选择性控制技术在TRT系统中的应用

为了解决高炉顶压生产短期内处于不正常的情况,即不使TRT系统停车而又起到对生产进行自动保护的目的,山东莱钢TRT系统对旁通阀采取了选择性控制技术。该技术的应用稳定了高炉炉顶压力,既保证了安全生产,同时增加了经济效益,在国内TRT行业极具推广意义。     

DESIGN AND IMPLEMENTATION OF STATE OBSERVERS IN REACTIVE DISTILLATION

This study demonstrates that state observers can be developed and applied to infer the composition profiles of reactive distillation columns from noise-contaminated temperature measurements. The design and implementation of a Kalman filter (KF) and a Luenberger observer (LO) are carried out, and their performances are quantitatively assessed. The reliability, accuracy, and robustness of the two designs method are examined and compared quantitatively. The design and implementation of a Luenberger observer are simpler and easier to carry out than those of a Kalman filter. On the other hand, a Kalman filter is found to be more robust to a noisy measurements, erroneous initial estimates, and model uncertainties. A Luenberger observer could be used for composition estimation of reactive distillation when an ideal model of the system can reasonably approximate the real system; otherwise, a Kalman filter is recommended to be applied in more practical situations.     

A highly efficient novel azimuthal heliotrope

A new type of a single-axis azimuthal tracker is presented. The novel feature of this tracker is the ability to move the collector’s plane in two directions through a special support structure. This structure consists of a sliding mechanism on the central axis and a curved window on the cylindrical surface coaxial to the central axis. Consequently, the proposed novel heliotrope behaves similarly to a two-axis tracker. Two different windows designed on the cylindrical surface may be used to provide very high efficiencies throughout a year. Several performance measurements have been conducted on this novel tracker, a polar tracker and the reference two-axis tracker. Pyranometers, appropriately calibrated, were installed on all three systems to record the global incoming irradiance on the collector’s plane. It is shown that the new tracker system can be very efficient since its plane intercepts, at least, 98% of the insolation with respect to a two-axis tracker. The proposed system can be utilized in solar-related applications (photovoltaic or thermal).     

A flexible architecture for distributed knowledge based systems with nomadic access through handheld devices

Nowadays any Knowledge Based System (KBS) realization needs of intercommunication among distributed components and to use non-connected and distributed data sources, which poses several challenges to the classical Artificial Intelligence field of KBS.

The multiagent paradigm and the use of ontologies are considered to be suitable tools to face the problems of designing and developing today KBS. On the other hand, using such networked KBS through handheld devices makes more efficient exploitation and interaction with the system.

This paper presents an open and flexible architecture for a distributed KBS and an application of it to construct a system for Psychological Disorders consulting, the so called PDA² (Psychological Disorder Assistant through PDA). We analyze the main features of the architecture as well as the agent tools we may use to construct it. Additionally, we present a support ontology for Psychological Disorders.     

Stabilizing decentralized model predictive control of nonlinear systems

This note presents a stabilizing decentralized model predictive control (MPC) algorithm for nonlinear discrete time systems. No information is assumed to be exchanged between local control laws. The stability proof relies on the inclusion of a contractive constraint in the formulation of the MPC problem.     

An adaptive tracking problem for a family of retarded time-delay plants

Most of the existing switching control techniques are developed specifically for finite-dimensional linear time-invariant (LTI) systems. In many practical applications, however, it is essential to take time delay into consideration in the modelling as the control system can be highly sensitive to delay. In this paper, a multi-model switching control algorithm is proposed for retarded time-delay systems. It is assumed that the plant is represented by a family of known multi-input multi-output, observable, LTI models with multiple delays in the states, and that corresponding to each model in the known family, there exists a high-performance finite-dimensional LTI controller. In addition, it is supposed that a bound on the magnitude of the external inputs and disturbances is available. It is then shown that the proposed switching controller can stabilize the uncertain system, and that under some mild conditions, output tracking can be achieved in the given problem setting. Copyright © 2007 John Wiley & Sons, Ltd.     

DCOP FOR SMART HOMES: A CASE STUDY

The aim of this article is to bring forth the issue of integrating the services provided by intelligent artifacts in Ambient Intelligence applications. Specifically, we propose a Distributed Constraint Optimization procedure for achieving a functional integration of intelligent artifacts in a smart home. To this end, we employ Adopt-N , a state-of-the-art algorithm for solving Distributed Constraint Optimization Problems (DCOP). This article attempts to state the smart home coordination problem in general terms, and provides the details of a DCOP-based approach by describing a case study taken from the RoboCare project. More specifically, we show how (1) DCOP is a convenient metaphor for casting smart home coordination problems, and (2) the specific features which distinguish Adopt-N from other algorithms for DCOP represent a strong asset in the smart home domain.     

A novel distributed approach to robust fault detection and identification

In this paper, we propose a novel distributed robust fault detection and identification (RFDI) scheme for a class of nonlinear systems. Firstly, a detection and identification estimator—robust fault tracking approximator (RFTA) is designed for online health monitoring. A novel feature of the RFTA is that it can simultaneously detect and accurately identify the shape and magnitude of the fault and disturbance. Moreover, it takes less online training time compared with the traditional neural network based fault diagnosis schemes. For some distributed systems, a network of distributed estimators is constructed where the RFTA is embedded into each estimator. Then we use consensus filter to filter the outputs of each estimator. One of the most important merits of the consensus filter is that its outputs can dramatically improve the accuracy of fault detection and identification. Next, the stability of the distributed RFDI scheme is rigorously investigated. Finally, two numerical examples are given to illustrate the feasibility and effectiveness of the proposed approach.