An online fault tolerant actor-critic neuro-control for a class of nonlinear systems using neural network HJB approach

In this paper, we propose an actor-critic neuro-control for a class of continuous-time nonlinear systems under nonlinear abrupt faults, which is combined with an adaptive fault diagnosis observer (AFDO). Together with its estimation laws, an AFDO scheme, which estimates the faults in real time, is designed based on Lyapunov analysis. Then, based on the designed AFDO, a fault tolerant actor- critic control scheme is proposed where the critic neural network (NN) is used to approximate the value function and the actor NN updates the fault tolerant policy based on the approximated value function in the critic NN. The weight update laws for critic NN and actor NN are designed using the gradient descent method. By Lyapunov analysis, we prove the uniform ultimately boundedness (UUB) of all the states, their estimation errors, and NN weights of the fault tolerant system under the unpredictable faults. Finally, we verify the effectiveness of the proposed method through numerical simulations.     

Move blocking strategy applied to re-entrant manufacturing line scheduling

Model predictive control (MPC)-based approach to fab-wide scheduling has been suggested to solve constraint-aware production optimization and in-process inventory level control simultaneously at each scheduling instance. However, application of this approach to real fab suffers from computational difficulties brought by the need to solve a huge optimization problem on-line as real fab scheduling problems are characterized by long cycle times, multiple product types, hundreds of machines/processing steps and re-entrant product flows. This study explores the use of an offset-blocking strategy combined with a modified recursive least square (RLS) estimation in the fab-wide scheduler, in order to alleviate the difficulty. The strategy is tested on a modified version of published case study called Intel Mini-Fab (IMF) problem. Despite its simplicity, the blocking strategy showed excellent performance in the face of realistic demand changes and plant/model mismatch.     

An approach to multi-agent interactive control in an intelligent space

International Journal of Control, Automation and Systems - A new type of multi-agent interactive control is proposed in an intelligent space system, which is based on heterogeneous multiple vision...     

Comparative evaluation of performance measures for human driving skills

In this paper, we evaluate the adequacy of several performance measures for the evaluation of driving skills between different drivers. This work was motivated by the need for a training system that captures the driving skills of an expert driver and transfers the skills to novice drivers using a haptic-enabled driving simulator. The performance measures examined include traditional task performance measures, e.g., the mean position error, and a stochastic distance between a pair of hidden Markov models (HMMs), each of which is trained for an individual driver. The emphasis of the latter is on the differences between the stochastic somatosensory processes of human driving skills. For the evaluation, we developed a driving simulator and carried out an experiment that collected the driving data of an expert driver whose data were used as a reference for comparison and of many other subjects. The performance measures were computed from the experimental data, and they were compared to each other. We also collected the subjective judgement scores of the driver’s skills made by a highly-experienced external evaluator, and these subjective scores were compared with the objective performance measures. Analysis results showed that the HMM-based distance metric had a moderately high correlation between the subjective scores and it was also consistent with the other task performance measures, indicating the adequacy of the HMM-based metric as an objective performance measure for driving skill learning. The findings of this work can contribute to developing a driving simulator for training with an objective assessment function of driving skills.     

A review of interoperability assessment models

Interoperability is the ability of systems to provide services to and accept services from other systems, and to use the services exchanged so as to operate together in a more effective manner. The fact that interoperability can be improved means that the metrics for measuring interoperability can be defined. For the purpose of measuring the interoperability between systems, an interoperability assessment model is required. This paper deals with the existing interoperability assessment models. A compara- tive analysis among these models is provided to evaluate the similarities and differences in their philosophy and implementation. The analysis yields a set of recommendations for any party that is open to the idea of creating or improving an interoperability assessment model.     

Ultrastructural investigation of intact orbital implant surfaces using atomic force microscopy

This study examined the surface nanostructures of three orbital implants: nonporous poly(methyl methacrylate) (PMMA), porous aluminum oxide and porous polyethylene. The morphological characteristics of the orbital implants surfaces were observed by atomic force microscopy (AFM). The AFM topography, phase shift and deflection images of the intact implant samples were obtained. The surface of the nonporous PMMA implant showed severe scratches and debris. The surface of the aluminum oxide implant showed a porous structure with varying densities and sizes. The PMMA implant showed nodule nanostructures, 215.56 ± 52.34 nm in size, and the aluminum oxide implant showed crystal structures, 730.22 ± 341.02 nm in size. The nonporous PMMA implant showed the lowest roughness compared with other implant biomaterials, followed by the porous aluminum oxide implant. The porous polyethylene implant showed the highest roughness and severe surface irregularities. Overall, the surface roughness of orbital implants might be associated with the rate of complications and cell adhesion. SCANNING 33: 211–221, 2011. © 2011 Wiley Periodicals, Inc.     

The effect of vacancies on the annular dark field image contrast of grain boundaries: a SrTiO(3) case study

The analysis of grain boundary structure in high resolution electron microscopy is often hindered by contrast variation within the grain boundary region which is not explained by simple models of the grain boundary structure. Recent work suggests that structural disorder along the beam direction and the presence of vacancies contribute significantly to this effect. One might expect a significant reduction in contrast in a Z-contrast image of a grain boundary would imply that vacancies present must result from the absence of heavier elements. Using a [001](210) Σ5 grain boundary in SrTiO₃ as a test case and first principles structure relaxation to calculate stable defect structures, we show that the reduction in the intensity from fully occupied Sr columns due to the structural distortion resulting from a nearby O vacancy can be as great as that due to introducing a Sr vacancy in the column itself. The effect on energy dispersive X-ray spectroscopy signals is also considered, but found to be smaller than that on Z-contrast images.     

A strong direct product theorem for quantum query complexity

We show that quantum query complexity satisfies a strong direct product theorem. This means that computing k copies of a function with fewer than k times the quantum queries needed to compute one copy of the function implies that the overall success probability will be exponentially small in k. For a boolean function f, we also show an XOR lemma—computing the parity of k copies of f with fewer than k times the queries needed for one copy implies that the advantage over random guessing will be exponentially small. We do this by showing that the multiplicative adversary method, which inherently satisfies a strong direct product theorem, characterizes bounded-error quantum query complexity. In particular, we show that the multiplicative adversary bound is always at least as large as the additive adversary bound, which is known to characterize bounded-error quantum query complexity.