In this paper a second-order data-driven Active Disturbance Rejection Control (ADRC) is
merged with a proportional-derivative Takagi-Sugeno Fuzzy (PDTSF) logic controller …

In this paper, different learning methods based on Artificial Neural Networks (ANNs) are
examined to replace the default speed controller for high-precision position control and drift …

Calibrating the inverse kinematics of complex robots is often a challenging task. Finding
analytical solutions is not always possible and the convergence of numerical methods is not …

The vision-guided robot is intensively embedded in modern industry, but it is still a challenge
to track moving objects in real time accurately. In this paper, a hybrid adaptive control …

In the past, a robotic arm needed to be taught to carry out certain tasks, such as selecting a
single object type from a fixed location and orientation. Neural networks have autonomous …

Robotics include telerobotics, which involves controlling semi-autonomous robots from a
distance using communication networks such as Wi-Fi, Bluetooth, and the Deep Space …

During the past decades, robots have become an important part of human life. However, due
to algorithmic and hardware limitations, they have been unable to achieve high intelligence …

The derivation of a Tensor Product (TP)-based model of magnetic levitation systems using
the TP-based model transformation method is proposed. The TP model approximates the …

Inspired by the control system of voluntary movements developed in the human body based
on vision and neural system, this paper presents a new heuristic method merging artificial …