Meysar Zeinali

TL;DR: In this paper, an approach for tracking control of robot manipulators is presented, which incorporates the approximately known inverse dynamic model output as a model-base portion of the controller; an estimated uncertainty term to compensate for the unmodeled dynamics, external disturbances, and time-varying parameters; and a decentralized PID controller as a feedback portion to enhance closed-loop stability and account for the estimation error of uncertainties.

TL;DR: In this paper, a nonlinear control approach based on adaptive sliding-mode control (ASMC) is employed to tackle the problem of engine torque control during regenerative mode, and the results show that the controller performs remarkably well in terms of the robustness, tracking error convergence, and disturbance attenuation.

TL;DR: In this article, a robust and adaptive sliding mode control is proposed and implemented to control the clad height in the laser cladding process, where the velocity of the substrate is used as a control input while the molten pool height is obtained using a charge-coupled device (CCD) camera and an image processing algorithm.

TL;DR: A fuzzy inverse dynamic model that describes the scanning speed as a function of the cladding parameters in particular the clad height is developed and results are very promising and show that fuzzy models can accurately describe the process dynamics.

TL;DR: In this article, a new and systematic approach to combine sliding mode control, adaptive control design techniques and PID control for tracking control of cable-driven parallel robot manipulators, in the presence of model uncertainties is presented.