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Adaptive Genetic Algorithms with Elitist Strategy to the Design of Active Vibration controller for Linear Motors Position PlainChen, Yih-Ren 05 July 2001 (has links)
We use the adaptive probabilities of crossover and mutation, elitist strategy, and extinction and immigration strategy to improve the simple genetic algorithm in this study. We expect that the search technique can avoid falling into the local maximum due to the premature convergence, and the chance of finding the near-optimal parameter in the larger searching space could be obviously increased.
The accelerometer is then taken as the sensor for output measurement, and the designed actuator and digital PID controller is implemented to actively suppress the vibration of the plain that is due to the excitation effect of the high-speed and precision positioning of the linear motor. From the computer simulations and the experimented results, it is obvious that the near-optimal digital PID controller designed by modified genetic approach can improve the effect of vibration suppression; the settling time is also decrease. For the vibration suppressions of high-speed precision positioning problems, the vibrating plain system can fastly be stabilized.
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