Title :
A stable neural adaptive force controller for a hydraulic actuator
Author :
Daachi, B. ; Benallegue, A. ; Sirdi, N. K M
Author_Institution :
Lab. de Robotique, Paris, France
Abstract :
A neural network adaptive force controller is proposed for a real hydraulic system. The dynamic model of this system is highly non-linear and very complex to obtain. Thus, it is considered as a black box, and a priori identification becomes necessary. A neural network is used to approximate the model, then a controller using the Lyapunov approach is designed. The neural network parameters are updated online according to an adaptation algorithm obtained via stability analysis. The performance of the proposed neural network controller is validated on an experimental plant.
Keywords :
Lyapunov methods; actuators; adaptive control; control system synthesis; force control; force sensors; hydraulic control equipment; identification; neurocontrollers; position control; stability; three-term control; Lyapunov approach; a priori identification; adaptation algorithm; black box model; dynamic model; hydraulic actuator; neural network controller; stability analysis; stable neural adaptive force controller; Adaptive control; Adaptive systems; Control systems; Force control; Hydraulic actuators; Hydraulic systems; Neural networks; Nonlinear dynamical systems; Programmable control; Stability analysis;
Conference_Titel :
Robotics and Automation, 2001. Proceedings 2001 ICRA. IEEE International Conference on
Print_ISBN :
0-7803-6576-3
DOI :
10.1109/ROBOT.2001.933154
