“…These methods are popular and well described (Fletcher 1987;Nocedal and Wright 2006). In literature, we can find several gradient-based algorithms (such as PostOptimality (Braun et al 1993), System Sensitivity Analysis (Olds 1994), Local Distributed Criteria (Filatyev et al 2009)) which present some interest in a MDO framework.…”
Section: Gradient-based Algorithmsmentioning
confidence: 99%
“…Indirect methods (Pontryagin Maximum Principle) are used in Perrot (2003) and in the LDC method (Filatyev and Golikov 2008;Filatyev et al 2009) to solve the trajectory optimization problem. In indirect methods, an adjoint vector x is used to indirectly optimize the control law.…”
Section: Optimal Control Handlingmentioning
confidence: 99%
“…These informations (adjoint vector and sensibility of the objective with regard to the parameters) could be exploited in the global optimization process (the optimality conditions would be integrated to the system-level equality constraints h = 0), in order to change the design parameters z and the state variables x. These considerations could improve the efficiency of the optimization process (like in the LDC method (Filatyev and Golikov 2008;Filatyev et al 2009)).…”
Section: Trajectory Optimization In the Design Processmentioning
“…These methods are popular and well described (Fletcher 1987;Nocedal and Wright 2006). In literature, we can find several gradient-based algorithms (such as PostOptimality (Braun et al 1993), System Sensitivity Analysis (Olds 1994), Local Distributed Criteria (Filatyev et al 2009)) which present some interest in a MDO framework.…”
Section: Gradient-based Algorithmsmentioning
confidence: 99%
“…Indirect methods (Pontryagin Maximum Principle) are used in Perrot (2003) and in the LDC method (Filatyev and Golikov 2008;Filatyev et al 2009) to solve the trajectory optimization problem. In indirect methods, an adjoint vector x is used to indirectly optimize the control law.…”
Section: Optimal Control Handlingmentioning
confidence: 99%
“…These informations (adjoint vector and sensibility of the objective with regard to the parameters) could be exploited in the global optimization process (the optimality conditions would be integrated to the system-level equality constraints h = 0), in order to change the design parameters z and the state variables x. These considerations could improve the efficiency of the optimization process (like in the LDC method (Filatyev and Golikov 2008;Filatyev et al 2009)).…”
Section: Trajectory Optimization In the Design Processmentioning
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