Automatica (Journal of IFAC)
Composite adaptive control of robot manipulators
Automatica (Journal of IFAC)
Elements of artificial neural networks
Elements of artificial neural networks
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Contact impedance estimation for robotic systems
IEEE Transactions on Robotics
Neural-Network-Based Contact Force Observers for Haptic Applications
IEEE Transactions on Robotics
Force reflecting teleoperation with adaptive impedance control
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Neural-network predictive control for nonlinear dynamic systems with time-delay
IEEE Transactions on Neural Networks
Implementing online natural gradient learning: problems and solutions
IEEE Transactions on Neural Networks
The Effects of Simulated Inertia and Force Prediction on Delayed Telepresence
Presence: Teleoperators and Virtual Environments
Web-based mobile robot platform for real-time exercises
Expert Systems with Applications: An International Journal
Trends in the control schemes for bilateral teleoperation with time delay
AIS'11 Proceedings of the Second international conference on Autonomous and intelligent systems
Adaptive fuzzy logic control for time-delayed bilateral teleoperation
AIS'12 Proceedings of the Third international conference on Autonomous and Intelligent Systems
Remote minimally invasive surgery --haptic feedback and selective automation in medical robotics
Applied Bionics and Biomechanics - Surgical Robotics
Hi-index | 0.00 |
An early control methodology for time delayed plants is the Smith predictor, in which the plant model is utilized to predict the non-delayed output of the plant and move the delay out of the control loop. Recent Smith predictor based teleoperation control architectures have used linear or fixed-parameter dynamic approximations of the slave/environment at the master for environment contact prediction. This paper discusses and analyzes the performance of the previous work and proposes new architectures to overcome their shortcomings. The proposed architectures consist of a novel pseudo two-channel nonlinear predictive controller and its variations that use neural networks for online estimation of the slave and environment dynamics to replicate the environment contact force at the master using a similar local network. Intermittent contact experiments are conducted on a teleoperation test-bed consisting of two Planar Twin-Pantograph haptic devices. The experimental results with half a second delay demonstrate significant improvement in stability and performance by the proposed neural network based predictive control architectures over traditional force-position and linear Smith predictor based control architectures.