Title :
Advanced control techniques based in artificial intelligence for robotics manipulators
Author :
Almansa, A. ; De la Sen, Manuel
Author_Institution :
Dept. of Manuf. Process., ROBOTIKER, Bizkaia, Spain
Abstract :
The performance quality in nonlinear model based control of mechanical manipulators is conditioned to the reliability of the mathematical model and precision in the knowledge of all the involved parameters. Control methods based on artificial intelligence techniques (learning algorithms, system identification and neural networks) can be applied to improve its performance. A neural control scheme is proposed, consisting basically of a neural network for learning the robot inverse dynamics and online generating the control signal. Also an online supervision based on optimisation techniques is designed and implemented for such neural control. Simulation results are provided to evaluate the alternative variations to the proposed central scheme
Keywords :
identification; intelligent control; learning (artificial intelligence); manipulator dynamics; neurocontrollers; real-time systems; identification; inverse dynamics; learning algorithms; mathematical model; neural networks; neurocontrol; nonlinear model; online supervision; optimisation; robotics manipulators; Artificial intelligence; Artificial neural networks; Control systems; Design optimization; Learning; Manipulators; Mathematical model; Robots; Signal generators; System identification;
Conference_Titel :
Emerging Technologies and Factory Automation, 1999. Proceedings. ETFA '99. 1999 7th IEEE International Conference on
Conference_Location :
Barcelona
Print_ISBN :
0-7803-5670-5
DOI :
10.1109/ETFA.1999.815411
