Abstract Models are among the most essential tools in robotics, such as kinematics and
dynamics models of the robot's own body and controllable external objects. It is widely …

Systematization, and clustering, as the next key direction for AUVs to perform their functions,
is becoming an area of enthusiasm among related researchers. And this must be …

We show that for an adaptive controller that uses recorded and instantaneous data
concurrently for adaptation, a verifiable condition on linear independence of the recorded …

This paper presents an adaptive neural network (NN) control of a two-degree-of-freedom
manipulator driven by an electrohydraulic actuator. To restrict the system output in a …

For a 3-D underwater workspace with a variable ocean current, an integrated multiple
autonomous underwater vehicle (AUV) dynamic task assignment and path planning …

This paper addresses the robust trajectory tracking problem for a robot manipulator in the
presence of uncertainties and disturbances. First, a neural network-based sliding mode …

This paper investigates the problem of stabilization of sampled-data neural-network-based
systems with state quantization. Different with previous works, the communication limitation …

In this paper, a multilayer feedforward neural network-based approach is proposed for
human–robot collision detection taking safety standards into consideration. One multi-output …

ADAPTIVE control has been extensively studied for aerospace applications. Many active
research directions exist: for example, Lewis [1], Kim and Lewis [2], and Patiño et al.[3] have …

This paper focuses on a problem of event-triggered stabilization for a class of nonuniformly
sampled neural-network-based control systems (NNBCSs). First, a new event-triggered data …