The demand for electricity is increased due to the development of the industry, the
electrification of transport, the rise of household demand, and the increase in demand for …

Abstract The integration of Deep Learning (DL) and the Internet of Things (IoT) has
revolutionized technology in the twenty-first century, enabling humans and machines to …

As a classical and effective method for solving various time-varying problems, the zeroing
neural network (ZNN) is widely applied in the scientific and industrial realms. In plentiful …

Recently, robotic manipulators have been playing an increasingly critical part in scientific
research and industrial applications. However, modeling of robotic manipulators is …

Modeling accuracy of DC-DC converters may deviate largely in the presence of different
variation levels of constant power loads (CPLs), hence is well acknowledged as a main …

This brief proposes a bearing-only collision-free formation coordination strategy for
networked heterogeneous robots, where each robot only measures the relative bearings of …

In recent years, swarm intelligence optimization algorithms have been proven to have
significant effects in solving combinatorial optimization problems. Introducing the concept of …

An optimal and smooth trajectory for industrial robots has a positive impact on reducing the
execution time in an operation and the vibration in their joints. In this paper, a methodology …

This brief proposes a memory-based sampled-data consensus framework for general linear
multi-agent systems (MAS) in the presence of a class of nonlinear actuator faults (NAF). To …