Stability limit of human-in-the-loop model reference adaptive control architectures

Model reference adaptive control (MRAC) offers mathematical and design tools to effectively cope with many challenges of real-world control problems such as exogenous disturbances, system uncertainties and degraded modes of operations. On the other hand, when faced with human-in-the-loop settings, these controllers can lead to unstable system trajectories in certain applications. To establish an understanding of stability limitations of MRAC architectures in the presence of humans, here a mathematical framework is developed whereby an MRAC is designed in conjunction with a class of linear human models including human reaction delays. This framework is then used to reveal, through stability analysis tools, the stability limit of the MRAC–human closed-loop system and the range of model parameters respecting this limit. An illustrative numerical example of an adaptive flight control application with a Neal–Smith pilot model is presented to demonstrate the effectiveness of developed approaches.     

Wear estimation by testing the elastic behavior of tool surface

Impedance and Lamb wave structural health monitoring (SHM) techniques are two common approaches used to successfully monitor the integrity of a variety of structures. In this paper, the feasibility of applying both methods for monitoring tool wear is investigated. Additionally, the surface response to excitation (SuRE) was investigated using spectrum analyzers an alternative to the costlier impedance method. Three approaches were used to monitor the condition of both new and artificially worn drill bits. Artificial degradation of the drill bit cutting edges was necessary to avoid any possible data contamination from accidental damage to the sensors or wiring in a harsh machining environment. The estimated magnitude characteristics found from the impedance and spectrum analyzers correctly distinguished between new and worn tools. Lamb wave characteristics were represented by the envelopes of the propagated signal. The S-transformation was then used to obtain the envelope of the harmonic component of the signal at the excitation frequency. The envelopes were nearly identical at similar tool wear levels, and envelope characteristics changed significantly when Lamb wave reflections reached the sensor from the worn cutting edges. The study indicated that each of the three approaches used successfully detected tool wear.     

A multi-modal discrete-event simulation model for military deployment

This paper introduces a logistics and transportation simulation that can be used to provide insights into potential outcomes of proposed military deployment plans. More specifically, we model a large-scale real-world military deployment planning problem (DPP) that involves planning the movement of military units from their home bases to their final destinations using different transportation assets on a multi-modal transportation network. We apply, for the first time, the event graph methodology and listener event graph object framework to create a simulation model of the DPP. We use and extend Simkit, an open-source Java Application Programming Interface for creating discrete-event simulation (DES) models. We use a medium-resolution modeling approach, as opposed to either high-resolution or low-resolution modeling paradigms, to reduce lengths of simulation runs without compromising reality. To accurately incorporate real and detailed transportation network data into the simulation, we use GeoKIT, a licensed, state-of-the-art, Java-based geographical information system. While our DES model is not a panacea for all, it allows for testing the feasibility and sensitivity of deployment plans under stochastic conditions prior to committing members of the military into harm’s way. The purpose of the paper is to acquaint the readers with the details of the DPP, the simulation model created, and the results of the analysis of a typical real-world case study.     

Estimation of the chatter zones of drilled holes by using s-transformation

S-transformation based on diagnostic of machining operations from displacement, velocity, torque, and force data is proposed. Damping ratio was calculated from the time-frequency-amplitude plots of the s-transformation. The values were called damping index by considering the influence of the window functions on the calculations. Variance of the damping index in a small band around the first natural frequency of the system was found an effective chatter detection tool. The s-transformation of all the signals considered had similar characteristics and the sharp drop of the variance of the damping index indicated chatter development.     

Identification of the prefailure phase in microdrilling operations using multiple sensors

The life of microdrills with a diameter of less than 1 mm is short and unpredictable. Estimation of tool wear and the prefailure phase are more difficult than conventional drilling operations since most special machine tools for microdrilling have stepping motors that create fluctuating forces which consequently produce vibration. In this paper, a new method is proposed for detection of the prefailure phase of microdrilling, just 0.2 to 1 s before breakage occurs. The system measures the thrust force and microdrill velocity by using a dynamometer and a laser vibrometer, respectively. Seven characteristic features of the signals are obtained by describing their shape and spike characteristics. Adaptive Resonance Theory (ART2)-based neural networks are used for interpretation of the signal features. The proposed system accurately classified all the cases studied when a vigilance parameter of 0.995 of the ART2-type neural network was selected.     

Output feedback adaptive command following and disturbance rejection for nonminimum phase uncertain dynamical systems

In this paper, we develop an output feedback adaptive control framework for continuous‐time nonminimum phase multivariable systems for output stabilization, command following, and disturbance rejection. The approach is based on a nonminimal state space realization that generates an expanded set of states using the filtered inputs and filtered outputs and their derivatives of the original system. Specifically, a direct adaptive controller for the nonminimal state space model is constructed using the expanded states of the nonminimal realization and is shown to be effective for multi‐input, multi‐output nonminimum phase systems with unstable dynamics. The adaptive controller does not require any model information nor does it require information of the system poles and system zeros or estimation of the system Markov parameters. Several illustrative numerical examples are provided to demonstrate the efficacy of the proposed approach. Copyright © 2010 John Wiley & Sons, Ltd.     

A case study on trace metals in surface sediments and dissolved inorganic nutrients in surface water of Olüdeniz Lagoon-Mediterranean, Turkey

Hydro-chemical parameters (salinity, temperature, pH, dissolved oxygen, nitrate, silicate and phosphate) in seawater and major trace metals (Al, Fe, Mn, Cr, V, Zn, Pb, Cu) in sediments were evaluated for the assessment of quality of seawater and sediments in very small lagoon in Mediterranean, Olüdeniz. Enrichment factors for metals in sediment were in the range of 1.62-8.09, comparable to crustal rock composition. For metals, comparison with literature data revealed relatively low metal concentrations for Olüdeniz sediments. Correlation analyses on the sediment metal data showed strong correlation in between Cr, Fe and Zn. Surface water salinity slightly decreases within the lagoon, indicating that limited fresh waters inflow to the lagoon. In October, the lagoon waters contained very low phosphate concentrations but measurable values of nitrate and silicate, yielding high NO(3)(-)/PO(4)(3-) ratios (90). Very low Chlorophyll-a (biomass indicator) concentrations measured in the lagoon suggest the phosphorus limitation of primary productivity.