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This thesis proposes a distributed observer design for a class of nonlinear systems that arise in the application of model reduction techniques. Distributed observer design techniques have been proposed in the literature to address estimation problems over sensor networks. In large complex sensor networks, an efficient technique that minimizes the extent of the required communication is highly desirable. This is especially true when sensors have problems caused by physical limitations that result in incorrect information at the local level affecting the estimation of states globally. To address this problem, scalable algorithms for a suitable distributed observer have been developed. Most algorithms are focussed on large linear dynamical systems and they are not directly generalizable to nonlinear systems. In this thesis, scalable algorithms for distributed observers are proposed for a class of large scale observable nonlinear system. Distributed systems models multi-agent systems in which each agents attempts to accomplish local tasks. In order to achieve global objectives, there should be agreement regarding some commonly known variables that depend on the state of all agents. These variables are called consensus states. Once identified, such consensus states can be exploited in the development of distributed consensus algorithms. Consensus algorithms are used to develop information exchange protocols between agents such that global objectives are met through local action. In this thesis, a higher order observer is applied in the distributed sensor network system to design a distributed observer for a class nonlinear systems. Fusion of measurement and covariance information is applied to the higher order filter as the first method. The consensus filter is embedded in the local nonlinear observer for fusion of data. The second method is based on the communication of state estimates between neighbouring sensors rather than fusion of data measurement and covariance. The second method is found to reduce disagreement of the states estimation between each sensor. The performance of these new algorithms is demonstrated by simulation, and the second method is effectively applied over the first method. / Thesis (Master, Chemical Engineering) -- Queen's University, 2012-12-12 11:22:49.113

Approved for public release; distribution is unlimited / A pipeline technique by Loomis and Sinha has been applied to the design of recursive digital filters. Recursive digital filters operating at hitherto impossibly high rates can be designed by this technique. An alternate technique by R. Gnanasekaran allows high speed implementation using the state-space structure directly. High throughput is also achieved by use of pipelined multiply-add modules. The actual hardware complexity will depend upon the number of pipeline stages. These techniques are used for the design of the I IR notch filter and finally, a comparison of the performance and complexity of these two techniques is presented. / http://archive.org/details/infiniteimpulser00jang / Lieutenant, Royal Thai Navy

Today in most vehicles in battle, a camera system is used to manually lock a target and maintaining visual of the target as the vehicle is moving. In order to simplify this, this thesis investigates the approach to semi-automate the process by first manually locking the target and then let the camera approximate the trajectory of the enemy vehicle. In this thesis, the enemy vehicle is not moving. The ability to provide a truthful simulation environment for testing is crucial and will be discussed in this thesis along with three different estimators derived from the Kalman filter. Parameter identification and dynamic modelling of the camera are also presented that serves as a basis for the part of automatic control and for the experiments on the hardware. The simulation environment gave promising results when locating the target based on angle and radius estimation. By simulating a human operator, big deviations from the true value was no longer a problem since its purpose is to take over and steer the camera to the correct value. After gathering results from the simulations, Model-Based Design made it possible to test the algorithms in real life. The biggest challenge was to produce lifelike motions to test the hardware on and therefore made it harder to conclude the end result for the experiments carried out by the hardware on the moving platform.

This thesis presents a brief introduction to microwave components and technology. It also presents two novel dual-band designs, their analysis, topology, simulation and fabrication. In chapter 2, a novel dual-band bandpass filter using asymmetric stub-loaded stepped-impedance resonators (SLSIRs) operating at 1 and 2.6 GHz is shown. This type of design applies suitable arrangements to improve the filter’s performance. Then, in chapter 3, a novel dual-band balun (transforms unbalanced input signals to balanced output signals or vice versa) operating at 1.1 and 2 GHz with flexible frequency ratios is presented, which has more advantages in microwave applications. Then, conclusion and future works are discussed in chapter 4.

In this thesis the production and filtration performance of electrospun nylon-4,6 nanofiber mats was experimentally studied. The average fiber diameter of nylon-4,6 fibers is controlled by altering the polymer concentration in solution. Adding small amount of pyridine to the electrospinning solution controlled fiber beading and other defects. These fibers were then deposited onto a wide variety of conductive and dielectric substrate materials. A corona ion source was used to eliminate surface charging effects observed at the surface of all substrates. The resulting fiber mats, uniform in size and distribution as verified by SEM imaging, are tested for filtration efficiency and pressure drop. A Figure of Merit (FOM) is calculated for each filter produced and compared to high-grade commercial filters.