Hamid Toshani
Hamid Toshani
Ph.D Candidate in Electrical Engineering, Iran University of Science and Technology
Verified email at elec.iust.ac.ir
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Real-time inverse kinematics of redundant manipulators using neural networks and quadratic programming: a Lyapunov-based approach
H Toshani, M Farrokhi
Robotics and Autonomous Systems 62 (6), 766-781, 2014
Constrained generalised minimum variance controller design using projection-based recurrent neural network
H Toshani, M Farrokhi, Y Alipouri
IET Control Theory & Applications 11 (2), 143-154, 2017
Kinematic control of a seven DOF robot manipulator with joint limits and obstacle avoidance using neural networks
H Toshani, M Farrokhi
The 2nd International Conference on Control, Instrumentation and Automation …, 2011
Robust chattering-free optimal sliding-mode control using recurrent neural networks: An H-based approach
H Toshani, M Farrokhi
Transactions of the Institute of Measurement and Control 41 (13), 3565-3580, 2019
Optimal sliding‐mode control of linear systems with uncertainties and input constraints using projection neural network
H Toshani, M Farrokhi
Optimal Control Applications and Methods 39 (2), 963-980, 2017
Control of magnetic levitation system using recurrent neural network-based adaptive optimal backstepping strategy
A Fatemimoghadam, H Toshani, M Manthouri
Transactions of the Institute of Measurement and Control 42 (13), 2382-2395, 2020
Consensus tracking of multi-agent systems using constrained neural-optimiser-based sliding mode control
R Rahmani, H Toshani, S Mobayen
International Journal of Systems Science 51 (14), 2653-2674, 2020
Vibration Analysis of Brushless Doubly Fed Machines in the Presence of Rotor Eccentricity
S Abdi, E Abdi, H Toshani, R McMahon
IEEE Transactions on Energy Conversion 35 (3), 1372-1380, 2020
Inverse Kinematics of 7 DOF Robot Manipulator under Joint Angle Limits and Obstacle in the Workspace of Robot using Neural network, Fuzzy System and Quadratic Programming Approach
H Toshani, M Farrokhi
Journal of Control 6 (2), 23-37, 2012
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