Ing. Loi Do

LAMMPS, an acronym for Large-scale Atomic and Molecular Massively Parallel Simulator, is a widely used open-source tool for high-fidelity molecular dynamics (MD) simulations. In this paper, we take the initial steps towards using LAMMPS for synthesis and validation of feedback control in nanoscale manipulation. We begin by introducing the field of MD itself, discussing the specific challenges related to control synthesis, applications of nanoscale manipulation, and the intricacies of high-fidelity MD simulations. Then, we explain the main steps in modeling a molecular system in LAMMPS and provide an illustrative example. In the example, we consider a nanoscale flake of molybdenum disulfide manipulated with the tip of an atomic force microscope over an atomic surface. We designed a simple PID controller to slide the flake with the microscope tip into a desired position. To run LAMMPS simulations with closed-loop control, we utilized the official Python wrapper for LAMMPS, upon which we implemented additional functionalities. We share the code of the simulations freely with the research community through a public repository.

This paper tailors synchronization of multi-agent systems to motion control of the Frenkel-Kontorova (FK) model, a one-dimensional chain of harmonically coupled identical particles in a spatially periodic potential field. In particular, the goal is to drive all particles in the FK model to the desired trajectory by controlling only a single—boundary—particle. The proposed solution augments harmonic coupling in the FK model with dissipative inter-particle interactions, allowing all particles in the chain to synchronize to a particular reference trajectory. The boundary control represents a special case of pinning control. Moreover, as the FK model describes the frictional dynamics of a nanosheet sliding over a surface, we use its synchronization for controlling the nanoscale sliding friction. The key idea is to introduce a sliding reference trajectory that allows particles to move near synchrony. Synchronization effectively increases the system’s stiffness, so less energy ends up dissipated through inter-particle relative motion, thus reducing the frictional force. We validate the proposed solution through numerical simulations.

In this paper, we document a design of a computational method for an onboard prediction of a breaking distance for a city rail vehicle|a tram. The method is based on an onboard simulation of tram braking dynamics. Inputs to this simulation are the data from a digital map and the estimated (current) position and speed, which are, in turn, estimated by combining a mathematical model of dynamics of a tram with the measurements from a GNSS/GPS receiver, an accelerometer and the data from a digital map. Experiments with real trams verify the functionality, but reliable identification of the key physical parameters turns out critically important. The proposed method provides the core functionality for a collision avoidance system based on vehicle-to-vehicle (V2V) communication.