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The Distributed Control Program Generator of Microprocessor-based EnvironmentHuang, Szu-kai 30 July 2012 (has links)
In the field of the industrial automatic control, both MCU (Micro Control Unit) and PLC (Programmable Logic Controller) are widely being used in DCS (Distributed Control System). Since MCU can provide complex process scheduling, accurate timing control and PLC has the advantages of easy programming and maintaining. However, the control programs of the MCU are hard to design and maintain. Identically, the poor signal processing ability, high cost and the restrictive functions are the major defects of PLC.
In order to solve the drawbacks described above in MCU and PLC, we provide a PLC-like interface for users to access the devices and set the registers of MCU. Likewise, designers can develop the control program via Event-table-driven modules. On the other hand, our main goal of DCS is to quickly construct the distributed N level network topology based on Modbus protocol, which is efficient and reliable. Therefore, we bring up a data collection method and Slave-to-Slave strategy so as to distribute the master loading, reduce the package transmission times and improve the real-time latency.
In conclusion, our research results not only congregate the benefits of MCU and PLC but provide an environment to quickly construct and conveniently monitor DCS, which meets the time-to-market demands.
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Examining the relative costs and benefits of shifting the locus of control in a novel air traffic management environment via multi-agent dynamic analysis and simulationBigelow, Matthew Steven 28 June 2011 (has links)
The current air traffic management system has primarily evolved via incremental changes around historic control, navigation, and surveillance technologies. As a result, the system as a whole is not capable of handling air traffic capacities well beyond current levels, despite recent developments, such as ADS-B, that could potentially enable new concepts of operation. Methods of analyzing air traffic for safety and performance have also evolved around current-day operating constructs. Thus, attempts to examine future systems tend to use different analysis methods developed for each. Most notably, questions of 'locus of control' - whether the control should be centralized or de-centralized and distributed - have no common framework by which to judge relative costs and benefits. For instance, a completely centralized control paradigm is commonly asserted to provide an airspace-wide optimal traffic management solution due to a more complete picture of the state of the airspace, whereas a completely decentralized control paradigm is commonly asserted to provide a more user-specific optimal traffic management solution, to distribute the traffic management workload, and potentially be more robust. Given the disparate nature of these assertions and the different types of evaluations commonly used with each, some shared framework must be established to allow comparisons between very different control paradigms.
The objective of this thesis was to construct a formal framework to examine the relative costs and benefits of shifting the locus of control in a novel air traffic management environment. This framework provides useful definitions and quantitative measures of flexibility and robustness with respect to various control paradigms ranging between, and including, completely centralized and completely decentralized concepts of operation. Multi-agent dynamic analysis and simulation was used to analyze the range of dynamics found in the different control paradigms. In addition, futuristic air traffic management concepts were developed in sufficient detail to demonstrate the framework. In other words, the objectives were met because the framework was demonstrated to have the ability to identify (or dispel) hypotheses about the relative costs and benefits of locus of control.
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Coordinated-distributed optimal control of large-scale linear dynamic systemsMarcos, Natalia I. Unknown Date
No description available.
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DEVELOPMENT AND EVALUATION OF A CONTROLLER AREA NETWORK BASED AUTONOMOUS VEHICLEDarr, Matthew John 01 January 2004 (has links)
Through the work of researchers and the development of commercially availableproducts, automated guidance has become a viable option for agricultural producers.Some of the limitations of commercially available technologies are that they onlyautomate one function of the agricultural vehicle and that the systems are proprietary toa single machine model.The objective of this project was to evaluate a controller area network (CAN bus)as the basis of an automated guidance system. The prototype system utilized severalmicrocontroller-driven nodes to act as control points along a system wide CAN bus.Messages were transferred to the steering, transmission, and hitch control nodes from atask computer. The task computer utilized global positioning system data to determinethe appropriate control commands.Infield testing demonstrated that each of the control nodes could be controlledsimultaneously over the CAN bus. Results showed that the task computer adequatelyapplied a feedback control model to the system and achieved guidance accuracy levelswell within the range sought. Testing also demonstrated the system's ability tocomplete normal field operations such as headland turning and implement control.
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Distributed H∞ Control of Segmented Telescope MirrorsUlutas, Baris 12 August 2014 (has links)
Segmented mirrors are to be used in the next generation of the ground-based optical telescopes to increase the size of the primary mirrors. A larger primary mirror enables the collection of more light, which results in higher image resolutions. The main reason behind the choice of segmented mirrors over monolithic mirrors is to reduce manufacturing, transportation, and maintenance costs of the overall system. However, segmented mirrors bring new challenges to the telescope design and control problem. The large number of inputs and outputs make the computations for centralized control schemes intractable. Centralized controllers also result in systems that are vulnerable to a complete system failure due to a malfunction of the controller.
Distributed control is a viable alternative that requires the use of a network of simple individual segment controllers that can address two levels of coupling among segments and achieve the same performance objectives. Since segments share a common support structure, there exists a coupling among segments at the dynamics level. Any control action in one segment may excite the natural modes of the support structure and disturb other segments through this common support. In addition, the objective of maintaining a smooth mirror surface requires minimization of the relative displacements among neighbouring segment edges. This creates another level of coupling generally referred to as the objective coupling.
This dissertation investigates the distributed H∞ control of the segmented next generation telescope primary mirrors in the presence of wind disturbances. Three distributed H∞ control techniques are proposed and tested on three segmented primary mirror models: the dynamically uncoupled model, the dynamically coupled model and the finite element model of Thirty Meter Telescope (TMT) project. It is shown that the distributed H∞ controllers are able to satisfy the stringent imaging performance requirements. / Graduate / 0548
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Λογισμικό για κατανεμημένο έλεγχοΡήγα, Φωτεινή 14 September 2010 (has links)
Η παρούσα εργασία πραγματεύεται ζητήματα που αφορούν σε συστήματα αυτομάτου ελέγχου με ιδιαίτερη έμφαση στα συστήματα κατανεμημένου ελέγχου. Σε αυτό το πλαίσιο, πραγματοποιείται στην εργασία καταρχάς μια σύντομη ανασκόπηση σε σχέση με τα συστήματα ελέγχου και με το πώς αυτά τα συστήματα εισήχθησαν για χρήση στη βιομηχανία. Στη συνέχεια, παρουσιάζονται τα κατανεμημένα συστήματα ελέγχου, τα βασικά χαρακτηριστικά τους αλλά και οι βασικές μεθοδολογίες σχεδίασης ενός τέτοιου συστήματος.
Γίνεται επίσης σημαντική αναφορά στα πολυπρακτορικά συστήματα (Multi Agent Systems – MAS) τα οποία αποτελούν το μέλλον της ανάπτυξης των κατανεμημένων συστημάτων. Τέλος, συνοψίζονται τα βασικά προβλήματα, οι τάσεις αλλά και η κατάσταση στην αγορά αναφορικά με αυτά τα συστήματα. / -
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Optimisation stochastique et adaptative pour surveillance coopérative par une équipe de micro-véhicules aériens / Adaptive stochastic optimization for cooperative coverage with a swarm of Micro Air VehiclesRenzaglia, Alessandro 27 April 2012 (has links)
L'utilisation d'équipes de robots a pris de l'ampleur ces dernières années. Cela est dû aux avantages que peut offrir une équipe de robot par rapport à un robot seul pour la réalisation d'une même tâche. Cela s'explique aussi par le fait que ce type de plates-formes deviennent de plus en plus abordables et fiables. Ainsi, l'utilisation d'une équipe de véhicules aériens devient une alternative viable. Cette thèse se concentre sur le problème du déploiement d'une équipe de Micro-Véhicules Aériens (MAV) pour effectuer des missions de surveillance sur un terrain inconnu de morphologie arbitraire. Puisque la morphologie du terrain est inconnue et peut être complexe et non-convexe, les algorithmes standards ne sont pas applicables au problème particulier traité dans cette thèse. Pour y remédier, une nouvelle approche basée sur un algorithme d'optimisation cognitive et adaptatif (CAO) est proposée et évaluée. Une propriété fondamentale de cette approche est qu'elle partage les mêmes caractéristiques de convergence que les algorithmes de descente de gradient avec contraintes qui exigent une connaissance parfaite de la morphologie du terrain pour optimiser la couverture. Il est également proposé une formulation différente du problème afin d'obtenir une solution distribuée, ce qui nous permet de surmonter les inconvénients d'une approche centralisée et d'envisager également des capacités de communication limitées. De rigoureux arguments mathématiques et des simulations étendues établissent que l'approche proposée fournit une méthodologie évolutive et efficace qui intègre toutes les contraintes physiques particulières et est capable de guider les robots vers un arrangement qui optimise localement la surveillance. Finalement, la méthode proposée est mise en œuvre sur une équipe de MAV réels pour réaliser la surveillance d'un environnement extérieur complexe. / The use of multi-robot teams has gained a lot of attention in recent years. This is due to the extended capabilities that the teams offer compared to the use of a single robot for the same task. Moreover, as these platforms become more and more affordable and robust, the use of teams of aerial vehicles is becoming a viable alternative. This thesis focuses on the problem of deploying a swarm of Micro Aerial Vehicles (MAV) to perform surveillance coverage missions over an unknown terrain of arbitrary morphology. Since the terrain's morphology is unknown and it can be quite complex and non-convex, standard algorithms are not applicable to the particular problem treated in this thesis. To overcome this, a new approach based on the Cognitive-based Adaptive Optimization (CAO) algorithm is proposed and evaluated. A fundamental property of this approach is that it shares the same convergence characteristics as those of constrained gradient-descent algorithms, which require perfect knowledge of the terrain's morphology to optimize coverage. In addition, it is also proposed a different formulation of the problem in order to obtain a distributed solution, which allows us to overcome the drawbacks of a centralized approach and to consider also limited communication capabilities. Rigorous mathematical arguments and extensive simulations establish that the proposed approach provides a scalable and efficient methodology that incorporates any particular physical constraints and limitations able to navigate the robots to an arrangement that (locally) optimizes the surveillance coverage. The proposed method is finally implemented in a real swarm of MAVs to carry out surveillance coverage in an outdoor complex area.
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Motion control of autonomous underwater vehicles using advanced model predictive control strategyShen, Chao 26 March 2018 (has links)
The increasing reliance on oceans, rivers and waterways in a spectrum of human activities have demonstrated the large demand for advanced marine technologies that facilitate multifarious in-water services and tasks. The autonomous underwater vehicle (AUV) is a representative marine technology which has been contributing continuously to many ocean-related fields. An elaborate control system is essential to AUVs. However, AUVs present difficult control system design problems due to their nonlinear dynamics, the unpredictable environment and the poor knowledge about the hydrodynamic coupling of the vehicle degrees of freedom. When designing the motion controller, the practical constraints on the AUV system such as limited perceiving, computing and actuating capabilities should also be respected.
The model predictive control (MPC) is an advanced control technology that leverages optimization to calculate the control command. Thanks to the optimization nature, MPC can conveniently handle the complex nonlinearity in system dynamics as well as the state and control constraints. MPC takes the receding horizon control paradigm which gains satisfactory robustness against model uncertainties and external disturbances. Therefore, MPC is an ideal candidate for solving the AUV motion control problems. On the other hand, since the optimization is solved by iterative numerical algorithms, the obtained control signal is an implicit function of the system state, which complicates the characterization of the closed-loop properties. Moreover, the nonlinear system dynamics makes the online optimization nonlinear programming (NLP) problems. The high computational complexity may cause an issue on the real-time control for embedded platforms with limited computing resources. In order to push the advanced MPC technology towards real-world AUV applications, this PhD dissertation is concerned with fundamental AUV motion control problems and attempts to address the aforementioned challenges and provide novel solutions.
This dissertation proceeds with Chapter 1 by providing state-of-the-art introductions to related research areas. The mathematical model used for the AUV motion control is elaborated in Chapter 2. In Chapter 3, we consider the AUV navigation and control problem in constrained workspace. A unified receding horizon optimization framework consisting of the dynamic path planning and the nonlinear model predictive control (NMPC) tracking control is developed. Although the NMPC tracking controller well accommodates the practical constraints on the AUV system, it presents a brand new design philosophy compared with the existing control systems that are implemented on real AUVs. Since the existing AUV control systems are reliable controllers, AUV practitioners tend not to fully replace them but to improve the control performance by adding features. By considering this, in Chapter 4, we develop the Lyapunov-based model predictive control (LMPC) scheme which builds on the existing AUV control system and invoke online optimization to improve the control performance. Chapter 5 focuses on the path following (PF) problem. Unlike the trajectory tracking control which equally emphasizes the spatial and temporal control objectives, the PF control often prioritizes the path convergence over the speed assignment. To incorporate this objective prioritization into the controller design, a novel multi-objective model predictive control (MOMPC) scheme is developed. While the MPC technique provides several salient features (e.g., optimality, constraints handling, objective prioritization, robustness, etc.), those features come at a price: a computational bottleneck is formed by the heavy burden of solving online optimizations in real time. To explicitly address this issue, in Chapter 6, the computational complexity of the MPC algorithms is particularly emphasized. Two novel strategies which potentially alleviate the computational burden of the MPC-based AUV tracking control are proposed. In Chapter 7, some conclusive remarks are provided and a few avenues for future research are identified. / Graduate
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Sistema para sensoriamento e controle para aplicações em biomecatrônica. / Sensing and control system for applications in biomechatronics.Luís Filipe Fragoso de Barros e Silva Rossi 26 January 2012 (has links)
Diversos trabalhos relacionados ao desenvolvimento de dispositivos robóticos biomecatrônicos estão sendo realizados em vários laboratórios no mundo. Apesar desta crescente tendência, devido a uma falta de padronização nas tecnologias utilizadas, em especial no sistema de sensoriamento e controle, há uma grande divergência nos sistemas resultantes. De forma a se conseguir atender os requisitos dos projetos, muito tempo é despendido no desenvolvimento de sistemas de sensoriamento e controle dedicados. Dentro deste cenário, neste trabalho foi projetado e implementado um sistema de sensoriamento e controle modular específico para sistemas robóticos. Este foi desenvolvido de forma a poder ser utilizado em diversos projetos reduzindo o esforço para a sua implementação. O referido sistema foi dividido em três módulos: Processador Central, Nós e Rede de Comunicação. Foi dada uma especial atenção no aspecto relacionado à comunicação por ser um fator-chave para se conseguir manter compatibilidade entre diferentes sistemas. Uma rede de comunicação denominada R-Bone foi desenvolvida pelo fato de que os sistemas existentes não atendem aos requisitos propostos. Uma descrição conceitual do sistema projetado é apresentada e a sua implementação detalhada. Todos os aspectos técnicos relevantes foram descritos de forma a facilitar a sua replicação por outros grupos. Um driver para sistema operacional Linux foi desenvolvido em conjunto com uma camada de abstração para simplificar o seu uso. Os testes realizados demonstraram que o sistema desenvolvido atende os requisitos propostos, mantendo uma condição de estabilidade adequada em seu tempo de resposta, baixa latência e pouca defasagem entre os sinais coletados pelos sensores. De forma a contribuir para uma possível padronização dos sistemas utilizados na área, todos os arquivos e informações relevantes para a replicação do sistema proposto foram disponibilizados sob a licença GNU LGPL em um servidor SVN. / Several works related to the development of biomechatronic robotic systems are being taken in several laboratories around the world. Despite this increasing trend, due to a lack of standardization in the used technologies, in special related to the control and sensing system, there is a wide divergence in the resulting system. In order to meet the project requirements, a lot of time is spent in the development of a custom control and sensing system. In this scenario, a modular sensing and control system specifically designed to be used in robotic systems, was designed and implemented. The last was developed in order to be used in several projects, thus reducing the effort spent on its implementation. This system was divided into three modules: Central Processor, Nodes and Communication Network. A special attention was given to the aspects related to the communication as it is the key-factor to keep compatibility among different systems. A communication network named R-Bone was developed, and its implementation was detailed. All the relevant technical aspects were described in order to facilitate its replication by other groups. A driver for the Linux operating system was developed in conjunction with an abstraction layer to simplify its use. The tests demonstrated that the system meets the proposed requirements, keeping a proper stability condition in the response time, low latency and little skew between the signals collected by the sensors. In order to contribute to a possible standardization of the systems used in the biomechatronics field, all the files with relevant information to make possible the replication of the proposed system were made available under the GNU LGPL license in a SVN server.
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Hybrid Power System Intelligent Operation and Protection Involving Distributed Architectures and Pulsed LoadsMohamed, Ahmed A 21 March 2013 (has links)
Efficient and reliable techniques for power delivery and utilization are needed to account for the increased penetration of renewable energy sources in electric power systems. Such methods are also required for current and future demands of plug-in electric vehicles and high-power electronic loads. Distributed control and optimal power network architectures will lead to viable solutions to the energy management issue with high level of reliability and security. This dissertation is aimed at developing and verifying new techniques for distributed control by deploying DC microgrids, involving distributed renewable generation and energy storage, through the operating AC power system.
To achieve the findings of this dissertation, an energy system architecture was developed involving AC and DC networks, both with distributed generations and demands. The various components of the DC microgrid were designed and built including DC-DC converters, voltage source inverters (VSI) and AC-DC rectifiers featuring novel designs developed by the candidate. New control techniques were developed and implemented to maximize the operating range of the power conditioning units used for integrating renewable energy into the DC bus. The control and operation of the DC microgrids in the hybrid AC/DC system involve intelligent energy management. Real-time energy management algorithms were developed and experimentally verified. These algorithms are based on intelligent decision-making elements along with an optimization process. This was aimed at enhancing the overall performance of the power system and mitigating the effect of heavy non-linear loads with variable intensity and duration. The developed algorithms were also used for managing the charging/discharging process of plug-in electric vehicle emulators.
The protection of the proposed hybrid AC/DC power system was studied. Fault analysis and protection scheme and coordination, in addition to ideas on how to retrofit currently available protection concepts and devices for AC systems in a DC network, were presented. A study was also conducted on the effect of changing the distribution architecture and distributing the storage assets on the various zones of the network on the system’s dynamic security and stability. A practical shipboard power system was studied as an example of a hybrid AC/DC power system involving pulsed loads. Generally, the proposed hybrid AC/DC power system, besides most of the ideas, controls and algorithms presented in this dissertation, were experimentally verified at the Smart Grid Testbed, Energy Systems Research Laboratory. All the developments in this dissertation were experimentally verified at the Smart Grid Testbed.
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