The Experts below are selected from a list of 9690 Experts worldwide ranked by ideXlab platform
Yuanqing Xia - One of the best experts on this subject based on the ideXlab platform.
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stochastic Spacecraft Trajectory optimization with the consideration of chance constraints
IEEE Transactions on Control Systems and Technology, 2020Co-Authors: Runqi Chai, Al Savvaris, Senchun Chai, Antonios Tsourdos, Yuanqing XiaAbstract:This brief investigates a computational framework based on optimal control for addressing the problem of stochastic Trajectory optimization with the consideration of chance constraints. This design employs a discretization technique to parameterize uncertain variables and create the Trajectory ensemble. Subsequently, the resulting discretized version of the problem is solved by applying standard optimal control solvers. In order to provide reliable gradient information to the optimization algorithm, a smooth and differentiable chance-constraint approximation method is proposed to replace the original probability constraints. The established methodology is implemented to explore the optimal trajectories for a Spacecraft entry flight planning scenario with noise-perturbed dynamics and probabilistic constraints. Simulation results and comparative studies demonstrate that the present chance-constraint handling strategy can outperform other existing approaches analyzed in this brief, and this computational framework can produce reliable and less conservative solutions for the chance-constrained stochastic Spacecraft Trajectory planning problem.
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a review of optimization techniques in Spacecraft flight Trajectory design
Progress in Aerospace Sciences, 2019Co-Authors: Runqi Chai, Al Savvaris, Senchun Chai, Antonios Tsourdos, Yuanqing XiaAbstract:Abstract For most atmospheric or exo-atmospheric Spacecraft flight scenarios, a well-designed Trajectory is usually a key for stable flight and for improved guidance and control of the vehicle. Although extensive research work has been carried out on the design of Spacecraft trajectories for different mission profiles and many effective tools were successfully developed for optimizing the flight path, it is only in the recent five years that there has been a growing interest in planning the flight trajectories with the consideration of multiple mission objectives and various model errors/uncertainties. It is worth noting that in many practical Spacecraft guidance, navigation and control systems, multiple performance indices and different types of uncertainties must frequently be considered during the path planning phase. As a result, these requirements bring the development of multi-objective Spacecraft Trajectory optimization methods as well as stochastic Spacecraft Trajectory optimization algorithms. This paper aims to broadly review the state-of-the-art development in numerical multi-objective Trajectory optimization algorithms and stochastic Trajectory planning techniques for Spacecraft flight operations. A brief description of the mathematical formulation of the problem is firstly introduced. Following that, various optimization methods that can be effective for solving Spacecraft Trajectory planning problems are reviewed, including the gradient-based methods, the convexification-based methods, and the evolutionary/metaheuristic methods. The multi-objective Spacecraft Trajectory optimization formulation, together with different class of multi-objective optimization algorithms, is then overviewed. The key features such as the advantages and disadvantages of these recently-developed multi-objective techniques are summarised. Moreover, attentions are given to extend the original deterministic problem to a stochastic version. Some robust optimization strategies are also outlined to deal with the stochastic Trajectory planning formulation. In addition, a special focus will be given on the recent applications of the optimized Trajectory. Finally, some conclusions are drawn and future research on the development of multi-objective and stochastic Trajectory optimization techniques is discussed.
Runqi Chai - One of the best experts on this subject based on the ideXlab platform.
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stochastic Spacecraft Trajectory optimization with the consideration of chance constraints
IEEE Transactions on Control Systems and Technology, 2020Co-Authors: Runqi Chai, Al Savvaris, Senchun Chai, Antonios Tsourdos, Yuanqing XiaAbstract:This brief investigates a computational framework based on optimal control for addressing the problem of stochastic Trajectory optimization with the consideration of chance constraints. This design employs a discretization technique to parameterize uncertain variables and create the Trajectory ensemble. Subsequently, the resulting discretized version of the problem is solved by applying standard optimal control solvers. In order to provide reliable gradient information to the optimization algorithm, a smooth and differentiable chance-constraint approximation method is proposed to replace the original probability constraints. The established methodology is implemented to explore the optimal trajectories for a Spacecraft entry flight planning scenario with noise-perturbed dynamics and probabilistic constraints. Simulation results and comparative studies demonstrate that the present chance-constraint handling strategy can outperform other existing approaches analyzed in this brief, and this computational framework can produce reliable and less conservative solutions for the chance-constrained stochastic Spacecraft Trajectory planning problem.
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Stochastic Trajectory Optimization Problems with Chance Constraints
Design of Trajectory Optimization Approach for Space Maneuver Vehicle Skip Entry Problems, 2020Co-Authors: Runqi Chai, Al Savvaris, Antonios Tsourdos, Senchun ChaiAbstract:This chapter investigates a computational framework based on optimal control for addressing the problem of stochastic Trajectory optimization with the consideration of chance constraints. This design employs a discretization technique to parametrize uncertain variables and create the Trajectory ensemble. Subsequently, the resulting discretized version of the problem is solved by applying standard optimal control solvers. In order to provide reliable gradient information to the optimization algorithm, a smooth and differentiable chance-constraint approximation method is proposed to replace the original probability constraints. The established methodology is implemented to explore the optimal trajectories for a Spacecraft entry flight planning scenario with noise-perturbed dynamics and probabilistic constraints. Simulation results and comparative studies demonstrate that the present chance-constraint-handling strategy can outperform other existing approaches analyzed in this study, and the developed computational framework can produce reliable and less conservative solutions for the chance-constrained stochastic Spacecraft Trajectory planning problem. We hope that by reading this section, readers can gain a better understanding in terms of the definitions, solution approaches, and current challenges of the stochastic Spacecraft Trajectory design problems.
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Overview of Trajectory Optimization Techniques
Design of Trajectory Optimization Approach for Space Maneuver Vehicle Skip Entry Problems, 2020Co-Authors: Runqi Chai, Al Savvaris, Antonios Tsourdos, Senchun ChaiAbstract:This chapter aims to broadly review the state-of-the-art development in Spacecraft Trajectory optimization problems and optimal control methods. Specifically, the main focus will be on the recently proposed optimization methods that have been utilized in constrained Trajectory optimization problems and multi-objective Trajectory optimization problems. An overview regarding the development of optimal control methods is first introduced. Following that, various optimization methods that can be effective for solving Spacecraft Trajectory planning problems are reviewed, including the gradient-based methods, the convexification-based methods, the evolutionary/metaheuristic methods, and the dynamic programming-based methods. In addition, a special focus will be given on the recent applications of the optimized Trajectory. Finally, the multi-objective Spacecraft Trajectory optimization problem, together with different classes of multi-objective optimization algorithms, is briefly outlined at the end of the chapter.
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a review of optimization techniques in Spacecraft flight Trajectory design
Progress in Aerospace Sciences, 2019Co-Authors: Runqi Chai, Al Savvaris, Senchun Chai, Antonios Tsourdos, Yuanqing XiaAbstract:Abstract For most atmospheric or exo-atmospheric Spacecraft flight scenarios, a well-designed Trajectory is usually a key for stable flight and for improved guidance and control of the vehicle. Although extensive research work has been carried out on the design of Spacecraft trajectories for different mission profiles and many effective tools were successfully developed for optimizing the flight path, it is only in the recent five years that there has been a growing interest in planning the flight trajectories with the consideration of multiple mission objectives and various model errors/uncertainties. It is worth noting that in many practical Spacecraft guidance, navigation and control systems, multiple performance indices and different types of uncertainties must frequently be considered during the path planning phase. As a result, these requirements bring the development of multi-objective Spacecraft Trajectory optimization methods as well as stochastic Spacecraft Trajectory optimization algorithms. This paper aims to broadly review the state-of-the-art development in numerical multi-objective Trajectory optimization algorithms and stochastic Trajectory planning techniques for Spacecraft flight operations. A brief description of the mathematical formulation of the problem is firstly introduced. Following that, various optimization methods that can be effective for solving Spacecraft Trajectory planning problems are reviewed, including the gradient-based methods, the convexification-based methods, and the evolutionary/metaheuristic methods. The multi-objective Spacecraft Trajectory optimization formulation, together with different class of multi-objective optimization algorithms, is then overviewed. The key features such as the advantages and disadvantages of these recently-developed multi-objective techniques are summarised. Moreover, attentions are given to extend the original deterministic problem to a stochastic version. Some robust optimization strategies are also outlined to deal with the stochastic Trajectory planning formulation. In addition, a special focus will be given on the recent applications of the optimized Trajectory. Finally, some conclusions are drawn and future research on the development of multi-objective and stochastic Trajectory optimization techniques is discussed.
Senchun Chai - One of the best experts on this subject based on the ideXlab platform.
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stochastic Spacecraft Trajectory optimization with the consideration of chance constraints
IEEE Transactions on Control Systems and Technology, 2020Co-Authors: Runqi Chai, Al Savvaris, Senchun Chai, Antonios Tsourdos, Yuanqing XiaAbstract:This brief investigates a computational framework based on optimal control for addressing the problem of stochastic Trajectory optimization with the consideration of chance constraints. This design employs a discretization technique to parameterize uncertain variables and create the Trajectory ensemble. Subsequently, the resulting discretized version of the problem is solved by applying standard optimal control solvers. In order to provide reliable gradient information to the optimization algorithm, a smooth and differentiable chance-constraint approximation method is proposed to replace the original probability constraints. The established methodology is implemented to explore the optimal trajectories for a Spacecraft entry flight planning scenario with noise-perturbed dynamics and probabilistic constraints. Simulation results and comparative studies demonstrate that the present chance-constraint handling strategy can outperform other existing approaches analyzed in this brief, and this computational framework can produce reliable and less conservative solutions for the chance-constrained stochastic Spacecraft Trajectory planning problem.
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Stochastic Trajectory Optimization Problems with Chance Constraints
Design of Trajectory Optimization Approach for Space Maneuver Vehicle Skip Entry Problems, 2020Co-Authors: Runqi Chai, Al Savvaris, Antonios Tsourdos, Senchun ChaiAbstract:This chapter investigates a computational framework based on optimal control for addressing the problem of stochastic Trajectory optimization with the consideration of chance constraints. This design employs a discretization technique to parametrize uncertain variables and create the Trajectory ensemble. Subsequently, the resulting discretized version of the problem is solved by applying standard optimal control solvers. In order to provide reliable gradient information to the optimization algorithm, a smooth and differentiable chance-constraint approximation method is proposed to replace the original probability constraints. The established methodology is implemented to explore the optimal trajectories for a Spacecraft entry flight planning scenario with noise-perturbed dynamics and probabilistic constraints. Simulation results and comparative studies demonstrate that the present chance-constraint-handling strategy can outperform other existing approaches analyzed in this study, and the developed computational framework can produce reliable and less conservative solutions for the chance-constrained stochastic Spacecraft Trajectory planning problem. We hope that by reading this section, readers can gain a better understanding in terms of the definitions, solution approaches, and current challenges of the stochastic Spacecraft Trajectory design problems.
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Overview of Trajectory Optimization Techniques
Design of Trajectory Optimization Approach for Space Maneuver Vehicle Skip Entry Problems, 2020Co-Authors: Runqi Chai, Al Savvaris, Antonios Tsourdos, Senchun ChaiAbstract:This chapter aims to broadly review the state-of-the-art development in Spacecraft Trajectory optimization problems and optimal control methods. Specifically, the main focus will be on the recently proposed optimization methods that have been utilized in constrained Trajectory optimization problems and multi-objective Trajectory optimization problems. An overview regarding the development of optimal control methods is first introduced. Following that, various optimization methods that can be effective for solving Spacecraft Trajectory planning problems are reviewed, including the gradient-based methods, the convexification-based methods, the evolutionary/metaheuristic methods, and the dynamic programming-based methods. In addition, a special focus will be given on the recent applications of the optimized Trajectory. Finally, the multi-objective Spacecraft Trajectory optimization problem, together with different classes of multi-objective optimization algorithms, is briefly outlined at the end of the chapter.
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a review of optimization techniques in Spacecraft flight Trajectory design
Progress in Aerospace Sciences, 2019Co-Authors: Runqi Chai, Al Savvaris, Senchun Chai, Antonios Tsourdos, Yuanqing XiaAbstract:Abstract For most atmospheric or exo-atmospheric Spacecraft flight scenarios, a well-designed Trajectory is usually a key for stable flight and for improved guidance and control of the vehicle. Although extensive research work has been carried out on the design of Spacecraft trajectories for different mission profiles and many effective tools were successfully developed for optimizing the flight path, it is only in the recent five years that there has been a growing interest in planning the flight trajectories with the consideration of multiple mission objectives and various model errors/uncertainties. It is worth noting that in many practical Spacecraft guidance, navigation and control systems, multiple performance indices and different types of uncertainties must frequently be considered during the path planning phase. As a result, these requirements bring the development of multi-objective Spacecraft Trajectory optimization methods as well as stochastic Spacecraft Trajectory optimization algorithms. This paper aims to broadly review the state-of-the-art development in numerical multi-objective Trajectory optimization algorithms and stochastic Trajectory planning techniques for Spacecraft flight operations. A brief description of the mathematical formulation of the problem is firstly introduced. Following that, various optimization methods that can be effective for solving Spacecraft Trajectory planning problems are reviewed, including the gradient-based methods, the convexification-based methods, and the evolutionary/metaheuristic methods. The multi-objective Spacecraft Trajectory optimization formulation, together with different class of multi-objective optimization algorithms, is then overviewed. The key features such as the advantages and disadvantages of these recently-developed multi-objective techniques are summarised. Moreover, attentions are given to extend the original deterministic problem to a stochastic version. Some robust optimization strategies are also outlined to deal with the stochastic Trajectory planning formulation. In addition, a special focus will be given on the recent applications of the optimized Trajectory. Finally, some conclusions are drawn and future research on the development of multi-objective and stochastic Trajectory optimization techniques is discussed.
Antonios Tsourdos - One of the best experts on this subject based on the ideXlab platform.
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stochastic Spacecraft Trajectory optimization with the consideration of chance constraints
IEEE Transactions on Control Systems and Technology, 2020Co-Authors: Runqi Chai, Al Savvaris, Senchun Chai, Antonios Tsourdos, Yuanqing XiaAbstract:This brief investigates a computational framework based on optimal control for addressing the problem of stochastic Trajectory optimization with the consideration of chance constraints. This design employs a discretization technique to parameterize uncertain variables and create the Trajectory ensemble. Subsequently, the resulting discretized version of the problem is solved by applying standard optimal control solvers. In order to provide reliable gradient information to the optimization algorithm, a smooth and differentiable chance-constraint approximation method is proposed to replace the original probability constraints. The established methodology is implemented to explore the optimal trajectories for a Spacecraft entry flight planning scenario with noise-perturbed dynamics and probabilistic constraints. Simulation results and comparative studies demonstrate that the present chance-constraint handling strategy can outperform other existing approaches analyzed in this brief, and this computational framework can produce reliable and less conservative solutions for the chance-constrained stochastic Spacecraft Trajectory planning problem.
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Stochastic Trajectory Optimization Problems with Chance Constraints
Design of Trajectory Optimization Approach for Space Maneuver Vehicle Skip Entry Problems, 2020Co-Authors: Runqi Chai, Al Savvaris, Antonios Tsourdos, Senchun ChaiAbstract:This chapter investigates a computational framework based on optimal control for addressing the problem of stochastic Trajectory optimization with the consideration of chance constraints. This design employs a discretization technique to parametrize uncertain variables and create the Trajectory ensemble. Subsequently, the resulting discretized version of the problem is solved by applying standard optimal control solvers. In order to provide reliable gradient information to the optimization algorithm, a smooth and differentiable chance-constraint approximation method is proposed to replace the original probability constraints. The established methodology is implemented to explore the optimal trajectories for a Spacecraft entry flight planning scenario with noise-perturbed dynamics and probabilistic constraints. Simulation results and comparative studies demonstrate that the present chance-constraint-handling strategy can outperform other existing approaches analyzed in this study, and the developed computational framework can produce reliable and less conservative solutions for the chance-constrained stochastic Spacecraft Trajectory planning problem. We hope that by reading this section, readers can gain a better understanding in terms of the definitions, solution approaches, and current challenges of the stochastic Spacecraft Trajectory design problems.
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Overview of Trajectory Optimization Techniques
Design of Trajectory Optimization Approach for Space Maneuver Vehicle Skip Entry Problems, 2020Co-Authors: Runqi Chai, Al Savvaris, Antonios Tsourdos, Senchun ChaiAbstract:This chapter aims to broadly review the state-of-the-art development in Spacecraft Trajectory optimization problems and optimal control methods. Specifically, the main focus will be on the recently proposed optimization methods that have been utilized in constrained Trajectory optimization problems and multi-objective Trajectory optimization problems. An overview regarding the development of optimal control methods is first introduced. Following that, various optimization methods that can be effective for solving Spacecraft Trajectory planning problems are reviewed, including the gradient-based methods, the convexification-based methods, the evolutionary/metaheuristic methods, and the dynamic programming-based methods. In addition, a special focus will be given on the recent applications of the optimized Trajectory. Finally, the multi-objective Spacecraft Trajectory optimization problem, together with different classes of multi-objective optimization algorithms, is briefly outlined at the end of the chapter.
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a review of optimization techniques in Spacecraft flight Trajectory design
Progress in Aerospace Sciences, 2019Co-Authors: Runqi Chai, Al Savvaris, Senchun Chai, Antonios Tsourdos, Yuanqing XiaAbstract:Abstract For most atmospheric or exo-atmospheric Spacecraft flight scenarios, a well-designed Trajectory is usually a key for stable flight and for improved guidance and control of the vehicle. Although extensive research work has been carried out on the design of Spacecraft trajectories for different mission profiles and many effective tools were successfully developed for optimizing the flight path, it is only in the recent five years that there has been a growing interest in planning the flight trajectories with the consideration of multiple mission objectives and various model errors/uncertainties. It is worth noting that in many practical Spacecraft guidance, navigation and control systems, multiple performance indices and different types of uncertainties must frequently be considered during the path planning phase. As a result, these requirements bring the development of multi-objective Spacecraft Trajectory optimization methods as well as stochastic Spacecraft Trajectory optimization algorithms. This paper aims to broadly review the state-of-the-art development in numerical multi-objective Trajectory optimization algorithms and stochastic Trajectory planning techniques for Spacecraft flight operations. A brief description of the mathematical formulation of the problem is firstly introduced. Following that, various optimization methods that can be effective for solving Spacecraft Trajectory planning problems are reviewed, including the gradient-based methods, the convexification-based methods, and the evolutionary/metaheuristic methods. The multi-objective Spacecraft Trajectory optimization formulation, together with different class of multi-objective optimization algorithms, is then overviewed. The key features such as the advantages and disadvantages of these recently-developed multi-objective techniques are summarised. Moreover, attentions are given to extend the original deterministic problem to a stochastic version. Some robust optimization strategies are also outlined to deal with the stochastic Trajectory planning formulation. In addition, a special focus will be given on the recent applications of the optimized Trajectory. Finally, some conclusions are drawn and future research on the development of multi-objective and stochastic Trajectory optimization techniques is discussed.
Al Savvaris - One of the best experts on this subject based on the ideXlab platform.
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stochastic Spacecraft Trajectory optimization with the consideration of chance constraints
IEEE Transactions on Control Systems and Technology, 2020Co-Authors: Runqi Chai, Al Savvaris, Senchun Chai, Antonios Tsourdos, Yuanqing XiaAbstract:This brief investigates a computational framework based on optimal control for addressing the problem of stochastic Trajectory optimization with the consideration of chance constraints. This design employs a discretization technique to parameterize uncertain variables and create the Trajectory ensemble. Subsequently, the resulting discretized version of the problem is solved by applying standard optimal control solvers. In order to provide reliable gradient information to the optimization algorithm, a smooth and differentiable chance-constraint approximation method is proposed to replace the original probability constraints. The established methodology is implemented to explore the optimal trajectories for a Spacecraft entry flight planning scenario with noise-perturbed dynamics and probabilistic constraints. Simulation results and comparative studies demonstrate that the present chance-constraint handling strategy can outperform other existing approaches analyzed in this brief, and this computational framework can produce reliable and less conservative solutions for the chance-constrained stochastic Spacecraft Trajectory planning problem.
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Stochastic Trajectory Optimization Problems with Chance Constraints
Design of Trajectory Optimization Approach for Space Maneuver Vehicle Skip Entry Problems, 2020Co-Authors: Runqi Chai, Al Savvaris, Antonios Tsourdos, Senchun ChaiAbstract:This chapter investigates a computational framework based on optimal control for addressing the problem of stochastic Trajectory optimization with the consideration of chance constraints. This design employs a discretization technique to parametrize uncertain variables and create the Trajectory ensemble. Subsequently, the resulting discretized version of the problem is solved by applying standard optimal control solvers. In order to provide reliable gradient information to the optimization algorithm, a smooth and differentiable chance-constraint approximation method is proposed to replace the original probability constraints. The established methodology is implemented to explore the optimal trajectories for a Spacecraft entry flight planning scenario with noise-perturbed dynamics and probabilistic constraints. Simulation results and comparative studies demonstrate that the present chance-constraint-handling strategy can outperform other existing approaches analyzed in this study, and the developed computational framework can produce reliable and less conservative solutions for the chance-constrained stochastic Spacecraft Trajectory planning problem. We hope that by reading this section, readers can gain a better understanding in terms of the definitions, solution approaches, and current challenges of the stochastic Spacecraft Trajectory design problems.
-
Overview of Trajectory Optimization Techniques
Design of Trajectory Optimization Approach for Space Maneuver Vehicle Skip Entry Problems, 2020Co-Authors: Runqi Chai, Al Savvaris, Antonios Tsourdos, Senchun ChaiAbstract:This chapter aims to broadly review the state-of-the-art development in Spacecraft Trajectory optimization problems and optimal control methods. Specifically, the main focus will be on the recently proposed optimization methods that have been utilized in constrained Trajectory optimization problems and multi-objective Trajectory optimization problems. An overview regarding the development of optimal control methods is first introduced. Following that, various optimization methods that can be effective for solving Spacecraft Trajectory planning problems are reviewed, including the gradient-based methods, the convexification-based methods, the evolutionary/metaheuristic methods, and the dynamic programming-based methods. In addition, a special focus will be given on the recent applications of the optimized Trajectory. Finally, the multi-objective Spacecraft Trajectory optimization problem, together with different classes of multi-objective optimization algorithms, is briefly outlined at the end of the chapter.
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a review of optimization techniques in Spacecraft flight Trajectory design
Progress in Aerospace Sciences, 2019Co-Authors: Runqi Chai, Al Savvaris, Senchun Chai, Antonios Tsourdos, Yuanqing XiaAbstract:Abstract For most atmospheric or exo-atmospheric Spacecraft flight scenarios, a well-designed Trajectory is usually a key for stable flight and for improved guidance and control of the vehicle. Although extensive research work has been carried out on the design of Spacecraft trajectories for different mission profiles and many effective tools were successfully developed for optimizing the flight path, it is only in the recent five years that there has been a growing interest in planning the flight trajectories with the consideration of multiple mission objectives and various model errors/uncertainties. It is worth noting that in many practical Spacecraft guidance, navigation and control systems, multiple performance indices and different types of uncertainties must frequently be considered during the path planning phase. As a result, these requirements bring the development of multi-objective Spacecraft Trajectory optimization methods as well as stochastic Spacecraft Trajectory optimization algorithms. This paper aims to broadly review the state-of-the-art development in numerical multi-objective Trajectory optimization algorithms and stochastic Trajectory planning techniques for Spacecraft flight operations. A brief description of the mathematical formulation of the problem is firstly introduced. Following that, various optimization methods that can be effective for solving Spacecraft Trajectory planning problems are reviewed, including the gradient-based methods, the convexification-based methods, and the evolutionary/metaheuristic methods. The multi-objective Spacecraft Trajectory optimization formulation, together with different class of multi-objective optimization algorithms, is then overviewed. The key features such as the advantages and disadvantages of these recently-developed multi-objective techniques are summarised. Moreover, attentions are given to extend the original deterministic problem to a stochastic version. Some robust optimization strategies are also outlined to deal with the stochastic Trajectory planning formulation. In addition, a special focus will be given on the recent applications of the optimized Trajectory. Finally, some conclusions are drawn and future research on the development of multi-objective and stochastic Trajectory optimization techniques is discussed.