872 resultados para model reference adaptive control systems


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In this paper, a linear lightweight electric cylinder constructed using shape memory alloy (SMA) is proposed. Spring SMA is used as the actuator to control the position and force of the cylinder rod. The model predictive control algorithm is investigated to compensate SMA hysteresis phenomenon and control the cylinder. In the predictive algorithm, the future output of the cylinder is computed based on the cylinder model, and the control signal is computed to minimize the error and power criterion. The cylinder model parameters are estimated by an online identification algorithm. Experimental results show that the SMA cylinder is able to precisely control position and force by using the predictive control strategy though the hysteresis effect existing in the actuator. The performance of the proposed controller is compared with that of a conventional PID controller

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Fuel economy has become an important consideration in forklift truck design, particularly in Europe. A simulation of the fuel consumption and performance of a forklift truck has been developed, validated and subsequently used to determine the energy consumed by individual powertrain components during drive cycles.
The truck used in this study has a rated lifting capacity of 2500kg, and is powered by a 2.6 litre naturally aspirated diesel engine with a fuel pump containing a mechanical variable-speed governor. The drivetrain consisted of a torque convertor, hydraulic clutch and single speed transmission.
AVL Cruise was used to simulate the vehicle powertrain, with coupled Mathworks Simulink models used to simulate the hydraulic and control systems and governor. The vehicle has been simulated on several performance and fuel consumption drive cycles with the main focus being the VDI 2198 fuel consumption drive cycle.
To validate the model, a truck was instrumented and measurements taken to compare the performance and instantaneous fuel consumption to simulated values. The fuel injector pump was modified and calibrated to enable instantaneous fuel flow to be measured.
The model has been validated to within acceptable limits and has been used to investigate the effect four different torque converters have on the fuel consumption and performance of the forklift truck. The study demonstrates how the model can be used to compare the fuel consumption and performance trade-offs when selecting drivetrain components.

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This paper presents a new methodology for solving the multi-vehicle formation control problem. It employs a unique extension-decomposition-aggregation scheme to transform the overall complex formation control problem into a group of subproblems, which work via boundary interactions or disturbances. Thus, it is proved that the overall formation system is exponentially stable in the sense of Lyapunov, if all the individual augmented subsystems (IASs) are stable. Linear matrix inequality-based H8 control methodology is employed to design the decentralized formation controllers to reject the impact of the formation changes being treated as boundary disturbances and guarantee the stability of all the IASs, consequently maintaining the stability of the overall formation system. Simulation studies are performed to verify the stability, performance, and effectiveness of the proposed strategy.

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The adoption of each new level of automotive emissions legislation often requires the introduction of additional emissions reduction techniques or the development of existing emissions control systems. This, in turn, usually requires the implementation of new sensors and hardware which must subsequently be monitored by the on-board fault detection systems. The reliable detection and diagnosis of faults in these systems or sensors, which result in the tailpipe emissions rising above the progressively lower failure thresholds, provides enormous challenges for OBD engineers. This paper gives a review of the field of fault detection and diagnostics as used in the automotive industry. Previous work is discussed and particular emphasis is placed on the various strategies and techniques employed. Methodologies such as state estimation, parity equations and parameter estimation are explained with their application within a physical model diagnostic structure. The utilization of symptoms and residuals in the diagnostic process is also discussed. These traditional physical model based diagnostics are investigated in terms of their limitations. The requirements from the OBD legislation are also addressed. Additionally, novel diagnostic techniques, such as principal component analysis (PCA) are also presented as a potential method of achieving the monitoring requirements of current and future OBD legislation.

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This paper studies the system modelling and control aspects of switched reluctance generator (SRG) based variable speed wind turbines. A control system is implemented to provide proper operation of the SRG as well as power tracking capabilities for varying wind speeds. The control system for the grid side inverter that will allow the SRG to properly generate power to the system is also presented. Studies are presented of both the SRG and inverter control systems capabilities during a balanced three-phase fault. The paper will demonstrate that the SRG based wind turbine presents a feasible variable wind speed solution with good fault response capabilities.

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Physical Access Control Systems are commonly used to secure doors in buildings such as airports, hospitals, government buildings and offices. These systems are designed primarily to provide an authentication mechanism, but they also log each door access as a transaction in a database. Unsupervised learning techniques can be used to detect inconsistencies or anomalies in the mobility data, such as a cloned or forged Access Badge, or unusual behaviour by staff members. In this paper, we present an overview of our method of inferring directed graphs to represent a physical building network and the flows of mobility within it. We demonstrate how the graphs can be used for Visual Data Exploration, and outline how to apply algorithms based on Information Theory to the graph data in order to detect inconsistent or abnormal behaviour.

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Modern networks are large, highly complex and dynamic. Add to that the mobility of the agents comprising many of these networks. It is difficult or even impossible for such systems to be managed centrally in an efficient manner. It is imperative for such systems to attain a degree of self-management. Self-healing i.e. the capability of a system in a good state to recover to another good state in face of an attack, is desirable for such systems. In this paper, we discuss the self-healing model for dynamic reconfigurable systems. In this model, an omniscient adversary inserts or deletes nodes from a network and the algorithm responds by adding a limited number of edges in order to maintain invariants of the network. We look at some of the results in this model and argue for their applicability and further extensions of the results and the model. We also look at some of the techniques we have used in our earlier work, in particular, we look at the idea of maintaining virtual graphs mapped over the existing network and assert that this may be a useful technique to use in many problem domains.

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Melt viscosity is one of the main factors affecting product quality in extrusion processes particularly with regard to recycled polymers. However, due to wide variability in the physical properties of recycled feedstock, it is difficult to maintain the melt viscosity during extrusion of polymer blends and obtain good quality product without generating scrap. This research investigates the application of ultrasound and temperature control in an automatic extruder controller, which has ability to maintain constant melt viscosity from variable recycled polymer feedstock during extrusion processing. An ultrasonic modulation system has been developed and fitted to the extruder prior to the die to convey ultrasonic energy from a high power ultrasonic generator to the polymer melt. Two separate control loops have been developed to run simultaneously in one controller: the first loop controls the ultrasonic energy or temperature to maintain constant die pressure, the second loop is used to control extruder screw speed to maintain constant throughput at the extruder die. Time response and energy consumption of the control methods in real-time experiments are also investigated and reported this paper.

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The BDI architecture, where agents are modelled based on their beliefs, desires and intentions, provides a practical approach to develop large scale systems. However, it is not well suited to model complex Supervisory Control And Data Acquisition (SCADA) systems pervaded by uncertainty. In this paper we address this issue by extending the operational semantics of Can(Plan) into Can(Plan)+. We start by modelling the beliefs of an agent as a set of epistemic states where each state, possibly using a different representation, models part of the agent's beliefs. These epistemic states are stratified to make them commensurable and to reason about the uncertain beliefs of the agent. The syntax and semantics of a BDI agent are extended accordingly and we identify fragments with computationally efficient semantics. Finally, we examine how primitive actions are affected by uncertainty and we define an appropriate form of lookahead planning.

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Conventional understandings of what the Westminster model implies anticipate reliance on a top-down, hierarchical approach to budgetary accountability, reinforced by a post–New Public Management emphasis on recentralizing administrative capacity. This article, based on a comparative analysis of the experiences of Britain and Ireland, argues that the Westminster model of bureaucratic control and oversight itself has been evolving, hastened in large part due to the global financial crisis. Governments have gained stronger controls over the structures and practices of agencies, but agencies are also key players in securing better governance outcomes. The implication is that the crisis has not seen a return to the archetypal command-and-control model, nor a wholly new implementation of negotiated European-type practices, but rather a new accountability balance between elements of the Westminster system itself that have not previously been well understood.

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In Italy, standards for the management of free-roaming dogs (FRDs) are defined by regional norms, generating a high variability of approaches around the country. Despite efforts carried out by the competent authorities, FRDs are still a reality impacting upon animal health and welfare and public costs. A similar scenario can be found in many other Mediterranean and Balkan counties. Here we present 14 years of data (2000–2013) retrieved from the admission dog registry of a public shelter (PS) responsible for the collection of stray dogs from one Italian province. The aim of this retrospective study was to describe the local FRD population, identifying its source and to evaluate the effectiveness of the actions implemented by the local authorities. In the investigated period, 7,475 dogs were admitted to the PS. Despite the intense sterilisation plan (mean 381.7 sterilisations per year), the overall number of dogs entering PS did not decrease consistently across the years. Results highlighted a lack of responsibility of owners by failing to sterilise and identify their dogs and allowing intact animals to roam free, therefore producing uncontrolled and unwanted litters. The current dog population management strategy, based on both sheltering and capture-neuter-release programmes, is insufficient to tackle the straying phenomenon. Educational and sterilisation programmes should be an integral part of a successfully implemented FRD control plan. Our results provide further insight on free-roaming dog population dynamics and control systems, and may have important implications for many other local contexts across Europe trying to overcome the straying phenomenon.

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In this brief, a hybrid filter algorithm is developed to deal with the state estimation (SE) problem for power systems by taking into account the impact from the phasor measurement units (PMUs). Our aim is to include PMU measurements when designing the dynamic state estimators for power systems with traditional measurements. Also, as data dropouts inevitably occur in the transmission channels of traditional measurements from the meters to the control center, the missing measurement phenomenon is also tackled in the state estimator design. In the framework of extended Kalman filter (EKF) algorithm, the PMU measurements are treated as inequality constraints on the states with the aid of the statistical criterion, and then the addressed SE problem becomes a constrained optimization one based on the probability-maximization method. The resulting constrained optimization problem is then solved using the particle swarm optimization algorithm together with the penalty function approach. The proposed algorithm is applied to estimate the states of the power systems with both traditional and PMU measurements in the presence of probabilistic data missing phenomenon. Extensive simulations are carried out on the IEEE 14-bus test system and it is shown that the proposed algorithm gives much improved estimation performances over the traditional EKF method.

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Esta tese tem como principal objetivo analisar as características, a importância e o papel da inovação territorial em turismo e o seu impacto no desenvolvimento dos destinos. Consiste num estudo multidisciplinar suportado numa exaustiva revisão da literatura sobre temas como desenvolvimento, inovação e modelos de inovação territorial. Com base nas principais conclusões de natureza conceptual, considerou-se o modelo dos sistemas regionais de inovação como o mais adequado para aplicação ao sistema turístico, e a constituição de redes como estruturas fundamentais para a sua operacionalização. A partir desta abordagem teórica, foi desenvolvido um quadro conceptual para a análise da inovação sistémica no sector do turismo. Esta abordagem permitiu a definição de um conjunto de hipóteses, as quais foram testadas através dos resultados da parte empírica da tese. Foram desenvolvidos dois estudos empíricos distintos, mas complementares nas regiões do Douro e de Aveiro. O primeiro teve como objetivo inquirir empresas turísticas, enquanto o segundo foi dirigido a instituições regionais com intervenção no sector do turismo ou na inovação. Os resultados obtidos conduziram a importantes conclusões sobre o desempenho das empresas e regiões em termos de inovação, os padrões de networking desenvolvidos no âmbito de processos de inovação, a importância do conhecimento existente nas regiões e os fatores específicos das mesmas para a inovação em turismo, a perceção das empresas turísticas sobre o ambiente de inovação e o seu contributo para a evolução e para o sucesso dos destinos turísticos. A tese recorre a uma abordagem quantitativa que inclui estatística descritiva e indutiva e ao método da análise de redes (sociometria). A combinação de métodos levou a importantes conclusões sobre a inovação em turismo, com uma focalização especial no que a relaciona com os sistemas regionais de inovação. As conclusões permitem avançar com um conjunto de implicações e sugestões para futuros projetos de investigação sobre o tema, bem como para a gestão dos destinos turísticos, uma vez que contribui para um maior e mais aprofundado conhecimento do fenómeno da inovação em turismo desenvolvida a nível regional. Os resultados demonstram que diferentes regiões apresentam sistemas regionais de inovação distintos. Assim, não existe um modelo único que possa ser aplicado indistintamente em todas as regiões. Contudo, as conclusões apontam para a existência de padrões e práticas que aperfeiçoam o seu funcionamento, aumentando o desempenho ao nível da inovação, bem como a competitividade global do destino.