{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/40461"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/40461","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"A unified method to predict pilot-induced oscillations","abstract":"A pilot-induced oscillation (PIO) is a dynamic coupling between pilot and aircraft that produces undesired oscillations as a result of attempted pilot control of the vehicle. Present day methods that are intended to predict which aircraft are susceptible to PIO deal primarily with the linear dynamics associated with both the pilot and vehicle. These methods are incapable of handling multiple dynamic effects. An analysis method that is able to handle several dynamic effects simultaneously, including nonlinearities arbitrarily located in both the pilot and vehicle models, is offered. The new unified analysis method draws from recent advances in pilot modeling, stability robustness analysis, and multivariable describing function analysis to solve the problem of identifying aircraft with PIO tendencies. The method handles simultaneous dynamic characteristics as well as nonlinear effects. Control surface rate limiting is one nonlinear effect that is known to contribute to many PIO occurrences. An example analysis of the M2-F2 lifting body is used to demonstrate how several individual dynamic effects can be analyzed simultaneously to predict aircraft PIO susceptibility. In this case, the combined effect of five separate nonlinearities and two linear parameter variations are studied. While the PIO tendency of the M2-F2 is most likely caused by poor flying qualities, a unified PIO analysis shows exactly which dynamic elements couple with the pilot dynamics to cause oscillations. The analysis results show the PIO amplitude and frequency that occurred during flight testing and piloted simulation of the M2-F2 can be accurately predicted assuming a Modified Optimal Control Model of the human pilot and simultaneous limiting in the pilot command and roll feedback channels.","abstract_html":"A pilot-induced oscillation (PIO) is a dynamic coupling between pilot and aircraft that produces undesired oscillations as a result of attempted pilot control of the vehicle. Present day methods that are intended to predict which aircraft are susceptible to PIO deal primarily with the linear dynamics associated with both the pilot and vehicle. These methods are incapable of handling multiple dynamic effects. An analysis method that is able to handle several dynamic effects simultaneously, including nonlinearities arbitrarily located in both the pilot and vehicle models, is offered. The new unified analysis method draws from recent advances in pilot modeling, stability robustness analysis, and multivariable describing function analysis to solve the problem of identifying aircraft with PIO tendencies. The method handles simultaneous dynamic characteristics as well as nonlinear effects. Control surface rate limiting is one nonlinear effect that is known to contribute to many PIO occurrences. An example analysis of the M2-F2 lifting body is used to demonstrate how several individual dynamic effects can be analyzed simultaneously to predict aircraft PIO susceptibility. In this case, the combined effect of five separate nonlinearities and two linear parameter variations are studied. While the PIO tendency of the M2-F2 is most likely caused by poor flying qualities, a unified PIO analysis shows exactly which dynamic elements couple with the pilot dynamics to cause oscillations. The analysis results show the PIO amplitude and frequency that occurred during flight testing and piloted simulation of the M2-F2 can be accurately predicted assuming a Modified Optimal Control Model of the human pilot and simultaneous limiting in the pilot command and roll feedback channels.","abstract_has_math":false,"creators":["Page, Anthony Baker"],"institution":"Virginia Tech","degree_name":"Ph. 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Present day methods that are intended to predict which aircraft are susceptible to PIO deal primarily with the linear dynamics associated with both the pilot and vehicle. These methods are incapable of handling multiple dynamic effects. An analysis method that is able to handle several dynamic effects simultaneously, including nonlinearities arbitrarily located in both the pilot and vehicle models, is offered. The new unified analysis method draws from recent advances in pilot modeling, stability robustness analysis, and multivariable describing function analysis to solve the problem of identifying aircraft with PIO tendencies. The method handles simultaneous dynamic characteristics as well as nonlinear effects. Control surface rate limiting is one nonlinear effect that is known to contribute to many PIO occurrences. An example analysis of the M2-F2 lifting body is used to demonstrate how several individual dynamic effects can be analyzed simultaneously to predict aircraft PIO susceptibility. In this case, the combined effect of five separate nonlinearities and two linear parameter variations are studied. While the PIO tendency of the M2-F2 is most likely caused by poor flying qualities, a unified PIO analysis shows exactly which dynamic elements couple with the pilot dynamics to cause oscillations. The analysis results show the PIO amplitude and frequency that occurred during flight testing and piloted simulation of the M2-F2 can be accurately predicted assuming a Modified Optimal Control Model of the human pilot and simultaneous limiting in the pilot command and roll feedback channels."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Ph. D."]},{"key":"dc:format.medium","label":"Dc Format Medium","values":["BTD"]},{"key":"dc:format.mimetype","label":"Dc Format Mimetype","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["A unified method to predict pilot-induced oscillations"]}]}],"canonical_facts":{"dc:contributor.committeechair":["Anderson, Mark R."],"dc:contributor.committeemember":["Lutze, Frederick H.","Cliff, Eugene M.","Durham, Wayne C.","Robertshaw, Harry H."],"dc:contributor.department":["Aerospace Engineering"],"dc:creator":["Page, Anthony Baker"],"dc:date.accessioned":["2014-03-14T21:23:38Z"],"dc:date.available":["2014-03-14T21:23:38Z","2005-12-22"],"dc:date.issued":["1996"],"dc:description.abstract":["A pilot-induced oscillation (PIO) is a dynamic coupling between pilot and aircraft that produces undesired oscillations as a result of attempted pilot control of the vehicle. Present day methods that are intended to predict which aircraft are susceptible to PIO deal primarily with the linear dynamics associated with both the pilot and vehicle. These methods are incapable of handling multiple dynamic effects. An analysis method that is able to handle several dynamic effects simultaneously, including nonlinearities arbitrarily located in both the pilot and vehicle models, is offered. The new unified analysis method draws from recent advances in pilot modeling, stability robustness analysis, and multivariable describing function analysis to solve the problem of identifying aircraft with PIO tendencies. The method handles simultaneous dynamic characteristics as well as nonlinear effects. Control surface rate limiting is one nonlinear effect that is known to contribute to many PIO occurrences. An example analysis of the M2-F2 lifting body is used to demonstrate how several individual dynamic effects can be analyzed simultaneously to predict aircraft PIO susceptibility. In this case, the combined effect of five separate nonlinearities and two linear parameter variations are studied. While the PIO tendency of the M2-F2 is most likely caused by poor flying qualities, a unified PIO analysis shows exactly which dynamic elements couple with the pilot dynamics to cause oscillations. The analysis results show the PIO amplitude and frequency that occurred during flight testing and piloted simulation of the M2-F2 can be accurately predicted assuming a Modified Optimal Control Model of the human pilot and simultaneous limiting in the pilot command and roll feedback channels."],"dc:description.degree":["Ph. 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