The use of ‘particle swarm’ to optimize the control system in a PZT laminated plate

Abstract

In many active noise and vibration control systems it is desired to reduce the vibration and also the noise emitted by flexible structures. With this objective the task of the controller is to control the maximum number of modes allowed by the control system's limitations. Some of the key parameters in the control system design for this purpose are the location, number and size of actuators and sensors on a flexible structure. In this paper a simply-supported thin plate with laminated piezoelectric sensors and actuators is studied for noise and vibration attenuation. For this purpose, a performance index based on Hankel singular values of the system is selected. The resulting nonlinear optimization problem is solved using a new particle swarm optimization (PSO) algorithm. The results are compared with a genetic algorithm and verified with a simple state-feedback controller.

Passive control of damaged composite laminates with optimized location of piezoelectric fiber composite patches

“…Optimum actuator voltages were found by employing PSO technique in an analysis conducted using PZT by Agrawal and Shafei [14]. Montazeri et al [15] optimized the system of a simply supported laminated thin plate for active noise and vibration control using PSO. Bargh and Sadr [16] investigated the lay-up scheme of symmetrically laminated composite plates for maximization of fundamental frequency by means of PSO algorithm.…”

Active Vibration Control of Flexible Plate Structures with Distributed Disturbances

“…Many techniques have been reported to find optimal locations of sensors and actuators. Methods for optimal placement of sensors and actuators have been investigated by many researchers [12][13][14][15]. All the research works have shown the importance of optimal placement of sensor and actuator for achieving a significant level of vibration suppression.…”

Vibration Suppression of Flexible Plate Structures Using Swarm and Genetic Optimization Techniques

“…This means that the locations of these transducers have significant influence on the performance of the control system as well as the controlled response. Many techniques have been reported on finding optimal locations of sensors and actuators [11][12][13][14][15]. Han and Lee, 1999 [11], have used genetic algorithms (GA) to find suitable locations of piezoelectric sensors and actuators of a cantilevered composite plate with considerations of controllability, observability and spillover prevention.…”

“…The performance function was based on the maximization of dissipation energy due to a control action. Other approaches to find optimal position of the sensors and actuators using particle swarm optimization (PSO) are reported in [14][15]. In [14], Rao et al have used PSO to determine optimal placement of piezoelectric patch actuators and accelerometer sensors alongside an H ∞ based controller to suppress the first three modes of vibration in a composite fin-tip with surface bonded piezoelectric actuators and accelerometer sensors.…”