Distinct element method analysis of a retaining wall using a steel frame and fill materials

A technique is developed to clearly establish the shear resistance of a cellular structure, retaining wall composed of a steel frame and fill materials with both continuous and discontinuous characteristics. To overcome the limitation of the existing analysis approach based on continuum mechanics, in which the shear behavior and interaction between the frames and fill material of this type of structure are difficult to describe, this paper introduces displacement incremental analysis into the distinct element method. The results obtained by using the proposed approach are compared with experimental results to verify its accuracy. The results show an internal friction angle of fill materials and overburdening load are major factor determining the shear resistance of a retaining wall with a cellular structure type. From the results of the parametric study on the shear behavior of this type of structure, this paper also proposes a shear resistance moment-shear displacement formula for designing a retaining wall with a cellular structure type.     

Air‐ground Matching: Appearance‐based GPS‐denied Urban Localization of Micro Aerial Vehicles

In this paper, we address the problem of globally localizing and tracking the pose of a camera‐equipped micro aerial vehicle (MAV) flying in urban streets at low altitudes without GPS. An image‐based global positioning system is introduced to localize the MAV with respect to the surrounding buildings. We propose a novel air‐ground image‐matching algorithm to search the airborne image of the MAV within a ground‐level, geotagged image database. Based on the detected matching image features, we infer the global position of the MAV by back‐projecting the corresponding image points onto a cadastral three‐dimensional city model. Furthermore, we describe an algorithm to track the position of the flying vehicle over several frames and to correct the accumulated drift of the visual odometry whenever a good match is detected between the airborne and the ground‐level images. The proposed approach is tested on a 2 km trajectory with a small quadrocopter flying in the streets of Zurich. Our vision‐based global localization can robustly handle extreme changes in viewpoint, illumination, perceptual aliasing, and over‐season variations, thus outperforming conventional visual place‐recognition approaches. The dataset is made publicly available to the research community. To the best of our knowledge, this is the first work that studies and demonstrates global localization and position tracking of a drone in urban streets with a single onboard camera.     

Factor Graph Modeling of Rigid‐body Dynamics for Localization,Mapping, and Parameter Estimation of a Spinning Object in Space

This paper presents a new approach for solving the simultaneous localization and mapping problem for inspecting an unknown and uncooperative object that is spinning about an arbitrary axis in space. This approach probabilistically models the six degree‐of‐freedom rigid‐body dynamics in a factor graph formulation. Using the incremental smoothing and mapping system, this method estimates a feature‐based map of the target object, as well as this object's position, orientation, linear velocity, angular velocity, center of mass, principal axes, and ratios of inertia. This solves an important problem for spacecraft proximity operations. Additionally, it provides a generic framework for incorporating rigid‐body dynamics that may be applied to a number of other terrestrial‐based applications. To evaluate this approach, the Synchronized Position Hold Engage Reorient Experimental Satellites (SPHERES) were used as a testbed within the microgravity environment of the International Space Station. The SPHERES satellites, using body‐mounted stereo cameras, captured a dataset of a target object that was spinning at ten rotations per minute about its unstable, intermediate axis. This dataset was used to experimentally evaluate the approach described in this paper, and it showed that it was able to estimate a geometric map and the position, orientation, linear and angular velocities, center of mass, and ratios of inertia of the target object.     

Nonlinear Gains Recursive Sliding Mode Dynamic Surface Control with Integral Action

In this paper, by introducing a function with nonlinear gains and developing sliding surfaces with integral action in the dynamic surface control (DSC) recursive procedure, a novel DSC strategy is proposed. The drawbacks of conventional DSC methods, such as being sensitive to the design constant of the first order low‐pass filter and being unable to achieve zero steady‐state error for step reference signal, are overcome. Moreover, improvement of transient performance and reduction of control effort can be obtained. The stability analysis shows that the proposed new approach can guarantee semi‐global uniform ultimate boundedness (SGUUB) of all closed‐loop signals and that the ultimate tracking error bound in regulation can be made arbitrarily small.     

Heuristic Dynamic Programming Using Echo State Network For Multivariable Tracking Control Of Wastewater Treatment Process

This paper proposes a heuristic dynamic programming (HDP) scheme to simultaneously control the dissolved oxygen concentration and the nitrate level in wastewater treatment processes (WWTP). Unlike traditional HDP schemes, the optimal control values are calculated in an analytical way by the proposed HDP controller. It can reduce the learning burden of the HDP controller to a great extent. The system model and the evaluation index J are approximated by two echo state networks (ESNs). Gradient‐based learning algorithms are employed to train both ESNs online, and the convergence of the training algorithm is investigated based on Lyapunov theory. The performance of the proposed ESN‐based HDP (E‐HDP) controller is tested and evaluated on a WWTP benchmark. Experimental results demonstrate that the proposed approach can achieve effective performance.     

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.     

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.