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Genetic Approach with Elitist and Extinction Apply to the Design of Active Vibration ControllerChen, Chih-Kang 04 July 2000 (has links)
We use the elitist and extinction policies 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 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 controller designed by using genetic approach with elitist and extinction can improve the effect of vibration suppression; the settling time is also decrease. For the vibration suppressions of high-speed precision positioning problems, the results are satisfactory in the cases of short, middle and long distance.
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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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Human-Robot Interactive ControlJou, Yung-Tsan January 2003 (has links)
No description available.
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Control of a benchmark structure using GA-optimized fuzzy logic controlShook, David Adam 15 May 2009 (has links)
Mitigation of displacement and acceleration responses of a three story benchmark
structure excited by seismic motions is pursued in this study. Multiple 20-kN
magnetorheological (MR) dampers are installed in the three-story benchmark structure
and managed by a global fuzzy logic controller to provide smart damping forces to the
benchmark structure. Two configurations of MR damper locations are considered to
display multiple-input, single-output and multiple-input, multiple-output control
capabilities. Characterization tests of each MR damper are performed in a laboratory to
enable the formulation of fuzzy inference models. Prediction of MR damper forces by
the fuzzy models shows sufficient agreement with experimental results.
A controlled-elitist multi-objective genetic algorithm is utilized to optimize a set
of fuzzy logic controllers with concurrent consideration to four structural response
metrics. The genetic algorithm is able to identify optimal passive cases for MR damper
operation, and then further improve their performance by intelligently modulating the
command voltage for concurrent reductions of displacement and acceleration responses.
An optimal controller is identified and validated through numerical simulation and fullscale
experimentation. Numerical and experimental results show that performance of the
controller algorithm is superior to optimal passive cases in 43% of investigated studies.
Furthermore, the state-space model of the benchmark structure that is used in
numerical simulations has been improved by a modified version of the same genetic
algorithm used in development of fuzzy logic controllers. Experimental validation shows
that the state-space model optimized by the genetic algorithm provides accurate
prediction of response of the benchmark structure to base excitation.
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Angular Acceleration Assisted Stabilization Of A 2-dof Gimbal PlatformOzturk, Taha 01 October 2010 (has links) (PDF)
In this thesis work construction of the angular acceleration signal of a 2-DOF gimbal
platform and use of this signal for improving the stabilization performance is aimed.
This topic can be divided into two subtopics, first being the construction of angular
acceleration and the second being the use of this information in a way to improve
system performance. Both problems should be tackled in order to get satisfactory
results. The most important output of this work is defined as the demonstration of
the improvements obtained both theoretically and on experimental setup. Although
the system to be studied is a two axis gimbal platform, the results obtained can be
applied to other servo control problems. It is possible to define different performance
criteria for a servo control problem and different techniques will be addressed with
different control objectives. For this thesis work, the performance criterion is defined
as the stabilization performance of the platform. As a result, disturbance rejection
characteristics of the controller emerges as the main topic and methods for rejecting
these disturbances such as the friction torques and externally applied moments are
focused on throughout the studies. As expected, remarkable improvement is achieved
as a result of the use of acceleration feedback.
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