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The purpose of this paper is to design a discrete indirect adaptive fuzzy controller for a robotic manipulator. This paper addresses how to overcome the approximation error of the fuzzy system and uncertainties for asymptotic tracking control of robotic manipulators. The uncertainties include parametric uncertainty, un-modeled dynamics, discretization error and external disturbances.

The proposed controller is model-free and voltage-based in the form of discrete-time Mamdani fuzzy controller. The parameters of fuzzy controller are adaptively tuned for asymptotic tracking of a desired trajectory. A robust control term is used to compensate the approximation error of the fuzzy system. An adaptive mechanism is derived based on the stability analysis.

The proposed model-free discrete control is robust against all uncertainties associated with the robot manipulator and actuators. The approximation error of the fuzzy system is well compensated to achieve asymptotic tracking of the desired trajectories. Stability analysis and simulation results show its efficiency in the tracking control.

A novel discrete indirect adaptive fuzzy controller is designed for electrically driven robot manipulators using the voltage control strategy. The novelty of this paper is compensating the approximation error of the fuzzy system and discretizing error for asymptotic tracking of the desired trajectory.

Discrete control of robot manipulators with uncertain model is the purpose of this paper.

The proposed control design is model-free by employing an adaptive fuzzy estimator in the controller for the estimation of uncertainty as unknown function. An adaptive mechanism is proposed in order to overcome uncertainties. Parameters of the fuzzy estimator are adapted to minimize the estimation error using a gradient descent algorithm.

The proposed model-free discrete control is robust against all uncertainties associated with the model of robotic system including the robot manipulator and actuators, and external disturbances. Stability analysis verifies the proposed control approach. Simulation results show its efficiency in the tracking control.

A novel model-free discrete control approach for electrically driven robot manipulators is proposed. An adaptive fuzzy estimator is used in the controller to overcome uncertainties. The parameters of the estimator are regulated by a gradient descent algorithm. The most gradient descent algorithms have used a known cost function based on the tracking error for adaptation whereas the proposed gradient descent algorithm uses a cost function based on the uncertainty estimation error. Then, the uncertainty estimation error is calculated from the joint position error and its derivative using the closed-loop system.