At present, the levitation control methods of maglev vehicles are mostly based on the single-
point levitation model, ignoring the influence of coupling interference between multiple …

Aiming at the problem of poor transient performance of the control system caused by the
control uncertainty of the undertrained neural network, a neural network compensation …

Maglev transportation is a highly promising form of transportation for the future, primarily due
to its friction-free operation, exceptional comfort, and low risk of derailment. Unlike …

Real control systems require robust control performance to deal with unpredictable and
altering operating conditions of real-world systems. Improvement of disturbance rejection …

For improving the dynamic quality and steady-state performance, the hybrid controller based
on recurrent neural network (RNN) is designed to implement the position control of the …

The motivation of this paper is to solve the tracking control problem of hypersonic flight
vehicle (HFV) with uncertainties. To this end, a fixed-time neural network (NN)-based …

This paper studies a new fault-tolerant tracking control for magnetic levitation (MagLev)
systems. Remarkably, the controlled system not merely admits unknown functions, but also …

Magnetic levitation has been applied to maglev trains and magnetic suspension wind
tunnel. However, there are some problems with the existing levitation control. For example, it …

The magnetic levitation ball system is characterized by strong nonlinearity, multiple
disturbances, and intrinsic instability, which has long been a thorny problem in the field of …

In this study, we propose an improved linear active disturbance rejection control (I-LADRC)
method to achieve stable suspension of magnetic levitation balls. This method can not only …