Dynamic sliding mode control (DSMC) of nonlinear systems using neural networks is proposed. In DSMC the chattering is removed due to the integrator which is placed before the input control signal of the plant. However, in DSMC the augmented system is one dimension bigger than the actual system i.e. the states number of augmented system is more than the actual system and then to control of such ...

The Direct Simulation Monte Carlo (DSMC) method was used to study the evaporation / condensation of iodine evaporating between parallel circular plates. The numerical 1D and 2D solutions are compared to the experimental result obtained by Mager et al.

It is widely known that losses due to viscous, thermal and molecular relaxation play an important role in sound propagation. Traditionally, acoustics is concerned with the treatment of the fluid as a (linear) continuum using macroscopic quantities such as velocity and pressure as dependent variables. However, the continuum model has its limitations and the model breaks down for Knudsen numbers ...

The open-frame structure of work-class ROVs results in significant model uncertainties, and its motion is strongly disturbed by the umbilical cable. To address these problems, this article developed a nonlinear disturbance observer-based super-twisting double-loop sliding-mode control (NDO-STDSMC) method to achieve trajectory tracking with system uncertainties external disturbances. First, new ...

In this work we present a hybrid particle-grid Monte Carlo method for the Boltzmann equation, which is characterized by a significant reduction of the stochastic noise in the kinetic regime. The hybrid method is based on a first order splitting in time to separate the transport from the relaxation step. The transport step is solved by a deterministic scheme, while a hybrid DSMC-based method is ...