Design of discrete time adaptive PID control systems with parallel feedforward compensator

This paper deals with the design of an adaptive PID control system with a parallel feedforward compensator (PFC) for discrete-time SISO systems and its application to water level control of a 3-tank system. The proposed method utilizes the characteristics of almost strict positive realness (ASPR) of the controlled plant. A conventional design scheme of a PFC which realizes an ASPR augmented controlled plant is also proposed. Further it is shown that the introduction of an internal model improves the control performance of the control system with the PFC. The effectiveness of the proposed method is confirmed through water level control experiments on a three-tank SISO system.     

An Interactive Design System of Free‐Formed Bamboo‐Copters

We present an interactive design system for designing free‐formed bamboo‐copters, where novices can easily design free‐formed, even asymmetric bamboo‐copters that successfully fly. The designed bamboo‐copters can be fabricated using digital fabrication equipment, such as a laser cutter. Our system provides two useful functions for facilitating this design activity. First, it visualizes a simulated flight trajectory of the current bamboo‐copter design, which is updated in real time during the user's editing. Second, it provides an optimization function that automatically tweaks the current bamboo‐copter design such that the spin quality—how stably it spins—and the flight quality—how high and long it flies—are enhanced. To enable these functions, we present non‐trivial extensions over existing techniques for designing free‐formed model airplanes [ UKSI14 ], including a wing discretization method tailored to free‐formed bamboo‐copters and an optimization scheme for achieving stable bamboo‐copters considering both spin and flight qualities.     

Estimation of a nonvisible field-of-view mobile target incorporating optical and acoustic sensors

This paper presents a nonvisible field-of-view (NFOV) target estimation approach that incorporates optical and acoustic sensors. An optical sensor can accurately localize a target in its field-of-view whereas the acoustic sensor could estimate the target location over a much larger space, but only with limited accuracy. A recursive Bayesian estimation framework where observations of the optical and acoustic sensors are probabilistically treated and fused is proposed in this paper. A technique to construct the observation likelihood when two microphones are used as the acoustic sensor is also described. The proposed technique derives and stores the interaural level difference of observations from the two microphones for different target positions in advance and constructs the likelihood through correlation. A parametric study of the proposed acoustic sensing technique in a controlled test environment, and experiments with an NFOV target in an actual indoor environment are presented to demonstrate the capability of the proposed technique.     

Compressive multi-spectral imaging using self-correlations of images based on hierarchical joint sparsity models

We propose a novel multi-spectral imaging method based on compressive sensing (CS). In CS theory, the enhancement of signal sparsity is important for accurate signal reconstruction. The main novelty of the proposed method is the employment of a self-correlation of an image, that is a local intensity similarity and multi-spectral correlation, to enhance the sparsity of the multi-spectral image to be recovered. Local intensity similarity, which is based on the concept that spatial changes in intensity are likely to be similar within local regions, contributes to sparsity enhancement. Furthermore, we exploit multi-spectral correlation to improve the sparsity of the multi-spectral components to be recovered. In order to simultaneously exploit different types of characteristics (i.e., local intensity similarity and multi-spectral correlation) for representing a signal as sufficiently sparse, we introduce a hierarchical joint sparsity model in the CS image recovery process. Our experiments show that the use of a self-correlation significantly improves the performance of multi-spectral image reconstruction.     

Performance of SOR methods on modern vector and scalar processors

The building-cube method (BCM) is a new generation algorithm for CFD simulations. The basic idea of BCM is to simplify the algorithm in all stages of flow computation to achieve large-scale simulations. Calculation of a pressure field using the Successive Over Relaxation (SOR) method consumes most of the total execution time required for BCM. In this paper, effective implementations on modern vector and scalar processors are investigated. NEC SX-9 and Intel Nehalem-EX are the latest vector and scalar processors. Those processors have much higher peak performances than their previous-generation processors. However, their memory bandwidth improvement cannot catch up with the performance improvement of processors. This is the so-called memory wall problem. In our paper, we discuss optimization techniques for implementation of the SOR method based on architectural characteristics of these modern processors, and evaluate their effects on the sustained performances of these processors for BCM.     

A pilot survey of 39 Victorian WWTP effluents using a high speed luminescent umu test in conjunction with a novel GC-MS-database technique for automatic identification of micropollutants

In 2007, samples of treated effluent were collected at point of discharge to the environment from 39 wastewater treatment plants (WWTPs) located across Victoria, Australia grouped by treatment type. Sample genotoxicity was assessed with a high-throughput luminescent umu test method using Salmonella typhimurium TL210 strain, with and without addition of a commercially available metabolic activation system. Samples were also screened using a gas chromatographic-mass spectrometric mass-structure database recognition method. A genotoxic response was observed in half of the samples tested without metabolic activation system (相似文献   

High rate nitrogen removal by the CANON process at ambient temperature

Completely autotrophic nitrogen removal over nitrite (CANON) is a cost-effective nitrogen removal process. Implementation of the CANON process relies on the cooperation of ammonium-oxidizing and Anammox bacteria, as well as the inhibition of nitrite-oxidizing bacteria. Strict limitations on dissolved oxygen (DO) concentration in the reactor, and the addition of sufficient inorganic carbon in the influent, were adopted as the main operational strategies. The reactor was fed with synthetic inorganic wastewater composed mainly of NH(4)(+)-N, and operated for 106 days. Stable nitrogen removal rates (NRR) of around 1.4 kg N m(-3) d(-1) were obtained at ambient temperature. Morphological characteristics and analysis of bacterial community confirmed the formation of functional outer aerobic and inner anaerobic granular sludge, providing evidence of stable nitrogen removal.     

Construction of a brain–machine hybrid system to evaluate adaptability of an insect

Insects perform adaptive behavior according to changing environmental conditions using comparatively small brains. Because adaptability is generated through the relationship among brain, body and environment, it is necessary to examine how a brain works under these conditions. In this study, to understand neural processing involved in adaptive behavior, we constructed a brain–machine hybrid system using motor signals related to the steering behavior of the male silkworm moth for controlling a two-wheeled mobile robot. We developed this hybrid system according to the following steps. (1) We selected steering signals corresponding to walking direction that were activated during neck swinging induced by optic flow and pheromone stimuli. (2) To control a robot by neural activity, we implemented a spike-behavior conversion rule such that frequency of the left and right neck motor neurons’ spikes was linearly converted into rotation of the wheels. (3) For electrophysiological multi-unit recordings on a robot, we developed small amplifiers. Using this hybrid system, we could observe the programmed behavioral pattern and orientation toward a pheromone source. Moreover, we compared the orientation behavior of moths and that of the hybrid system at different pheromone stimulus frequencies. From these experiments, we concluded that we could reconstruct silkworm moth behavior on the hybrid system.     

Variations of stress intensity factor of a semi-elliptical surface crack subjected to mixed mode loading

Maximum stress intensity factors of a surface crack usually appear at the deepest point of the crack, or a certain point along crack front near the free surface depending on the aspect ratio of the crack. However, generally it has been difficult to obtain smooth distributions of stress intensity factors along the crack front accurately due to the effect of corner point singularity. It is known that the stress singularity at a corner point where the front of 3 D cracks intersect free surface is depend on Poisson's ratio and different from the one of ordinary crack. In this paper, a singular integral equation method is applied to calculate the stress intensity factor along crack front of a 3-D semi-elliptical surface crack in a semi-infinite body under mixed mode loading. The body force method is used to formulate the problem as a system of singular integral equations with singularities of the form r ⁻³ using the stress field induced by a force doublet in a semi-infinite body as fundamental solution. In the numerical calculation, unknown body force densities are approximated by using fundamental density functions and polynomials. The results show that the present method yields smooth variations of mixed modes stress intensity factors along the crack front accurately. Distributions of stress intensity factors are indicated in tables and figures with varying the elliptical shape and Poisson's ratio.