Robust model predictive controller with output feedback and target tracking

A model predictive controller (MPC) is proposed, which is robustly stable for some classes of model uncertainty and to unknown disturbances. It is considered as the case of open-loop stable systems, where only the inputs and controlled outputs are measured. It is assumed that the controller will work in a scenario where target tracking is also required. Here, it is extended to the nominal infinite horizon MPC with output feedback. The method considers an extended cost function that can be made globally convergent for any finite input horizon considered for the uncertain system. The method is based on the explicit inclusion of cost contracting constraints in the control problem. The controller considers the output feedback case through a non-minimal state-space model that is built using past output measurements and past input increments. The application of the robust output feedback MPC is illustrated through the simulation of a low-order multivariable system.

Fixed-point DSP implementation of nonlinear H(infinity) controller for large gap electromagnetic suspension system

Electromagnetic suspension systems are inherently nonlinear and often face hardware limitation when digitally controlled. The main contributions of this paper are: the design of a nonlinear H(infinity) controller. including dynamic weighting functions, applied to a large gap electromagnetic suspension system and the presentation of a procedure to implement this controller on a fixed-point DSP, through a methodology able to translate a floating-point algorithm into a fixed-point algorithm by using l(infinity) norm minimization due to conversion error. Experimental results are also presented, in which the performance of the nonlinear controller is evaluated specifically in the initial suspension phase. (C) 2009 Elsevier Ltd. All rights reserved.

ATM, a central controller of cellular responses to DNA damage

Mutations in the ATM gene lead to the genetic disorder ataxia-telangiectasia. ATM encodes a protein kinase that is mainly distributed in the nucleus of proliferating cells. Recent studies reveal that ATM regulates multiple cell cycle checkpoints by phosphorylating different targets at different stages of the cell cycle. ATM also functions in the regulation of DNA repair and apoptosis, suggesting that it is a central regulator of responses to DNA double-strand breaks.

Sensor-driven agenda for intelligent home care of the elderly

The exponential increase of home-bound persons who live alone and are in need of continuous monitoring requires new solutions to current problems. Most of these cases present illnesses such as motor or psychological disabilities that deprive of a normal living. Common events such as forgetfulness or falls are quite common and have to be prevented or dealt with. This paper introduces a platform to guide and assist these persons (mostly elderly people) by providing multisensory monitoring and intelligent assistance. The platform operates at three levels. The lower level, denominated ‘‘Data acquisition and processing’’performs the usual tasks of a monitoring system, collecting and processing data from the sensors for the purpose of detecting and tracking humans. The aim is to identify their activities in an intermediate level called ‘‘activity detection’’. The upper level, ‘‘Scheduling and decision-making’’, consists of a scheduler which provides warnings, schedules events in an intelligent manner and serves as an interface to the rest of the platform. The idea is to use mobile and static sensors performing constant monitoring of the user and his/her environment, providing a safe environment and an immediate response to severe problems. A case study on elderly fall detection in a nursery home bedroom demonstrates the usefulness of the proposal.

Network air gap controller

As ameaças à segurança da informação, (INFOSEC) atentam contra a perda da respectiva confidencialidade, integridade e disponibilidade, pelo que as organizações são impelidas a implementar políticas de segurança, quer ao nível físico quer ao nível lógico, utilizando mecanismos específicos de defesa. O projecto Network Air Gap Controller (NAGC) foi concebido no sentido de contribuir para as questões da segurança, designadamente daquelas que se relacionam directamente com a transferência de informação entre redes de classificação de segurança diferenciadas ou de sensibilidades distintas, sem requisitos de comunicação em tempo real, e que mereçam um maior empenho nas condições de robustez, de disponibilidade e de controlo. Os organismos que, em razão das atribuições e competências cometidas, necessitam de fazer fluir informação entre este tipo de redes, são por vezes obrigados a realizar a transferência de dados com recurso a um processo manual, efectuado pelo homem e não pela máquina, que envolve dispositivos amovivéis, como sejam o CD, DVD, PEN, discos externos ou switches manuais. Neste processo, vulgarmente designado por Network Air Gap (NAG), o responsável pela transferência de dados deverá assumir de forma infalível, como atribuições intrínsecas e inalienáveis da função exercida, as garantias do cumprimento de um vasto conjunto de normas regulamentares. As regras estabelecidas desdobram-se em ferramentas e procedimentos que se destinam, por exemplo, à guarda em arquivo de todas as transferências efectuadas; à utilização de ferramentas de segurança (ex: antivírus) antes da colocação da informação na rede de classificação mais elevada; ao não consentimento de transferência de determinados tipos de ficheiro (ex: executáveis) e à garantia de que, em consonância com a autonomia que normalmente é delegada no elemento responsável pela operação das comunicações, apenas se efectuam transferências de informação no sentido da rede de classificação inferior para a rede de classificação mais elevada. Face ao valor da informação e do impacto na imagem deste tipo de organizações, o operador de comunicações que não cumpra escrupulosamente o determinado é inexoravelmente afastado dessas funções, sendo que o processo de apuramento de responsabilidades nem sempre poderá determinar de forma inequívoca se as razões apontam para um acto deliberado ou para factores não intencionais, como a inépcia, o descuido ou a fadiga. Na realidade, as actividades periódicas e rotineiras, tornam o homem propenso à falha e poderão ser incontornavelmente asseguradas, sem qualquer tipo de constrangimentos ou diminuição de garantias, por soluções tecnológicas, desde que devidamente parametrizadas, adaptadas, testadas e amadurecidas, libertando os recursos humanos para tarefas de manutenção, gestão, controlo e inspecção. Acresce que, para este tipo de organizações, onde se multiplicam o número de redes de entrada de informação, com diferentes classificações e actores distintos, e com destinatários específicos, a utilização deste tipo de mecanismos assume uma importância capital. Devido a este factor multiplicativo, impõe-se que o NAGC represente uma opção válida em termos de oferta tecnológica, designadamente para uma gama de produtos de baixíssimo custo e que possa desenvolver-se por camadas de contributo complementar, em função das reais necessidades de cada cenário.

TINSEL – a web-based intelligent tutoring system on electrical installation design

This paper presents a project consisting on the development of an Intelligent Tutoring System, for training and support concerning the development of electrical installation projects to be used by electrical engineers, technicians and students. One of the major goals of this project is to devise a teaching model based on Intelligent Tutoring techniques, considering not only academic knowledge but also other types of more empirical knowledge, able to achieve successfully the training of electrical installation design.

Intelligent decision making in electricity markets: simulated annealing Q-Learning

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simulator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM is integrated with ALBidS, a system that provides several dynamic strategies for agents’ behavior. This paper presents a method that aims at enhancing ALBidS competence in endowing market players with adequate strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses a reinforcement learning algorithm to learn from experience how to choose the best from a set of possible actions. These actions are defined accordingly to the most probable points of bidding success. With the purpose of accelerating the convergence process, a simulated annealing based algorithm is included.

Short-term electricity prices forecasting in a competitive market by a hybrid intelligent approach

In this paper, a hybrid intelligent approach is proposed for short-term electricity prices forecasting in a competitive market. The proposed approach is based on the wavelet transform and a hybrid of neural networks and fuzzy logic. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Conclusions are duly drawn. (C) 2010 Elsevier Ltd. All rights reserved.

A multi-agent based approach for intelligent smart grid management

The spread and globalization of distributed generation (DG) in recent years has should highly influence the changes that occur in Electricity Markets (EMs). DG has brought a large number of new players to take action in the EMs, therefore increasing the complexity of these markets. Simulation based on multi-agent systems appears as a good way of analyzing players’ behavior and interactions, especially in a coalition perspective, and the effects these players have on the markets. MASCEM – Multi-Agent System for Competitive Electricity Markets was created to permit the study of the market operation with several different players and market mechanisms. MASGriP – Multi-Agent Smart Grid Platform is being developed to facilitate the simulation of micro grid (MG) and smart grid (SG) concepts with multiple different scenarios. This paper presents an intelligent management method for MG and SG. The simulation of different methods of control provides an advantage in comparing different possible approaches to respond to market events. Players utilize electric vehicles’ batteries and participate in Demand Response (DR) contracts, taking advantage on the best opportunities brought by the use of all resources, to improve their actions in response to MG and/or SG requests.

Intelligent management of end consumers loads including electric vehicles through a SCADA system

The large penetration of intermittent resources, such as solar and wind generation, involves the use of storage systems in order to improve power system operation. Electric Vehicles (EVs) with gridable capability (V2G) can operate as a means for storing energy. This paper proposes an algorithm to be included in a SCADA (Supervisory Control and Data Acquisition) system, which performs an intelligent management of three types of consumers: domestic, commercial and industrial, that includes the joint management of loads and the charge/discharge of EVs batteries. The proposed methodology has been implemented in a SCADA system developed by the authors of this paper – the SCADA House Intelligent Management (SHIM). Any event in the system, such as a Demand Response (DR) event, triggers the use of an optimization algorithm that performs the optimal energy resources scheduling (including loads and EVs), taking into account the priorities of each load defined by the installation users. A case study considering a specific consumer with several loads and EVs is presented in this paper.

Intelligent Bio-Inspired system for manufacturing scheduling under uncertainties

A novel approach to scheduling resolution by combining Autonomic Computing (AC), Multi-Agent Systems (MAS), Case-based Reasoning (CBR), and Bio-Inspired Optimization Techniques (BIT) will be described. AC has emerged as a paradigm aiming at incorporating applications with a management structure similar to the central nervous system. The main intentions are to improve resource utilization and service quality. In this paper we envisage the use of MAS paradigm for supporting dynamic and distributed scheduling in Manufacturing Systems with AC properties, in order to reduce the complexity of managing manufacturing systems and human interference. The proposed CBR based Intelligent Scheduling System was evaluated under different dynamic manufacturing scenarios.

A hybrid intelligent system for distributed dynamic scheduling

This chapter addresses the resolution of dynamic scheduling by means of meta-heuristic and multi-agent systems. Scheduling is an important aspect of automation in manufacturing systems. Several contributions have been proposed, but the problem is far from being solved satisfactorily, especially if scheduling concerns real world applications. The proposed multi-agent scheduling system assumes the existence of several resource agents (which are decision-making entities based on meta-heuristics) distributed inside the manufacturing system that interact with other agents in order to obtain optimal or near-optimal global performances.

Energy efficiency analysis considering the use of an intelligent systems management in a smart home

In this abstract is presented an energy management system included in a SCADA system existent in a intelligent home. The system control the home energy resources according to the players definitions (electricity consumption and comfort levels), the electricity prices variation in real time mode and the DR events proposed by the aggregators.