{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/83856"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/83856","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"System Characterization, Control and Optimal Feed -Rate Scheduling for High -Speed Machining and Nano Positioning","abstract":"Finally, a provably-optimal feedrate-optimization (trajectory planning) algorithm is developed to exploit the capabilities of a given physical motion system. System capabilities and process requirements are modeled and formulated as constraints to drive the algorithm. The resulting trajectory makes full use of the system capabilities and completes the required task in the minimum time, while satisfying all performance requirements such as dimensional error, maximum cutting force, etc. A bi-directional scan structure is adopted for the algorithm and a sub-optimization structure for each optimized point. These features make the algorithm computationally efficient, extendable to any state-dependent constraints and robust with respect to singularity difficulties often encountered in the optimal control approach. By studying the behavior of the algorithm in the phase plane, global optimality of this feedrate-optimization algorithm is proved.","abstract_html":"Finally, a provably-optimal feedrate-optimization (trajectory planning) algorithm is developed to exploit the capabilities of a given physical motion system. System capabilities and process requirements are modeled and formulated as constraints to drive the algorithm. The resulting trajectory makes full use of the system capabilities and completes the required task in the minimum time, while satisfying all performance requirements such as dimensional error, maximum cutting force, etc. A bi-directional scan structure is adopted for the algorithm and a sub-optimization structure for each optimized point. These features make the algorithm computationally efficient, extendable to any state-dependent constraints and robust with respect to singularity difficulties often encountered in the optimal control approach. By studying the behavior of the algorithm in the phase plane, global optimality of this feedrate-optimization algorithm is proved.","abstract_has_math":false,"creators":["Dong, Jingyan"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Mechanical Engineering","degree_department":null,"school":null,"contributors":["Ferreira, Placid M.","James A. 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Stori"],"dc:creator":["Dong, Jingyan"],"dc:date":["2015-09-25T21:12:28Z","10000-01-01","2006"],"dc:description":["Finally, a provably-optimal feedrate-optimization (trajectory planning) algorithm is developed to exploit the capabilities of a given physical motion system. System capabilities and process requirements are modeled and formulated as constraints to drive the algorithm. The resulting trajectory makes full use of the system capabilities and completes the required task in the minimum time, while satisfying all performance requirements such as dimensional error, maximum cutting force, etc. A bi-directional scan structure is adopted for the algorithm and a sub-optimization structure for each optimized point. These features make the algorithm computationally efficient, extendable to any state-dependent constraints and robust with respect to singularity difficulties often encountered in the optimal control approach. 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