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Full-Text Articles in Engineering
Design And Control Of Next-Generation Uavs For Effectively Interacting With Environments, Caiwu Ding
Design And Control Of Next-Generation Uavs For Effectively Interacting With Environments, Caiwu Ding
Dissertations
In this dissertation, the design and control of a novel multirotor for aerial manipulation is studied, with the aim of endowing the aerial vehicle with more degrees of freedom of motion and stability when interacting with the environments. Firstly, it presents an energy-efficient adaptive robust tracking control method for a class of fully actuated, thrust vectoring unmanned aerial vehicles (UAVs) with parametric uncertainties including unknown moment of inertia, mass and center of mass, which would occur in aerial maneuvering and manipulation. The effectiveness of this method is demonstrated through simulation. Secondly, a humanoid robot arm is adopted to serve as …
Optimal Sampling Paths For Autonomous Vehicles In Uncertain Ocean Flows, Andrew J. De Stefan
Optimal Sampling Paths For Autonomous Vehicles In Uncertain Ocean Flows, Andrew J. De Stefan
Dissertations
Despite an extensive history of oceanic observation, researchers have only begun to build a complete picture of oceanic currents. Sparsity of instrumentation has created the need to maximize the information extracted from every source of data in building this picture. Within the last few decades, autonomous vehicles, or AVs, have been employed as tools to aid in this research initiative. Unmanned and self-propelled, AVs are capable of spending weeks, if not months, exploring and monitoring the oceans. However, the quality of data acquired by these vehicles is highly dependent on the paths along which they collect their observational data. The …
Multi-Population-Based Differential Evolution Algorithm For Optimization Problems, Ishani Chatterjee
Multi-Population-Based Differential Evolution Algorithm For Optimization Problems, Ishani Chatterjee
Theses
A differential evolution (DE) algorithm is an evolutionary algorithm for optimization problems over a continuous domain. To solve high dimensional global optimization problems, this work investigates the performance of differential evolution algorithms under a multi-population strategy. The original DE algorithm generates an initial set of suitable solutions. The multi-population strategy divides the set into several subsets. These subsets evolve independently and connect with each other according to the DE algorithm. This helps in preserving the diversity of the initial set. Furthermore, a comparison of combination of different mutation techniques on several optimization algorithms is studied to verify their performance. Finally, …