Modelado dinámico y control de maniobras de dispositivos submarinos

Es bien conocido por todos que la Primera Revolución Industrial, que tuvo su inicio en la segunda mitad del Siglo XVIII, conllevó un aumento del uso de los recursos energéticos que no se ha detenido para llegar a los niveles de desarrollo tecnológico, industrial y de calidad de vida, de los que se dispone en la actualidad. A simple vista podría intuirse que para disponer de un mayor nivel tecnológico, industrial, de confort, etc. sea necesario un mayor consumo de energía primaria. La actual generación de energía está principalmente basada en el procesamiento de los diversos compuestos del carbono (hidrocarburos, gases y productos derivados del petróleo), que son contaminantes y además, se agotan. Desde hace unas pocas décadas, la humanidad ha sido consciente que es necesario generar energía a partir de fuentes de origen renovable, y que además resulten menos contaminantes. Así, en la actualidad, se ha llegado a un estado de desarrollo avanzado para la explotación de diversas fuentes de energías como la eólica, a la vez que se comienza a mirar con realismo la posibilidad de explotación de diversas energías de origen marino. Se considera que las energías renovables procedentes de los océanos que se encuentran más desarrolladas tecnológicamente hablando, sin tener en cuenta la energía eólica fuera costa (offshore), son la denominada energía undimotriz o de las olas y la energía de las corrientes marinas, no necesariamente en este orden. El trabajo propuesto en esta Tesis se centra en este último recurso energético y, aunque no se dispone todavía de ningún dispositivo en fase de explotación comercial, la concepción, diseño y desarrollo de dispositivos para la extracción de energía de las corrientes, y su evolución, han sido relativamente rápidos e importantes en estos últimos años. Existen ya diferentes dispositivos en fase de pruebas con resultados muy prometedores. Aunque los dispositivos actuales se encuentran limitados a la explotación energética en zonas de poca profundidad, los diferentes estudios del recurso indican la necesidad de explotar corrientes marinas a mayores profundidades, para lo que se están desarrollando actualmente dispositivos, cuya evolución en lo que a sistemas de fondeo se refiere, está siendo muy parecida a la que se ha producido en los parques eólicos fuera costa, similar a su vez, a la evolución llevada a cabo en las plataformas oceánicas para la explotación de recursos petrolíferos (denominados oil & gas) que se extraen de profundidades cada vez mayores. Las soluciones tecnológicas que resulten válidas han de ser también económicamente viables, y en la actualidad se requiere todavía reducir costos en todas las fases de instalación, explotación y mantenimiento de estos dispositivos, sea cual sea su profundidad de operación. Uno de los focos de estudio para abaratar los costes de explotación en general, pasa por abaratar y reducir los costes en las maniobras necesarias de inmersión (de la superficie del mar a la profundidad de operación) y emersión (de la profundidad de operación a la superficie del mar) de estos dispositivos, para llevar a cabo tareas de mantenimiento in situ, en el mar, y sin necesidad de buques especializados ni de su transporte a tierra. En esta Tesis se propone, en primer lugar, un método para evaluar el ciclo de vida de diversos dispositivos de aprovechamiento de las corrientes marinas. Se evidencia que el coste de la energía así generada sigue siendo no plenamente competitivo, por lo que se requiere avanzar en el abaratamiento de costes, principalmente en la instalación y en su mantenimiento. Para ello se propone como novedad principal, introducir sistemas de control en lazo cerrado para realizar maniobras de instalación y mantenimiento de forma automática. También se aporta un modelo dinámico original y muy sencillo para dispositivos bajo estos movimientos de emersión/inmersión, a partir del cual se han desarrollado los algoritmos de control para el propósito mencionado, que no es otro sino automatizar en todo lo posible las maniobras completas. Los algoritmos de control propuestos han sido validados mediante simulación. Se proponen trayectorias de referencia de movimiento suaves (smooth) similares a las utilizadas en robótica. Estos movimientos de cambios de profundidad en lazo cerrado, combinados con secuencias de movimientos en bucle abierto para cuando el dispositivo interacciona en la superficie libre, han dado lugar a nuevas maniobras completas de instalación y mantenimiento que se presentan en esta Tesis, diferentes a las actuales. Finalmente, y como justificación de la viabilidad económica del método novedoso aportado, se ha realizado un estudio comparativo de los costes de la tecnología propuesta, frente a la tecnología actual. Este nuevo sistema de maniobras automáticas implica un ciclo de vida diferente para los dispositivos de aprovechamiento de la energía de las corrientes, ciclo que se cuantifica a partir de un dispositivo base que ha sido modificado y adaptado para la nueva tecnología propuesta, demostrando su viabilidad tanto técnica como económica. ABSTRACT It’s well known that the First Industrial Revolution started in the second half of the eighteenth century, carried the increasing of the use of energy resource which have not been stopped until reach the present technology, industrial evolution and daily life quality. On the surface, it can be known intuitively that a higher consumption of primary energy resource is demanded for benefiting from a higher technological industrial and daily life level. Today, the generation of energy is mainly based in the processing of carbon products (hydrocarbons, gases and petroleum products) which are pollutants, and additionally, are depleted. From a few decades ago, the humanity is aware the energy should be obtained from renewable resources, which besides, should be cleaner. So, at the present, a technical develop has been gained to exploit several energy source, as wind energy, and, at the same time, the extraction of the marine energy starts to seem as a reality. The renewable marine energies considered more advanced and technically developed, without keeping in mind, the offshore wind energy, are the wave energy and the tidal current energy, not necessarily in that order. This Thesis is focused in this last energy resource, and, although, any device is under commercial operation, the concept, design and develop of this type of devices to extract the tidal current energy and their evolution has been comparatively fast and important the last years. There are several devices under test with promising results. Even through the current devices are limited to lower depth areas, the several studies of the tidal energy resource suggest the need to exploit the marine current at greater depths to what is being developed devices, where their evolution in the anchoring system is being very similar to the evolution performed in the offshore wind farms, which is at the same time, similar to the evolution in the oil and gas exploitation which are extracted to greatest depths. Viable technical solutions should be also viable economically and nowadays the cost in all phases of the project (installation, maintenance and operation) should be decreased whatever the operation depth is. One focus of study to lower the operation cost is the cost decreasing of immersion manoeuvring operations (from sea surface to the operation depth) and immersion manoeuvring operations (from operation depth to the sea surface), therefore the maintenance operations can be performed on – site, in the sea, and no specialized vessels are required to transport the devices from the sea to shore. In this dissertation, firstly is proposed a method to evaluate the life cycle of the tidal energy current devices. It is proved the energy generated by these devices is not fully competitive; therefore, the cost falling is mainly an objective in the installation and the maintenance operations. For that, it is proposed as main novelty, the using of closed loop control systems to perform the automatic installation and manoeuvring operations. It is also contributed with an original and simple dynamic model and for controlling the immersion/emersion movements of these devices, from which the control algorithms are developed in order to automate as much as possible the complete manoeuvring. The control algorithms proposed has been validated by simulations. Reference paths with smooth movements, similar which are used in robotics, are suggested. These movements to change the depth using closed loop control, combined with the sequences in open loop movements when the device is in free surface, have been development for a new complete manoeuvring to installation and maintenance operations which are advanced in this Thesis and they are different to the present manoeuvrings. Finally and as justification of the economic viability of this original method, a comparative cost study between the technology proposed and the current technology is performed. This new automatic manoeuvring system involves a different life cycle for the tidal energy current devices, cycle that is quantified from a base device which has been modified and adapted for the new proposed technology, showing the technical and economic viability.

Optimal control and operation of drum granulation processes

Process optimisation and optimal control of batch and continuous drum granulation processes are studied in this paper. The main focus of the current research has been: (i) construction of optimisation and control relevant, population balance models through the incorporation of moisture content, drum rotation rate and bed depth into the coalescence kernels; (ii) investigation of optimal operational conditions using constrained optimisation techniques; (iii) development of optimal control algorithms based on discretized population balance equations; and (iv) comprehensive simulation studies on optimal control of both batch and continuous granulation processes. The objective of steady state optimisation is to minimise the recycle rate with minimum cost for continuous processes. It has been identified that the drum rotation-rate, bed depth (material charge), and moisture content of solids are practical decision (design) parameters for system optimisation. The objective for the optimal control of batch granulation processes is to maximize the mass of product-sized particles with minimum time and binder consumption. The objective for the optimal control of the continuous process is to drive the process from one steady state to another in a minimum time with minimum binder consumption, which is also known as the state-driving problem. It has been known for some time that the binder spray-rate is the most effective control (manipulative) variable. Although other possible manipulative variables, such as feed flow-rate and additional powder flow-rate have been investigated in the complete research project, only the single input problem with the binder spray rate as the manipulative variable is addressed in the paper to demonstrate the methodology. It can be shown from simulation results that the proposed models are suitable for control and optimisation studies, and the optimisation algorithms connected with either steady state or dynamic models are successful for the determination of optimal operational conditions and dynamic trajectories with good convergence properties. (c) 2005 Elsevier Ltd. All rights reserved.

A methodology for analysis and control of discrete event dynamic systems

The rapid developments in computer technology have resulted in a widespread use of discrete event dynamic systems (DEDSs). This type of system is complex because it exhibits properties such as concurrency, conflict and non-determinism. It is therefore important to model and analyse such systems before implementation to ensure safe, deadlock free and optimal operation. This thesis investigates current modelling techniques and describes Petri net theory in more detail. It reviews top down, bottom up and hybrid Petri net synthesis techniques that are used to model large systems and introduces on object oriented methodology to enable modelling of larger and more complex systems. Designs obtained by this methodology are modular, easy to understand and allow re-use of designs. Control is the next logical step in the design process. This thesis reviews recent developments in control DEDSs and investigates the use of Petri nets in the design of supervisory controllers. The scheduling of exclusive use of resources is investigated and an efficient Petri net based scheduling algorithm is designed and a re-configurable controller is proposed. To enable the analysis and control of large and complex DEDSs, an object oriented C++ software tool kit was developed and used to implement a Petri net analysis tool, Petri net scheduling and control algorithms. Finally, the methodology was applied to two industrial DEDSs: a prototype can sorting machine developed by Eurotherm Controls Ltd., and a semiconductor testing plant belonging to SGS Thomson Microelectronics Ltd.

Adaptive rate control of dedicated short range communications based vehicle networks for road safety applications

Dedicated Short Range Communication (DSRC) is a promising technique for vehicle ad-hoc network (VANET) and collaborative road safety applications. As road safety applications require strict quality of services (QoS) from the VANET, it is crucial for DSRC to provide timely and reliable communications to make safety applications successful. In this paper we propose two adaptive message rate control algorithms for low priority safety messages, in order to provide highly available channel for high priority emergency messages while improve channel utilization. In the algorithms each vehicle monitors channel loads and independently controls message rate by a modified additive increase and multiplicative decrease (AIMD) method. Simulation results demonstrated the effectiveness of the proposed rate control algorithms in adapting to dynamic traffic load.

Enhancing the performance of intelligent control systems in the face of higher levels of complexity and uncertainty

Modern advances in technology have led to more complex manufacturing processes whose success centres on the ability to control these processes with a very high level of accuracy. Plant complexity inevitably leads to poor models that exhibit a high degree of parametric or functional uncertainty. The situation becomes even more complex if the plant to be controlled is characterised by a multivalued function or even if it exhibits a number of modes of behaviour during its operation. Since an intelligent controller is expected to operate and guarantee the best performance where complexity and uncertainty coexist and interact, control engineers and theorists have recently developed new control techniques under the framework of intelligent control to enhance the performance of the controller for more complex and uncertain plants. These techniques are based on incorporating model uncertainty. The newly developed control algorithms for incorporating model uncertainty are proven to give more accurate control results under uncertain conditions. In this paper, we survey some approaches that appear to be promising for enhancing the performance of intelligent control systems in the face of higher levels of complexity and uncertainty.

Control Strategues for Automatic Generation Control over MTDC Grid

Increasingly in power systems, there is a trend towards the sharing of reserves and integration of markets over wide areas in order to enable increased penetration of renewable sources in interconnected power systems. In this paper, a number of simple PI and gain based Model Predictive Control algorithms are proposed for Automatic Generation Control in AC areas connected to Multi-Terminal Direct Current grids. The paper discusses how this approach improves the sharing of secondary reserves and could assist in achieving EU energy targets for 2030 and beyond.

Real-time load-side control of electric power systems

Two trends are emerging from modern electric power systems: the growth of renewable (e.g., solar and wind) generation, and the integration of information technologies and advanced power electronics. The former introduces large, rapid, and random fluctuations in power supply, demand, frequency, and voltage, which become a major challenge for real-time operation of power systems. The latter creates a tremendous number of controllable intelligent endpoints such as smart buildings and appliances, electric vehicles, energy storage devices, and power electronic devices that can sense, compute, communicate, and actuate. Most of these endpoints are distributed on the load side of power systems, in contrast to traditional control resources such as centralized bulk generators. This thesis focuses on controlling power systems in real time, using these load side resources. Specifically, it studies two problems.

(1) Distributed load-side frequency control: We establish a mathematical framework to design distributed frequency control algorithms for flexible electric loads. In this framework, we formulate a category of optimization problems, called optimal load control (OLC), to incorporate the goals of frequency control, such as balancing power supply and demand, restoring frequency to its nominal value, restoring inter-area power flows, etc., in a way that minimizes total disutility for the loads to participate in frequency control by deviating from their nominal power usage. By exploiting distributed algorithms to solve OLC and analyzing convergence of these algorithms, we design distributed load-side controllers and prove stability of closed-loop power systems governed by these controllers. This general framework is adapted and applied to different types of power systems described by different models, or to achieve different levels of control goals under different operation scenarios. We first consider a dynamically coherent power system which can be equivalently modeled with a single synchronous machine. We then extend our framework to a multi-machine power network, where we consider primary and secondary frequency controls, linear and nonlinear power flow models, and the interactions between generator dynamics and load control.

(2) Two-timescale voltage control: The voltage of a power distribution system must be maintained closely around its nominal value in real time, even in the presence of highly volatile power supply or demand. For this purpose, we jointly control two types of reactive power sources: a capacitor operating at a slow timescale, and a power electronic device, such as a smart inverter or a D-STATCOM, operating at a fast timescale. Their control actions are solved from optimal power flow problems at two timescales. Specifically, the slow-timescale problem is a chance-constrained optimization, which minimizes power loss and regulates the voltage at the current time instant while limiting the probability of future voltage violations due to stochastic changes in power supply or demand. This control framework forms the basis of an optimal sizing problem, which determines the installation capacities of the control devices by minimizing the sum of power loss and capital cost. We develop computationally efficient heuristics to solve the optimal sizing problem and implement real-time control. Numerical experiments show that the proposed sizing and control schemes significantly improve the reliability of voltage control with a moderate increase in cost.

REAL TIME FUZZY CONTROLLER FOR QUADROTOR STABILITY CONTROL

In this report, we develop an intelligent adaptive neuro-fuzzy controller by using adaptive neuro fuzzy inference system (ANFIS) techniques. We begin by starting with a standard proportional-derivative (PD) controller and use the PD controller data to train the ANFIS system to develop a fuzzy controller. We then propose and validate a method to implement this control strategy on commercial off-the-shelf (COTS) hardware. An analysis is made into the choice of filters for attitude estimation. These choices are limited by the complexity of the filter and the computing ability and memory constraints of the micro-controller. Simplified Kalman filters are found to be good at estimation of attitude given the above constraints. Using model based design techniques, the models are implemented on an embedded system. This enables the deployment of fuzzy controllers on enthusiast-grade controllers. We evaluate the feasibility of the proposed control strategy in a model-in-the-loop simulation. We then propose a rapid prototyping strategy, allowing us to deploy these control algorithms on a system consisting of a combination of an ARM-based microcontroller and two Arduino-based controllers. We then use a combination of the code generation capabilities within MATLAB/Simulink in combination with multiple open-source projects in order to deploy code to an ARM CortexM4 based controller board. We also evaluate this strategy on an ARM-A8 based board, and a much less powerful Arduino based flight controller. We conclude by proving the feasibility of fuzzy controllers on Commercial-off the shelf (COTS) hardware, we also point out the limitations in the current hardware and make suggestions for hardware that we think would be better suited for memory heavy controllers.

DATA DRIVEN INTELLIGENT AGENT NETWORKS FOR ADAPTIVE MONITORING AND CONTROL

To analyze the characteristics and predict the dynamic behaviors of complex systems over time, comprehensive research to enable the development of systems that can intelligently adapt to the evolving conditions and infer new knowledge with algorithms that are not predesigned is crucially needed. This dissertation research studies the integration of the techniques and methodologies resulted from the fields of pattern recognition, intelligent agents, artificial immune systems, and distributed computing platforms, to create technologies that can more accurately describe and control the dynamics of real-world complex systems. The need for such technologies is emerging in manufacturing, transportation, hazard mitigation, weather and climate prediction, homeland security, and emergency response. Motivated by the ability of mobile agents to dynamically incorporate additional computational and control algorithms into executing applications, mobile agent technology is employed in this research for the adaptive sensing and monitoring in a wireless sensor network. Mobile agents are software components that can travel from one computing platform to another in a network and carry programs and data states that are needed for performing the assigned tasks. To support the generation, migration, communication, and management of mobile monitoring agents, an embeddable mobile agent system (Mobile-C) is integrated with sensor nodes. Mobile monitoring agents visit distributed sensor nodes, read real-time sensor data, and perform anomaly detection using the equipped pattern recognition algorithms. The optimal control of agents is achieved by mimicking the adaptive immune response and the application of multi-objective optimization algorithms. The mobile agent approach provides potential to reduce the communication load and energy consumption in monitoring networks. The major research work of this dissertation project includes: (1) studying effective feature extraction methods for time series measurement data; (2) investigating the impact of the feature extraction methods and dissimilarity measures on the performance of pattern recognition; (3) researching the effects of environmental factors on the performance of pattern recognition; (4) integrating an embeddable mobile agent system with wireless sensor nodes; (5) optimizing agent generation and distribution using artificial immune system concept and multi-objective algorithms; (6) applying mobile agent technology and pattern recognition algorithms for adaptive structural health monitoring and driving cycle pattern recognition; (7) developing a web-based monitoring network to enable the visualization and analysis of real-time sensor data remotely. Techniques and algorithms developed in this dissertation project will contribute to research advances in networked distributed systems operating under changing environments.

Optimal control of non-linear systems through hybrid cell-mapping/artificial-neural-networks techniques

In this paper, a real-time optimal control technique for non-linear plants is proposed. The control system makes use of the cell-mapping (CM) techniques, widely used for the global analysis of highly non-linear systems. The CM framework is employed for designing approximate optimal controllers via a control variable discretization. Furthermore, CM-based designs can be improved by the use of supervised feedforward artificial neural networks (ANNs), which have proved to be universal and efficient tools for function approximation, providing also very fast responses. The quantitative nature of the approximate CM solutions fits very well with ANNs characteristics. Here, we propose several control architectures which combine, in a different manner, supervised neural networks and CM control algorithms. On the one hand, different CM control laws computed for various target objectives can be employed for training a neural network, explicitly including the target information in the input vectors. This way, tracking problems, in addition to regulation ones, can be addressed in a fast and unified manner, obtaining smooth, averaged and global feedback control laws. On the other hand, adjoining CM and ANNs are also combined into a hybrid architecture to address problems where accuracy and real-time response are critical. Finally, some optimal control problems are solved with the proposed CM, neural and hybrid techniques, illustrating their good performance.

Development and testing of innovative methodologies for modelling and control of normal and knocking combustion and implementation of novel rapid prototyping solutions

The thesis work deals with topics that led to the development of innovative control-oriented models and control algorithms for modern gasoline engines. Knock in boosted spark ignition engines is the widest topic discussed in this document because it remains one of the most limiting factors for maximizing combustion efficiency in this kind of engine. First chapter is thus focused on knock and a wide literature review is proposed to summarize the preliminary knowledge that even represents the background and the reference for discussed activities. Most relevant results achieved during PhD course in the field of knock modelling and control are then presented, describing every control-oriented model that led to the development of an adaptive model-based combustion control system. The complete controller has been developed in the context of the collaboration with Ferrari GT and it allowed to completely redefine the knock intensity evaluation as well as the combustion phase control. The second chapter is focused on the activity related to a prototyping Port Water Injection system that has been developed and tested on a turbocharged spark ignition engine, within the collaboration with Magneti Marelli. Such system and the effects of injected water on the combustion process were then modeled in a 1-D simulation environment (GT Power). Third chapter shows the development and validation of a control-oriented model for the real-time calculation of exhaust gas temperature that represents another important limitation to the performance increase in modern boosted engines. Indeed, modelling of exhaust gas temperature and thermocouple behavior are themes that play a key role in the optimization of combustion and catalyst efficiency.

Mechanical design and hybrid control strategies for overconstrained cable-driven parallel robots

Cable-driven parallel robots offer significant advantages in terms of workspace dimensions and payload capability. They are attractive for many industrial tasks to be performed on a large scale, such as handling and manufacturing, without a substantial increase in costs and mechanical complexity with respect to a small-scale application. However, since cables can only sustain tensile stresses, cable tensions must be kept within positive limits during the end-effector motion. This problem can be managed by overconstraining the end-effector and controlling cable tensions. Tension control is typically achieved by mounting a load sensor on all cables, and using specific control algorithms to avoid cable slackness or breakage while the end-effector is controlled in a desired position. These algorithms require multiple cascade control loops and they can be complex and computationally demanding. To simplify the control of overconstrained cable-driven parallel robots, this Thesis proposes suitable mechanical design and hybrid control strategies. It is shown how a convenient design of the cable guidance system allows kinematic modeling to be simplified, without introducing geometric approximations. This guidance system employs swiveling pulleys equipped with position and tension sensors and provides a parallelogram arrangement of cables. Furthermore, a hybrid force/position control in the robot joint space is adopted. According to this strategy, a particular set of cables is chosen to be tension-controlled, whereas the other cables are length-controlled. The force-controlled cables are selected based on the computation of a novel index called force-distribution sensitivity to cable-tension errors. This index aims to evaluate the maximum expected cable-tension error in the length-controlled cables if a unit tension error is committed in the force-controlled cables. In practice, the computation of the force-distribution sensitivity allows determining which cables are best to be force-controlled, to ensure the lowest error in the overall force distribution when a hybrid force/position joint-space strategy is used.

Experimental investigation on adaptive robust controller designs applied to a free-floating space manipulator

This paper aims to formulate and investigate the application of various nonlinear H(infinity) control methods to a fiee-floating space manipulator subject to parametric uncertainties and external disturbances. From a tutorial perspective, a model-based approach and adaptive procedures based on linear parametrization, neural networks and fuzzy systems are covered by this work. A comparative study is conducted based on experimental implementations performed with an actual underactuated fixed-base planar manipulator which is, following the DEM concept, dynamically equivalent to a free-floating space manipulator. (C) 2011 Elsevier Ltd. All rights reserved.

Modeling extended Petri nets compatible with GHENeSys IEC61131 for industrial automation

Petri net (PN) modeling is one of the most used formal methods in the automation applications field, together with programmable logic controllers (PLCs). Therefore, the creation of a modeling methodology for PNs compatible with the IEC61131 standard is a necessity of automation specialists. Different works dealing with this subject have been carried out; they are presented in the first part of this paper [Frey (2000a, 2000b); Peng and Zhou (IEEE Trans Syst Man Cybern, Part C Appl Rev 34(4):523-531, 2004); Uzam and Jones (Int J Adv Manuf Technol 14(10):716-728, 1998)], but they do not present a completely compatible methodology with this standard. At the same time, they do not maintain the simplicity required for such applications, nor the use of all-graphical and all-mathematical ordinary Petri net (OPN) tools to facilitate model verification and validation. The proposal presented here completes these requirements. Educational applications at the USP and UEA (Brazil) and the UO (Cuba), as well as industrial applications in Brazil and Cuba, have already been carried out with good results.

Simulação e controlo de veículos autónomos terrestres

A implementação e venda de robôs autónomos tem sido um sector que nos últimos anos tem adquirido cada vez mais quota no mercado, nomeadamente no sector militar, agrícola e da vigilância. Como tal, tem sido também de grande importância a capacidade de implementar e testar robôs por parte das entidades que os fabricam. Uma das formas que tem garantido o sucesso do desenvolvimento de robôs é a simulação prévia dos mesmos antes que estes passem a fase de produção. Sendo assim, o LSA como entidade de desenvolvimento de robôs autónomos, tem necessidade de adquirir um sistema que simule os robôs em desenvolvimento. O trabalho desta tese consiste na realização de um sistema que simule robôs autónomos terrestres de forma que se possa observar o comportamento da cinemática, dinânica e hardware dos robôs em ambiente 3D. Esta aplicação de simulação pode mais tarde ser utilizada pelo laboratório para testar missões, validar alterações de estrutura, sensores, etc. Para além disso, com recurso ao simulador Player/Stage/Gazebo testar o robô LINCE e implementar algoritmos de controlo para o mesmo. Os algoritmos de controlo implementados baseiam-se em primitivas de controlo básico para serem utilizadas pelo sistema de navegação e gerar trajectórias complexas. Os algoritmos desenvolvidos nesta tese baseiam-se nas equações cinemáticas do veículo estudado. Estes algoritmos depois de testados no simulador, poderão ser colocados no Hardware do robô. Desta forma consegue-se desenvolver algoritmos para determinado robô sem que este esteja operacional.