A critical review of the existing Internal Combustion Engine (ICE) modeling, optimization,
diagnosis, and control challenges and the promising state-of-the-art Machine Learning (ML) …

Air pollution has become an extremely serious problem, with particulate matter having a
significantly greater impact on human health than other contaminants. The small diameter of …

Data center (DC) plays an important role to support services, such as e-commerce and cloud
computing. The resulting energy consumption from this growing market has drawn …

Considering the bias of the dynamics which is a global trend of the dynamical equation of a
robot manipulator because of the gravity or the constant payloads, two kinds of adaptive bias …

Teleoperated robot systems are able to support humans to accomplish their tasks in many
applications. However, the performance of teleoperation largely depends on motor …

This paper presents an adaptive fuzzy control (AFC) for uncertain fractional-order neural
networks (FONNs) with input nonlinearities and unmodeled dynamics. System uncertainties …

In existing neural network (NN) learning control methods, the trajectory of NN inputs must be
recurrent to satisfy a stringent condition termed persistent excitation (PE) so that NN …

We present a comprehensive tutorial review that explores the application of bio-inspired
approaches to robot control systems for grappling and manipulating a wide range of space …

In this paper, a new multi-objective dimension-based firefly algorithm (MODFA) is proposed
for solving the constrained multi-objective optimal power flow (MOOPF) problem with …

A motion cueing algorithm (MCA) is employed to transform the linear and angular motion
signals generated from a motion simulator without violating the physical and dynamical …