this paper presents a discrete-time robust control for electrically driven robot manipulators in the task space. a novel discrete-time model-free control law is proposed by employing an adaptive fuzzy estimator for the compensation of the uncertainty including model uncertainty, external disturbances and discretization error. parameters of the fuzzy estimator are adapted to minimize the estimat...

this paper presents a stable new algorithm for force/position control in robot manipulators. in this algorithm, position vectors are measured by sensors and then used in the control law. since using force sensor has some issues such as high costs and technical problems, an approach is presented to overcome these issues. in this respect, force sensor is replaced by an adaptive fuzzy estimator to...

This paper deals with control of parallel manipulators for very high acceleration tasks including two case studies. The first one is the case of non-redundant parallel manipulators, where we are interested in control of PAR2 robot for 2D pick-andplace trajectories following. The proposed control scheme in this case is a nonlinear dual mode adaptive controller complied with a high gain state obs...

In this paper, a learning controller for robot manipulators is developed. The controller is proven to yield in a semi-global asymptotic result in the presence of additive input and output disturbances. Lyapunovbased techniques are used to guarantee that the tracking error is asymptotically driven to zero. Numerical simulation results are presented to demonstrate the viability of the proposed le...

This 'paper presents the development of a Proportional-Integral sliding mode controller for tracking problem of robot manipulators. A robust sliding mode controller is derived so that the actual trajectory tracks the desired trajectory as closely as possible despite the highly non-linear and coupled dynamics. The proposed controller is designed using the centralized and decentralized approaches...