Extensive research has been conducted in dynamic mathematical problems and real-time
industrial control applications, leading to the emergence of zeroing neural dynamics (ZND) …

In combination with a robotic arm, a mobile platform can fulfill complicated functions but may
encounter singularity problems. To solve them, this work investigates the kinematic control of …

Inspired by the nature of actual dynamics systems with time-varying parameters, varying-
parameter convergence differential neural network (termed as VP-CDNN) has been put …

This paper presents the collision-free solution to the inverse kinematics of a mobile
manipulator. The main contribution is to propose a novel inverse kinematics solution …

Manipulability optimization plays a crucial role in the kinematic control of redundant
manipulators, as it reduces their risks of entering a singular state. However, manipulability is …

In order to find the theoretical solution of a dynamic Sylvester equation (DSE) in noisy
environment, a robust fast convergence zeroing neural network (RFCZNN) is proposed in …

To avoid the task failure caused by joint breakdown during the collaborative motion planning
of dual-redundant robot manipulators, a neural dynamic fault-tolerant (NDFT) scheme is …

A robust noise-tolerant zeroing neural network (ZNN) is introduced for solving time-varying
linear matrix equations (TVLME). The convergence speed of designed neural dynamics is …

Redundant robots may undergo structural changes due to factors such as modifications,
which pose challenges to their precise control and obstacle avoidance. To resolve this …

The trajectory tracking control (TTC) is an indispensable part in mobile manipulator (MM)
application. The actual usage of the MM can be affected by factors, such as external noise …