eidan Adel A.1,Alshukri Mohammed J.3

Affiliation:

1. Najaf Technical College, Al-Furat Al-Awsat Technical University , 540011 Najaf , Iraq

2. Refrigeration & Air-Conditioning Technical, Engineering Department, The Islamic University , 540011 Najaf , Iraq

3. Department of Mechanical Engineering, Faculty of Engineering, Kufa University , 54002 Najaf , Iraq

Abstract

Abstract This work presents an adaptive model predictive control (MPC) strategy to suppress the vibration in a laminated composite beam. The control method incorporates a system identification algorithm to estimate the system parameters online, which provides a precise simulation of system dynamics. A fixed-free cantilever composite beam equipped with piezoelectric actuators was used to evaluate the efficacy of the control method. The sensors and actuators are securely bonded to the upper and lower surfaces at arbitrary locations along the beam’s length. A unified mechanical displacement field is applied to all layers, while displacements are considered independently for each layer. The beam is composed of eight layers of material, each with a thickness of 0.2 mm and orientations specified as (90°/0°/90°/0°). To achieve the best performance, the parameters of the MPC were adjusted numerically. The numerical analysis revealed that placing the actuator near the clamped end at the fixed end resulted in superior control outcomes, with a settling time of approximately 1.8 s. Conversely, the longest settling time occurred when the actuator was positioned at the free end, taking around 4 s. This model could potentially be expanded to address vibration in more intricate beams exhibiting nonlinear characteristics. The deflection readings measured at the end of the beam have been utilized as feedback control signals for predicting future behavior over a predetermined control horizon. The subsequent cost function is minimized through a quadratic equation to determine the sequence of optimal yet constrained control inputs. The suggested active vibration control system is then implemented and assessed numerically to examine the effectiveness of the control method.

Publisher

Walter de Gruyter GmbH

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