A course in fuzzy systems and control
A course in fuzzy systems and control
Nonlinear Control Systems II
PD Control of robot with velocity estimation and uncertainties compensation
International Journal of Robotics and Automation
Expert Systems with Applications: An International Journal
A robust fuzzy logic controller for robot manipulators with uncertainties
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
An approach to online identification of Takagi-Sugeno fuzzy models
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
An online self-constructing neural fuzzy inference network and its applications
IEEE Transactions on Fuzzy Systems
Uniformly Stable Backpropagation Algorithm to Train a Feedforward Neural Network
IEEE Transactions on Neural Networks
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Regarding to the variations of the load and unmodeled dynamic, robot manipulators are known as a nonlinear dynamic system. Overcoming such problems like uncertainties and nonlinear characteristics in the model of two-link manipulator is the principal goal of this paper. To approach to this aim, a neural network is combined with a linear robust control in which the result has the advantages of, the first, approximated nonlinear elements and the second, the guaranteed robustness. To design the proposed controller, at first, multivariable feedback linearization is employed to convert the nonlinear model to linear one. Second, the unknown parameters of the system are identified by neural network based on a new proposed learning rule. Third, Mixed linear feedback-H驴驴驴 robust control method is proposed to stabilize the closed loop system. The closed loop system based on the proposed controller is analyzed and some numerical simulations are performed. Results show suitable responses of the closed loop system.