Simulated annealing based fixed order controller design and system simulations

Mahar, Faizullah; Ali, Syed Saad Azhar

doi:10.1109/iccaie.2011.6162127

Cited by 1 publication

(1 citation statement)

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“…Determination of optimal location of sensor-actuatorand controllers in AVC were successfully achievedusing genetic algorithm (GA) [9][10][11][12][13], particle swarm optimization (PSO)scheduling and network routing [18]. The tuning of Proportional-IntegralDirevative (PID) controller using ACO was successfully performed and reported [19][20][21], but these were tested only onarbitrary plants. Despite its simplicity, it was found out thatthe number of attempts using ACO in optimizing location of sensoractuator and controllers for AVC system is stillconsiderably low.…”

Section: Introductionmentioning

confidence: 99%

Ant Colony Optimization for Controller and Sensor-Actuator Location in Active Vibration Control

Nor

Muthalif

Wahid

2013

Journal of Low Frequency Noise, Vibration and Active Control

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Developing light weight yet stronger and more flexible panels in aircraft structure to with stand from failure due to vibration has been the interest of many researchers nowadays. Piezoelectric material has been the popular choice to attenuate vibration actively and numerous techniques of optimal control and actuator placement have been proposed. This paper discusseson active vibration control of a simply supported thin plate excited and actuated by piezoelectric patches. Mathematical model of the simply supported plate with piezoelectric patches is derived using Euler-Bernoulli model. The main focus is to find the optimal location of the collocated sensor-actuatorand controller gains using a swarm intelligent algorithm called Ant Colony Optimization (ACO) which later verified with Genetic Algorithm (GA). A simply supported plate is taken as a benchmark model to perform simulation study.

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