4 research outputs found

    Genetic programming for the automatic design of controllers for a surface ship

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    In this paper, the implementation of genetic programming (GP) to design a contoller structure is assessed. GP is used to evolve control strategies that, given the current and desired state of the propulsion and heading dynamics of a supply ship as inputs, generate the command forces required to maneuver the ship. The controllers created using GP are evaluated through computer simulations and real maneuverability tests in a laboratory water basin facility. The robustness of each controller is analyzed through the simulation of environmental disturbances. In addition, GP runs in the presence of disturbances are carried out so that the different controllers obtained can be compared. The particular vessel used in this paper is a scale model of a supply ship called CyberShip II. The results obtained illustrate the benefits of using GP for the automatic design of propulsion and navigation controllers for surface ships

    Methods of system identification, parameter estimation and optimisation applied to problems of modelling and control in engineering and physiology

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    Mathematical and computer-based models provide the foundation of most methods of engineering design. They are recognised as being especially important in the development of integrated dynamic systems, such as “control-configured” aircraft or in complex robotics applications. These models usually involve combinations of linear or nonlinear ordinary differential equations or difference equations, partial differential equations and algebraic equations. In some cases models may be based on differential algebraic equations. Dynamic models are also important in many other fields of research, including physiology where the highly integrated nature of biological control systems is starting to be more fully understood. Although many models may be developed using physical, chemical, or biological principles in the initial stages, the use of experimentation is important for checking the significance of underlying assumptions or simplifications and also for estimating appropriate sets of parameters. This experimental approach to modelling is also of central importance in establishing the suitability, or otherwise, of a given model for an intended application – the so-called “model validation” problem. System identification, which is the broad term used to describe the processes of experimental modelling, is generally considered to be a mature field and classical methods of identification involve linear discrete-time models within a stochastic framework. The aspects of the research described in this thesis that relate to applications of identification, parameter estimation and optimisation techniques for model development and model validation mainly involve nonlinear continuous time models Experimentally-based models of this kind have been used very successfully in the course of the research described in this thesis very in two areas of physiological research and in a number of different engineering applications. In terms of optimisation problems, the design, experimental tuning and performance evaluation of nonlinear control systems has much in common with the use of optimisation techniques within the model development process and it is therefore helpful to consider these two areas together. The work described in the thesis is strongly applications oriented. Many similarities have been found in applying modelling and control techniques to problems arising in fields that appear very different. For example, the areas of neurophysiology, respiratory gas exchange processes, electro-optic sensor systems, helicopter flight-control, hydro-electric power generation and surface ship or underwater vehicles appear to have little in common. However, closer examination shows that they have many similarities in terms of the types of problem that are presented, both in modelling and in system design. In addition to nonlinear behaviour; most models of these systems involve significant uncertainties or require important simplifications if the model is to be used in a real-time application such as automatic control. One recurring theme, that is important both in the modelling work described and for control applications, is the additional insight that can be gained through the dual use of time-domain and frequency-domain information. One example of this is the importance of coherence information in establishing the existence of linear or nonlinear relationships between variables and this has proved to be valuable in the experimental investigation of neuromuscular systems and in the identification of helicopter models from flight test data. Frequency-domain techniques have also proved useful for the reduction of high-order multi-input multi-output models. Another important theme that has appeared both within the modelling applications and in research on nonlinear control system design methods, relates to the problems of optimisation in cases where the associated response surface has many local optima. Finding the global optimum in practical applications presents major difficulties and much emphasis has been placed on evolutionary methods of optimisation (both genetic algorithms and genetic programming) in providing usable methods for optimisation in design and in complex nonlinear modelling applications that do not involve real-time problems. Another topic, considered both in the context of system modelling and control, is parameter sensitivity analysis and it has been found that insight gained from sensitivity information can be of value not only in the development of system models (e.g. through investigation of model robustness and the design of appropriate test inputs), but also in feedback system design and in controller tuning. A technique has been developed based on sensitivity analysis for the semi-automatic tuning of cascade and feedback controllers for multi-input multi-output feedback control systems. This tuning technique has been applied successfully to several problems. Inverse systems also receive significant attention in the thesis. These systems have provided a basis for theoretical research in the control systems field over the past two decades and some significant applications have been reported, despite the inherent difficulties in the mathematical methods needed for the nonlinear case. Inverse simulation methods, developed initially by others for use in handling-qualities studies for fixed-wing aircraft and helicopters, are shown in the thesis to provide some important potential benefits in control applications compared with classical methods of inversion. New developments in terms of methodology are presented in terms of a novel sensitivity based approach to inverse simulation that has advantages in terms of numerical accuracy and a new search-based optimisation technique based on the Nelder-Mead algorithm that can handle inverse simulation problems involving hard nonlinearities. Engineering applications of inverse simulation are presented, some of which involve helicopter flight control applications while others are concerned with feed-forward controllers for ship steering systems. The methods of search-based optimisation show some important advantages over conventional gradient-based methods, especially in cases where saturation and other nonlinearities are significant. The final discussion section takes the form of a critical evaluation of results obtained using the chosen methods of system identification, parameter estimation and optimisation for the modelling and control applications considered. Areas of success are highlighted and situations are identified where currently available techniques have important limitations. The benefits of an inter-disciplinary and applications-oriented approach to problems of modelling and control are also discussed and the value in terms of cross-fertilisation of ideas resulting from involvement in a wide range of applications is emphasised. Areas for further research are discussed

    Sistema de control de tráfico para la coexistencia entre vehículos autónomos y manuales mediante comunicaciones inalámbricas

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    Premio Extraordinario de Doctorado 2012Los avances en el campo de los sistemas inteligentes de transporte (ITS, del inglés Intelligent Transportation Systems) en los últimos años han propiciado la aparición de sistemas que ayudan de manera significativa a los conductores facilitando su labor, relegándoles de tareas tediosas. No es demasiado utópico pensar en un futuro en vehículos completamente automatizados circulando por las carreteras. Sin embargo, se precisa de un sistema de transición desde los vehículos que actualmente circulan por las carreteras hasta los vehículos completamente automatizados y, por ende, la coexistencia entre ellos. En el presente trabajo de tesis doctoral se presenta el diseño, desarrollo e implementación de un sistema global para el control del tráfico con vehículos guiados por conductores humanos o automáticos basado en comunicaciones inalámbricas con un doble objetivo: en primer lugar, disminuir de manera significativa la congestión actual del tráfico, fundamentalmente en entornos urbanos, y en segundo lugar, presentar un sistema seguro que permita pensar en una reducción del número de accidentes en las carreteras o, al menos, mitigar las consecuencias. Para lograr los objetivos propuestos se utilizarán diversas fuentes de información ya sean ubicadas en los vehículos -sistemas de navegación global por satélite (GNSS, del inglés Global Navigation Satellite System), sistemas inerciales (IMU, del inglés Inertial Measurement Unit) o cámaras- o en la infraestructura -unidades de control, sensores para detectar situaciones del tráfico. La arquitectura presentada busca la escalabilidad para permitir de manera sencilla la inclusión de nuevos dispositivos que permitan mejorar las prestaciones. Para validar la solución propuesta, se presentan diferentes experimentos llevados a cabo con vehículos comerciales, algunos de ellos modificados para permitir el control automático de los mismos en la pista de pruebas del IAI-CSIC. Dichos experimentos incluyen situaciones habituales del tráfico como pueden ser la conducción en atascos, la gestión de preferencias en intersecciones sin señalización, la evasión de un peatón que se cruce en la carretera o la llegada a una curva peligrosa no señalizada. El sistema propuesto soluciona estas situaciones reales de tráfico de forma eficiente y segura. Como principales aportaciones se destacan el sistema de control local del tráfico al que se le dota de inteligencia para optimizar las comunicaciones inalámbricas, las mejoras conseguidas sobre la arquitectura de control de los vehículos y la presentación de sistemas para el control de situaciones de tráfico en entornos desestructurados
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