Robust Control of Nonlinear Uncertain Systems
Robust Control of Nonlinear Uncertain Systems
Nonlinear and Adaptive Control Design
Nonlinear and Adaptive Control Design
Neural Network Control of Robot Manipulators and Nonlinear Systems
Neural Network Control of Robot Manipulators and Nonlinear Systems
IROS '95 Proceedings of the International Conference on Intelligent Robots and Systems-Volume 2 - Volume 2
Algorithms and Software for Nanomanipulation with Atomic Force Microscopes
International Journal of Robotics Research
Robotic Micro-Assembly
"Videolized" atomic force microscopy for interactive nanomanipulation and nanoassembly
IEEE Transactions on Nanotechnology
A Suite of Robust Controllers for the Manipulation of Microscale Objects
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Robust adaptive control using a universal approximator for SISO nonlinear systems
IEEE Transactions on Fuzzy Systems
Stochastic choice of basis functions in adaptive function approximation and the functional-link net
IEEE Transactions on Neural Networks
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This paper presents a novel control methodology for automatically manipulating nano particles on the substrate by using Atomic Force Microscope AFM. The interactive forces and dynamics between the tip, particle and substrate are modeled and analyzed including the roughness effect of the substrate. Further, the control signal is designed to consist of the robust integral of a neural network NN output plus the sign of the error feedback signal multiplied with an adaptive gain. Using the NN-based adaptive force controller, the task of pushing nano particles is demonstrated in simulation environment. Finally, the asymptotical tracking performance of the closed-loop system, boundedness of the NN weight estimates and applied forces are shown by using the Lyapunov-based stability analysis.