Sistemas inteligentes adaptativos aplicados a um robô auto-equilibrante de duas rodas.

Com o avanço no desenvolvimento e utilização de veículos e robôs autoequilibrantes, faz-se necessário a investigação de controladores capazes de atender os diversos desafios relacionados à utilização desses sistemas. Neste trabalho foi estudado o controle de equilíbrio e posição de um robô auto-equilibrante de duas rodas. O interesse particular nesta aplicação vem da sua estrutura e da riqueza de sua dinâmica física. Por ser um problema complexo e não trivial há grande interesse em avaliar os controladores inteligentes. A primeira parte da dissertação aborda o desenvolvimento de um controle clássico do tipo PID, para em seguida ser comparado com a implementação de dois tipos de controladores inteligentes: On-line Neuro Fuzzy Control (ONFC) e Proportional-Integral-Derivative Neural-Network (PIDNN). Também é apresentada a implementação dos controladores em uma plataforma de hardware, utilizando o kit LEGO Mindstorm, e numa plataforma de simulação utilizando o MATLAB-Simulink. Em seguida, dois estudos de casos são desenvolvidos visando comparar o desempenho dos controladores. O primeiro caso avalia o controle de equilíbrio e posição do robô auto-equilibrante de duas rodas sobre um terreno plano tendo como interesse observar o desempenho intrínseco do sistema sob ausência de fatores externos. O segundo caso estuda o controle de equilíbrio e posição do robô em terrenos irregulares visando investigar a resposta do sistema sob influência de condições adversas em seu ambiente. Finalmente, o desempenho de cada um dos controladores desenvolvidos é discutido, verificando-se resultados competitivos no controle do robô auto-equilibrante de duas rodas.

Auto ID based control systems - An overview

This paper will provide a rationale for developing control systems based on the availability of automated identification (Auto ID) information provision. Much of the Auto-ID research has to date focussed on developing the essential infrastructure for dynamically extracting, networking and storing product data. These developments will help to revolutionise the accuracy, quality and timeliness of data acquired by Business Information Systems and should lead to major cost savings and performance improvements as a result. This paper introduces an additional phase of Auto ID research and development in which the nature of control system decisions is reconsidered in the light of the availability of ubiquitous, unique, item-level information. The paper will: (i) Indicate why the availability of ubiquitous, unique, item-level data can enable enhanced and fundamentally different control approaches and highlight potential benefits from control systems incorporating this Auto ID data (ii) Demonstrate what is required to develop control systems based around the availability of Auto ID data. (iii) Outline the research challenges in determining how such systems will be developed.

Auto-calibration of a camera system using Image Alignment

Calibration of a camera system is a necessary step in any stereo metric process. It correlates all cameras to a common coordinate system by measuring the intrinsic and extrinsic parameters of each camera. Currently, manual calibration of a camera system is the only way to achieve calibration in civil engineering operations that require stereo metric processes (photogrammetry, videogrammetry, vision based asset tracking, etc). This type of calibration however is time-consuming and labor-intensive. Furthermore, in civil engineering operations, camera systems are exposed to open, busy sites. In these conditions, the position of presumably stationary cameras can easily be changed due to external factors such as wind, vibrations or due to an unintentional push/touch from personnel on site. In such cases manual calibration must be repeated. In order to address this issue, several self-calibration algorithms have been proposed. These algorithms use Projective Geometry, Absolute Conic and Kruppa Equations and variations of these to produce processes that achieve calibration. However, most of these methods do not consider all constraints of a camera system such as camera intrinsic constraints, scene constraints, camera motion or varying camera intrinsic properties. This paper presents a novel method that takes all constraints into consideration to auto-calibrate cameras using an image alignment algorithm originally meant for vision based tracking. In this method, image frames are taken from cameras. These frames are used to calculate the fundamental matrix that gives epipolar constraints. Intrinsic and extrinsic properties of cameras are acquired from this calculation. Test results are presented in this paper with recommendations for further improvement.

Pixel-level tunable liquid crystal lenses for auto-stereoscopic display

Mobile video and gaming are now widely used, and delivery of a glass-free 3D experience is of both research and development interest. The key drawbacks of a conventional 3D display based on a static lenticular lenslet array and parallax barriers are low resolution, limited viewing angle and reduced brightness, mainly because of the need of multiple-pixels for each object point. This study describes the concept and performance of pixel-level cylindrical liquid crystal (LC) lenses, which are designed to steer light to the left and right eye sequentially to form stereo parallax. The width of the LC lenses can be as small as 20-30 μm, so that the associated auto-stereoscopic display will have the same resolution as the 2D display panel in use. Such a thin sheet of tunable LC lens array can be applied directly on existing mobile displays, and can deliver 3D viewing experience while maintaining 2D viewing capability. Transparent electrodes were laser patterned to achieve the single pixel lens resolution, and a high birefringent LC material was used to realise a large diffraction angle for a wide field of view. Simulation was carried out to model the intensity profile at the viewing plane and optimise the lens array based on the measured LC phase profile. The measured viewing angle and intensity profile were compared with the simulation results. © 2014 SPIE.

A Complex BPF with On Chip Auto-tuning Architecture for Wireless Receivers

A 3(rd) order complex band-pass filter (BPF) with auto-tuning architecture is proposed in this paper. It is implemented in 0.18um standard CMOS technology. The complex filter is centered at 4.092MHz with bandwidth of 2.4MHz. The in-band 3(rd) order harmonic input intercept point (IIP3) is larger than 16.2dBm, with 50 Omega as the source impedance. The input referred noise is about 80uV(rms). The RC tuning is based on Binary Search Algorithm (BSA) with tuning accuracy of 3%. The chip area of the tuning system is 0.28 x 0.22 mm(2), less than 1/8 of that of the main-filter which is 0.92 x 0.59 mm(2). After tuning is completed, the tuning system will be turned off automatically to save power and to avoid interference. The complex filter consumes 2.6mA with a 1.8V power supply.