Nonlinear formation control strategies for agents without relative measurements under heterogeneous networks

This paper proposes cooperative control protocols for a group of unmanned vehicles to make a stable formation around a maneuvering target. The control protocols are proposed on the basis of heterogeneous communication networks, which represents more challenging and generalized situations. Two different scenarios are considered. Separate control protocols are developed for each case. In both scenarios, agents do not have relative position, velocity, and acceleration measurements as feedback. In the first scenario, each agent uses its own position and velocity measurement in a consensus algorithm. In the second scenario, each agent needs only its own position information for the consensus algorithm. For both protocols, agents compute virtual estimates of a target's position and velocity and exchange these among the neighbors. Three different communication networks are used for exchanging two virtual estimates calculated by each agent and a time derivative of one virtual estimate. Each interagent communication network is represented by a fixed, undirected, and connected graph. Furthermore, it is considered that at least one agent receives the position, velocity, and acceleration information of the maneuvering target. It is not necessary that the agent receiving the target's position and the agent receiving the velocity and/or the acceleration information of the target be the same. However, the target does not receive any information about any agent. Stability of the formation is analyzed by using Barbalat's lemma. It is also shown that, despite the large difference in received information, the acceleration of the agents remains bounded for all time. The performance of the proposed formation control protocols is illustrated through numerical simulations.     

Dynamical system learning using extreme learning machines with safety and stability guarantees

This article presents a continuous dynamical system model learning methodology that can be used to generate reference trajectories for the autonomous systems to follow, such that these trajectories are invariant to a given closed set and uniformly ultimately bounded with respect to an equilibrium point inside the closed set. The autonomous system dynamics are approximated using extreme learning machines (ELM), the parameters of which are learned subject to the safety constraints expressed using a reciprocal barrier function, and the stability constraints derived using a Lyapunov analysis in the presence of the ELM reconstruction error. This formulation leads to solving a constrained quadratic program (QP) that includes a finite number of decision variables with an infinite number of constraints. Theorems are developed to relax the QP with infinite number of constraints to a QP with a finite number of constraints which can be practically implemented using a QP solver. In addition, an active sampling methodology is developed that further reduced the number of required constraints for the QP by only evaluating the constraints at a smaller subset of points. The proposed method is validated using a motion reproduction task on a seven degree-of-freedom Baxter robot, where the task space position and velocity dynamics are learned using the presented methodology.     

Development and model-based transparency analysis of an Internet-distributed hardware-in-the-loop simulation platform

This paper summarizes efforts to integrate, for the first time, two geographically dispersed hardware-in-the-loop simulation setups over the Internet in an observer-free way for an automotive application. The two setups are the engine-in-the-loop simulation setup at the University of Michigan (UM) in Ann Arbor, MI, USA, and the driver-in-the-loop ride motion simulator at the US Army Tank-Automotive Research, Development and Engineering Center (TARDEC) in Warren, MI, USA. The goal of such integration is to increase the fidelity of experiments and to enable concurrent geographically dispersed systems engineering. First, experiments with the actual hardware are presented. The concept of transparency is discussed, and the infeasibility of performing a baseline experiment with ideally integrated hardware is presented as a challenge to characterize the transparency of the experimental setup. This motivates the second half of the paper, in which a model-based approach is taken to analyze the transparency of the system. The conclusion is that an observer-free solution is feasible for integrating the two pieces of hardware over the Internet in a transparent manner, even if the nominal delay is increased by four times. It is also found that different signals in the system can exhibit different levels of transparency.     

15—THE UNWINDING OF YARNS FROM PACKAGES PART III: UNWINDING FROM CONICAL PACKAGES

Tables of calculated balloon parameters are given for a range of unwinding conditions when conical packages are used. Both single and double balloons are considered. Empirical formulae for estimating the yarn tension at the eye are deduced.     

Electronic Properties of ZnO: Band Structure and Directional Compton Profiles

The electronic band structure and directional Compton profiles (DCPs) of ZnO are studied in this work. Calculations are performed considering a set of three schemes based on density functional theory (DFT), the Hartree–Fock (HF) method, and a hybrid scheme. All band structures predict direct bandgaps. The best agreement with experiment is, however, shown by the hybrid scheme. The three schemes are also applied to compute DCPs along [100], [110], and [001] directions. These are compared with measurements made on single crystals of ZnO employing a 59.54 keV gamma-ray Compton spectrometer. Calculations overestimate the momentum density in the low-momentum region while underestimate the anisotropies. Positions of extremes in anisotropies deduced from calculations are well reproduced by the measured anisotropies in some cases. Within the experimental limits, the DCPs from the HF method are in better agreement with the measurements compared with DFT.     

Experimental characterization and finite element modeling of critical thrust force in cfrp drilling

Composite laminates are used in many applications in ae-rospace/defense industries due to their high strength-to-weight ratio and corrosion resistance properties. In general, composite materials are hard-to-machine materials which exhibit low drilling efficiency and drilling-induced delamination damage at exit. Hence, it is important to understand the drilling processes for composite materials. This article presents a comprehensive study involving experimental characterization of drilling process to understand the cutting mechanism and relative effect of cutting parameters on delamination during drilling of carbon fiber reinforced plastic (CFRP). Thrust force and torque data are acquired for analyzing the cutting mechanism, initiation and propagation of delamination, and identification of critical thrust force below which no damage occurs. An FE model for prediction of critical thrust force has been developed and validated with experimental results. A [0/90] composite laminate is modeled simulating the last two plies in exit condition and a thin interface layer is inserted in between the plies to capture delamination extent. The tool geometry is modeled as “rigid body” with geometric features of twist drill used in experiments. The tool is indented on the workpiece to simulated tool feeding action into the workpiece. The FE model predicts the critical thrust force within 5% of the experimentally determined mean value.     

Computational Analysis of Particle Nucleation in Dilution Tunnels: Effects of Flow Configuration and Tunnel Geometry

Measurement of fine particle emission from combustion sources is important to understand their health effects, and to develop emissions regulations. Dilution sampling is the most commonly used technique to measure particle number distribution because it simulates the mixing and cooling of combustion exhaust with atmospheric air, which drives nucleation and condensation of semi volatile material. Experiments suggest that the measured size distribution is dependent on the dilution ratio used and the tunnel design. In the present work, computational analysis using a large-eddy-simulation (LES) based model is performed to investigate the effect of tunnel flow and geometric parameters on H₂SO₄-H₂O binary nucleation inside dilution tunnels. Model predictions suggest that the experimental trends are likely due to differences in the intensity of turbulent mixing inside the tunnels. It is found that the interaction of dilution air and combustion exhaust in the mixing layer greatly impacts the extent of nucleation. In general, a cross-flow interaction with enhanced turbulent mixing leads to greater number of nucleation-mode particles than an axial-flow interaction of combustion sample and dilution air.

Copyright 2014 American Association for Aerosol Research