6533b82bfe1ef96bd128d72d
RESEARCH PRODUCT
Adaptive Robot Control – An Experimental Comparison
Francesco AlongeFilippo D'ippolitosubject
0209 industrial biotechnologyArtificial neural networkComputer sciencelcsh:ElectronicsRobot manipulatorlcsh:TK7800-8360Control engineering02 engineering and technologylcsh:QA75.5-76.95Computer Science ApplicationsRobot control020901 industrial engineering & automationWaveletSettore ING-INF/04 - AutomaticaArtificial Intelligence0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processinglcsh:Electronic computers. Computer scienceSoftwareSimulationRobot control Model‐Based Adaptive control Wavelet based controldescription
This paper deals with experimental comparison between stable adaptive controllers of robotic manipulators based on Model Based Adaptive, Neural Network and Wavelet -Based control. The above control methods were compared with each other in terms of computational efficiency, need for accurate mathematical model of the manipulator and tracking performances. An original management algorithm of the Wavelet Network control scheme has been designed, with the aim of constructing the net automatically during the trajectory tracking, without the need to tune it to the trajectory itself. Experimental tests, carried out on a planar two link manipulator, show that the Wavelet-Based control scheme, with the new management algorithm, outperforms the conventional Model-Based schemes in the presence of structural uncertainties in the mathematical model of the robot, without pre-training and more efficiently than the Neural Network approach.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2012-11-01 | International Journal of Advanced Robotic Systems |