This paper focuses on the prediction of the safe autorotation landing operations of a helicopter following engine failure.The autorotation landing procedure is formulated as a nonlinear optimal control problem based o...This paper focuses on the prediction of the safe autorotation landing operations of a helicopter following engine failure.The autorotation landing procedure is formulated as a nonlinear optimal control problem based on an augmented six-degree-of-freedom rigid-body flight dynamic model.First,the cost function and constraints are properly selected.The direct transcription approach is then employed to solve the optimal control problem.For a UH-60 helicopter,the optimal solutions with the rigid-body model are compared with those obtained using a two-dimensional point-mass model.It is found that the optimal solutions using the two different models show reasonably good agreement,and furthermore the optimal solutions using the rigid-body model involve the time histories of angular rates and attitudes,lateral velocity and position,as well as pitch controls.Finally the optimal control formulations with different cost functions are proposed for taking account of 1-s time delay and minimum touchdown speed.The calculated control strategies and trajectories are realistic.展开更多
<strong>Background:</strong><span style="font-family:;" "=""><span style="font-family:Verdana;"> Intraoperative surgical planning tools (ISPTs) used in curren...<strong>Background:</strong><span style="font-family:;" "=""><span style="font-family:Verdana;"> Intraoperative surgical planning tools (ISPTs) used in current-generation robotic arm-assisted total knee arthroplasty (RTKA) systems (such as Navio</span><sup><span style="font-size:12px;font-family:Verdana;"><span lang="ZH-CN" style="font-size:12pt;font-family:宋体;">®</span></span></sup><span style="font-family:Verdana;"> and MAKO</span><sup><span style="font-size:12px;font-family:Verdana;"><span lang="ZH-CN" style="font-size:12pt;font-family:宋体;">®</span></span></sup><span style="font-family:Verdana;">) involve employment of postoperative passive joint balancing. This results in improper ligament tension, which may negatively impact joint stability, which, in turn, may adversely affect patient function after TKA. </span><b><span style="font-family:Verdana;">Methods:</span></b><span style="font-family:Verdana;"> A simulation-enhanced ISPT (SEISPT) that provides insights relating to postoperative active joint mechanics was developed. This involved four steps: 1) validation of a multi-body musculoskeletal model;2) optimization of the validated model;3) use of the validated and optimized model to derive knee performance equations (KPEs), which are equations that relate implant component characteristics to implant component biomechanical responses;and 4) optimization of the KPEs with respect to these responses. In a proof-of-concept study, KPEs that involved two</span></span><span style="font-family:Verdana;"> </span><span style="font-family:Verdana;">com</span><span style="font-family:Verdana;">- </span><span style="font-family:;" "=""><span style="font-family:Verdana;">ponent biomechanical responses that have been shown to strongly correlate with poor proprioception (a common patient complaint post-TKA) were used to calculate optimal positions and orientations of the femoral and tibial components in the TKA design implanted in one subject (as reported in a publicly-available dataset). </span><b><span style="font-family:Verdana;">Results:</span></b><span style="font-family:Verdana;"> The differences between the calculated implant positions and orientations and the corresponding achieved values for the implant components in the subject were not similar to component position and orientation errors reported in biomechanical literature studies involving Navio</span><sup><span style="font-size:12px;font-family:Verdana;"><span lang="ZH-CN" style="font-size:12pt;font-family:宋体;">®</span></span></sup><span style="font-family:Verdana;"> and MAKO</span><sup><span style="font-size:12px;font-family:Verdana;"><span lang="ZH-CN" style="font-size:12pt;font-family:宋体;">®</span></span></sup><span style="font-family:Verdana;">. Also, we indicate how SEISPT could be incorporated into the surgical workflow of Navio</span><sup><span style="font-size:12px;font-family:Verdana;"><span lang="ZH-CN" style="font-size:12pt;font-family:宋体;">®</span></span></sup><span style="font-family:Verdana;"> with minimal disruption and increase in cost. </span><b><span style="font-family:Verdana;">Conclusion:</span></b><span style="font-family:Verdana;"> SEISPT is a plausible alternative to current-gen</span></span><span style="font-family:Verdana;">- </span><span style="font-family:Verdana;">eration ISPTs.</span>展开更多
A hierarchic optimization strategy based on the offline path planning process and online trajectory planning process is presented to solve the trajectory optimization problem of multiple quad-rotor unmanned aerial veh...A hierarchic optimization strategy based on the offline path planning process and online trajectory planning process is presented to solve the trajectory optimization problem of multiple quad-rotor unmanned aerial vehicles in the collaborative assembling task. Firstly, the path planning process is solved by a novel parallel intelligent optimization algorithm, the central force optimization-genetic algorithm (CFO-GA), which combines the central force optimization (CFO) algorithm with the genetic algorithm (GA). Because of the immaturity of the CFO, the convergence analysis of the CFO is completed by the stability theory of the linear time-variant discrete-time sys- tems. The results show that the parallel CFO-GA algorithm converges faster than the parallel CFO and the central force optimization-sequential quadratic programming (CFO-SQP) algorithm. Then, the trajectory planning problem is established based on the path planning results. In order to limit the range of the attitude angle and guarantee the fight stability, the optimized object is changed from the ordinary six-degree-of-freedom rigid-body dynamic model to the dynamic model with an inner-loop attitude controller. The results show that the trajectory planning process can be solved by the mature SQP algorithm easily. Finally, the discussion and analysis of the real-time per- formance of the hierarchic optimization strategy are presented around the group number of the wav^oints and the eoual interval time.展开更多
文摘This paper focuses on the prediction of the safe autorotation landing operations of a helicopter following engine failure.The autorotation landing procedure is formulated as a nonlinear optimal control problem based on an augmented six-degree-of-freedom rigid-body flight dynamic model.First,the cost function and constraints are properly selected.The direct transcription approach is then employed to solve the optimal control problem.For a UH-60 helicopter,the optimal solutions with the rigid-body model are compared with those obtained using a two-dimensional point-mass model.It is found that the optimal solutions using the two different models show reasonably good agreement,and furthermore the optimal solutions using the rigid-body model involve the time histories of angular rates and attitudes,lateral velocity and position,as well as pitch controls.Finally the optimal control formulations with different cost functions are proposed for taking account of 1-s time delay and minimum touchdown speed.The calculated control strategies and trajectories are realistic.
文摘<strong>Background:</strong><span style="font-family:;" "=""><span style="font-family:Verdana;"> Intraoperative surgical planning tools (ISPTs) used in current-generation robotic arm-assisted total knee arthroplasty (RTKA) systems (such as Navio</span><sup><span style="font-size:12px;font-family:Verdana;"><span lang="ZH-CN" style="font-size:12pt;font-family:宋体;">®</span></span></sup><span style="font-family:Verdana;"> and MAKO</span><sup><span style="font-size:12px;font-family:Verdana;"><span lang="ZH-CN" style="font-size:12pt;font-family:宋体;">®</span></span></sup><span style="font-family:Verdana;">) involve employment of postoperative passive joint balancing. This results in improper ligament tension, which may negatively impact joint stability, which, in turn, may adversely affect patient function after TKA. </span><b><span style="font-family:Verdana;">Methods:</span></b><span style="font-family:Verdana;"> A simulation-enhanced ISPT (SEISPT) that provides insights relating to postoperative active joint mechanics was developed. This involved four steps: 1) validation of a multi-body musculoskeletal model;2) optimization of the validated model;3) use of the validated and optimized model to derive knee performance equations (KPEs), which are equations that relate implant component characteristics to implant component biomechanical responses;and 4) optimization of the KPEs with respect to these responses. In a proof-of-concept study, KPEs that involved two</span></span><span style="font-family:Verdana;"> </span><span style="font-family:Verdana;">com</span><span style="font-family:Verdana;">- </span><span style="font-family:;" "=""><span style="font-family:Verdana;">ponent biomechanical responses that have been shown to strongly correlate with poor proprioception (a common patient complaint post-TKA) were used to calculate optimal positions and orientations of the femoral and tibial components in the TKA design implanted in one subject (as reported in a publicly-available dataset). </span><b><span style="font-family:Verdana;">Results:</span></b><span style="font-family:Verdana;"> The differences between the calculated implant positions and orientations and the corresponding achieved values for the implant components in the subject were not similar to component position and orientation errors reported in biomechanical literature studies involving Navio</span><sup><span style="font-size:12px;font-family:Verdana;"><span lang="ZH-CN" style="font-size:12pt;font-family:宋体;">®</span></span></sup><span style="font-family:Verdana;"> and MAKO</span><sup><span style="font-size:12px;font-family:Verdana;"><span lang="ZH-CN" style="font-size:12pt;font-family:宋体;">®</span></span></sup><span style="font-family:Verdana;">. Also, we indicate how SEISPT could be incorporated into the surgical workflow of Navio</span><sup><span style="font-size:12px;font-family:Verdana;"><span lang="ZH-CN" style="font-size:12pt;font-family:宋体;">®</span></span></sup><span style="font-family:Verdana;"> with minimal disruption and increase in cost. </span><b><span style="font-family:Verdana;">Conclusion:</span></b><span style="font-family:Verdana;"> SEISPT is a plausible alternative to current-gen</span></span><span style="font-family:Verdana;">- </span><span style="font-family:Verdana;">eration ISPTs.</span>
文摘A hierarchic optimization strategy based on the offline path planning process and online trajectory planning process is presented to solve the trajectory optimization problem of multiple quad-rotor unmanned aerial vehicles in the collaborative assembling task. Firstly, the path planning process is solved by a novel parallel intelligent optimization algorithm, the central force optimization-genetic algorithm (CFO-GA), which combines the central force optimization (CFO) algorithm with the genetic algorithm (GA). Because of the immaturity of the CFO, the convergence analysis of the CFO is completed by the stability theory of the linear time-variant discrete-time sys- tems. The results show that the parallel CFO-GA algorithm converges faster than the parallel CFO and the central force optimization-sequential quadratic programming (CFO-SQP) algorithm. Then, the trajectory planning problem is established based on the path planning results. In order to limit the range of the attitude angle and guarantee the fight stability, the optimized object is changed from the ordinary six-degree-of-freedom rigid-body dynamic model to the dynamic model with an inner-loop attitude controller. The results show that the trajectory planning process can be solved by the mature SQP algorithm easily. Finally, the discussion and analysis of the real-time per- formance of the hierarchic optimization strategy are presented around the group number of the wav^oints and the eoual interval time.