Knowledge-based control and case-based diagnosis based upon empirical knowledge and fuzzy logic for the SBR plant.

Because biological wastewater treatment plants (WWTPs) involve a long time-delay and various disturbances, in general, skilled operators manually control the plant based on empirical knowledge. And operators usually diagnose the plant using similar cases experienced in the past. For the effective management of the plant, system automation has to be accomplished based upon operating recipes. This paper introduces automatic control and diagnosis based upon the operator's knowledge. Fuzzy logic was employed to design this knowledge-based controller because fuzzy logic can convert the linguistic information to rules. The controller can manage the influent and external carbon in considering the loading rate. The input of the controller is not the loading rate but the dissolved oxygen (DO) lag-time, which has a strong relation to the loading rate. This approach can replace an expensive sensor, which measures the loading rate and ammonia concentration in the reactor, with a cheaper DO sensor. The proposed controller can assure optimal operation and prevent the over-feeding problem. Case-based diagnosis was achieved by the analysis of profile patterns collected from the past. A new test profile was diagnosed by comparing it with template patterns containing normal and abnormal cases. The proposed control and diagnostic system will guarantee the effective and stable operation of WWTPs.     

Simulation of humidity control and greenhouse temperature tracking in a growth chamber using a passive air conditioning unit

In this paper, we define a dynamic discrete model of a passive air conditioning unit, without the more typical compression or absorption-refrigeration cycle. The unit is composed of heat exchangers, a positioning system and humid corrugated pads. The aim of the study was to follow the temperature in a greenhouse and to replicate it with a desired and stable relative humidity in a ventilated growth chamber. A control law, based on a quadratic criterion and dynamic programming, taking output error and energy consumption minimisation into account, was used to control the behaviour of the unit in spite of air intake disturbances. The results of the simulation indicate that the air conditioning unit can produce a variable climate in the growth chamber, with a wide range of relative humidity setpoints.     

The influence of Johnson–Cook material constants on finite element simulation of machining of AISI 316L steel

In literature, five different sets of work material constants used in the Johnson–Cook's (J–C) constitutive equation are implemented in a numerical model to describe the behaviour of AISI 316L steel. The aim of this research is to study the effects of five different sets of material constants of the J–C constitutive equation in finite-element modelling of orthogonal cutting of AISI 316L on the experimental and predicted cutting forces, chip morphology, temperature distributions and residual stresses. Several experimental equipments were used to estimate the experimental results, such as piezoelectric dynamometer for cutting forces measurements, thermal imaging system for temperature measurements and X-ray diffraction technique for residual stresses determination on the machined surfaces; while an elastic–viscoplastic FEM formulation was implemented to predict the local and global variables involved in this research. It has been observed that all the considered process output and, in particular the residual stresses are very sensitive to the J–C's material constants.     

A distributed adverse drug reaction detection system using intelligent agents with a fuzzy recognition‐primed decision model

Discovering unknown adverse drug reactions (ADRs) in postmarketing surveillance as early as possible is highly desirable. Nevertheless, current postmarketing surveillance methods largely rely on spontaneous reports that suffer from serious underreporting, latency, and inconsistent reporting. Thus these methods are not ideal for rapidly identifying rare ADRs. The multiagent systems paradigm is an emerging and effective approach to tackling distributed problems, especially when data sources and knowledge are geographically located in different places and coordination and collaboration are necessary for decision making. In this article, we propose an active, multiagent framework for early detection of ADRs by utilizing electronic patient data distributed across many different sources and locations. In this framework, intelligent agents assist a team of experts based on the well‐known human decision‐making model called Recognition‐Primed Decision (RPD). We generalize the RPD model to a fuzzy RPD model and utilize fuzzy logic technology to not only represent, interpret, and compute imprecise and subjective cues that are commonly encountered in the ADR problem but also to retrieve prior experiences by evaluating the extent of matching between the current situation and a past experience. We describe our preliminary multiagent system design and illustrate its potential benefits for assisting expert teams in early detection of previously unknown ADRs. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 827–845, 2007.     

Inference in distributed data clustering

In this paper we address confidentiality issues in distributed data clustering, particularly the inference problem. We present KDEC-S algorithm for distributed data clustering, which is shown to provide mining results while preserving confidentiality of original data. We also present a confidentiality framework with which we can state the confidentiality level of KDEC-S. The underlying idea of KDEC-S is to use an approximation of density estimation such that the original data cannot be reconstructed to a given extent.     

Tracking-error model-based predictive control for mobile robots in real time

In this paper, a model-predictive trajectory-tracking control applied to a mobile robot is presented. Linearized tracking-error dynamics is used to predict future system behavior and a control law is derived from a quadratic cost function penalizing the system tracking error and the control effort. Experimental results on a real mobile robot are presented and a comparison of the control obtained with that of a time-varying state-feedback controller is given. The proposed controller includes velocity and acceleration constraints to prevent the mobile robot from slipping and a Smith predictor is used to compensate for the vision-system dead-time. Some ideas for future work are also discussed.     

Geographical information systems applied in the field of renewable energy sources

This article presents a synthetic vision of geographical information systems (GIS) applications that are state of the art in the renewable energy field. The objective is to analyze the main qualities and problems of these applications, focusing on specific samples, and to carry out a methodological proposal in this genre.From this point of view, the study synthesizes the analyzed applications in three big groups: Decisions Support Systems (DSS) based on GIS; renewable energy and distributed generation of electricity; and decentralized generation for the rural electrification. In addition, a synthetic table and bibliographical references is provided for each group.Finally, several conclusions and a methodological outline are contributed for GIS application in the rural electrification with renewable energy.     

Mechanical properties of alternating high-low sp3 content thick non-hydrogenated diamond-like amorphous carbon films

Thick non-hydrogenated DLC films (∼ 1μm), consisting of alternating sub-layers of high/low sp³ content, were deposited onto n++ Si substrates using the filtered cathodic vacuum arc method. These films were systematically studied to determine how the changes in composition of the sub-layers would affect the mechanical properties such as intrinsic stress, hardness, friction coefficient, wear rate and surface roughness. Variations of both the ratio of hard to soft layers (from 1:3 to 3:1) and thickness of individual layers (from 12.5nm to 75nm) were studied in detail. The stress of the film was sufficiently lowered (7.8GPa–2.4GPa) by the multilayer approach. The results indicated that although hardness has some correlations with the internal composition of the film, the reduced Young's modulus is largely not affected. Wear and frictional characterizations also showed that the multilayer was a good candidate for many mechanical applications.