Real-time robust adaptive fuzzy fractional-order control of electrically driven flexible-joint robots has been addressed in this paper. Two important practical situations have been considered: the fact that robot actuators have limited voltage, and the fact that current signals are contaminated with noise. Through of a novel voltage-based fractional order control for an integer-order dynamical ...

This work addresses an autonomous underwater vehicle (AUV) for applying nonlinear control which is capable of disturbance rejection via intelligent estimation of uncertainties. Adaptive radial basis function neural network (RBF NN) controller is proposed to approximate unknown nonlinear dynamics. The problem of designing an adaptive RBF NN controller was augmented with sliding mode robust term ...

This paper develops an adaptive controller for robot manipulators. The design decouples the system’s adaptation and control loops to allow for fast estimation rates, while guaranteeing robustness. The control scheme is tested in different manipulation scenarios, namely, (i) trajectory tracking where the desired joint motions are predefined and (ii) command following where the desired motions ar...

An adaptive robust approach for actuator fault-tolerant control of a class of uncertain nonlinear systems is proposed. The two chief ways in which the system performance can degrade following an actuator-fault are undesirable transients and unacceptably large steady-state tracking errors. Adaptive control based schemes can achieve good final tracking accuracy in spite of change in system parame...

A desired compensation adaptive robust control (DCARC) framework is presented for nonlinear systems having both parametric uncertainties and uncertain nonlinearities. The paper first considers a class of higher order nonlinear systems transformable to a normal form with matched model uncertainties. For this class of uncertain systems, the desired values of all states for tracking a known desire...