scholarly journals Displaced Electric Sail Orbits Design and Transition Trajectory Optimization

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Naiming Qi ◽  
Mingying Huo ◽  
Qiufan Yuan
Keyword(s):  
Genetic Algorithm ◽  
Trajectory Optimization ◽  
Pseudospectral Method ◽  
Optimal Solution ◽  
Optimization Method ◽  
Solar Sails ◽  
Spherical Coordinate ◽  
Gauss Pseudospectral Method ◽  
Displaced Orbit ◽  
And Control

Displaced orbits for spacecraft propelled by electric sails are investigated as an alternative to the use of solar sails. The orbital dynamics of electric sails based spacecraft are studied within a spherical coordinate system, which permits finding the solutions of displaced electric sail orbits and optimize transfer trajectory. Transfer trajectories from Earth's orbit to displaced orbit are also studied in an optimal framework, by using genetic algorithm and Gauss pseudospectral method. The initial guesses for the state and control histories used in the Gauss pseudospectral method are interpolated from the best solution of a genetic algorithm. Numerical simulations show that the electric sail is able to perform the transfer from Earth’s orbit to displaced orbit in acceptable time, and the hybrid optimization method has the capability to search the feasible and optimal solution without any initial value guess.

scholarly journals Punching trajectory optimization method for warp-knitted vamp based on improved ant colony optimization algorithm and Radau pseudospectral method

2021 ◽  
Vol 16 ◽  
pp. 155892502110591
Author(s):  
Chi Xinfu ◽  
Li Qiyang ◽  
Zhang Xiaowei ◽  
Sun Yize
Keyword(s):  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
Trajectory Optimization ◽  
Pseudospectral Method ◽  
Optimal Solution ◽  
Optimization Method ◽  
Feedback Mechanism ◽  
Ant Colony ◽  
Ant Colony Optimization Algorithm ◽  
Low Efficiency

Aiming at the problems of complex trajectory, low efficiency and high operational difficulty of the robot in multi-point punching of warp-knitted vamp, a method of optimizing punching trajectory based on improved ant colony optimization algorithm and Radau pseudospectral method is proposed. After obtaining the position coordinates of punching points, an improved ant colony optimization algorithm is used to calculate the punching sequence of the shortest path through all punching points, and then Radau pseudospectral method is used to solve the optimal trajectory of the laser punching robot. Improved ant colony optimization algorithm combines a distributed calculation method and the positive feedback mechanism. Radau pseudospectral method can transform the optimal control problems into nonlinear programming problems, and the combination of the two can quickly and reliably obtain the optimal solution. To verify the method, under the condition of selecting the same number and location of punching points, the experiments of Radau pseudospectral method to solve the trajectory planning of laser punching robot is carried out. The experimental results show that improved ant colony optimization algorithm can calculate the path of the vamp punching point in a shorter time and with high accuracy. Radau pseudospectral method can obtain smooth trajectories satisfying various constraints, which can meet the requirements of accuracy and efficiency in practical production.

Reentry Trajectory Optimization of Airbreathing Hypersonic Vehicles Based on Gauss Pseudospectral Method

2011 ◽  
Vol 383-390 ◽  
pp. 7375-7380 ◽  
Author(s):  
Bo Yang ◽  
Shang Sun
Keyword(s):  
Trajectory Optimization ◽  
Optimization Problems ◽  
Kinetic Equations ◽  
Pseudospectral Method ◽  
Hypersonic Vehicles ◽  
Gauss Pseudospectral Method ◽  
Suboptimal Solution ◽  
Reentry Trajectory ◽  
Reentry Trajectory Optimization ◽  
And Control

According to the nonlinear, multivariable and multi-constraint features of the reentry trajectory optimization problem of airbreathing hypersonic vehicles, a suboptimal solution method is developed. The reentry trajectory generation is converted to a nonlinear programming (NLP) problem by using Gauss pseudospectral method (GPM). The state and control variables on Gauss nodes are chosen as parameters to be optimized and the minimum total heat absorption is chosen as the optimal performance index. Then the sequential quadratic programming (SQP) method is used to solve the NLP problem. The states of optimized trajectory are compared with the states obtained by the integral of kinetic equations. By simulating on an example of airbreathing hypersonic vehicles, it is demonstrated that the above method is not sensitive to the estimate of motion states and is easier to converge. And the method is effective to solve trajectory optimization problems.

Multi-Objective Trajectory Optimization of Free-Floating Space Manipulator Using NSGA-II

2015 ◽  
Vol 713-715 ◽  
pp. 800-804 ◽  
Author(s):  
Gang Chen ◽  
Cong Wei ◽  
Qing Xuan Jia ◽  
Han Xu Sun ◽  
Bo Yang Yu
Keyword(s):  
Trajectory Optimization ◽  
Interpolation Method ◽  
Optimal Solution ◽  
Optimization Method ◽  
Joint Space ◽  
Motion Path ◽  
Objective Functions ◽  
Nsga Ii ◽  
Space Manipulator ◽  
Multi Objective

In this paper, a kind of multi-objective trajectory optimization method based on non-dominated sorting genetic algorithm II (NSGA-II) is proposed for free-floating space manipulator. The aim is to optimize the motion path of the space manipulator with joint angle constraints and joint velocity constraints. Firstly, the kinematics and dynamics model are built. Secondly, the 3-5-3 piecewise polynomial is selected as interpolation method for trajectory planning of joint space. Thirdly, three objective functions are established to simultaneously minimize execution time, energy consumption and jerk of the joints. At last, the objective functions are combined with the NSGA-II algorithm to get the Pareto optimal solution set. The effectiveness of the mentioned method is verified by simulations.

The Applications of Improved Genetic Algorithm on Hypersonic Vehicle Trajectory Optimization

2012 ◽  
Vol 466-467 ◽  
pp. 1095-1099
Author(s):  
Liu Xu ◽  
Wei Min Li ◽  
Lin Zhang ◽  
An Tang Zhang
Keyword(s):  
Genetic Algorithm ◽  
Trajectory Optimization ◽  
Optimal Trajectory ◽  
Optimal Solution ◽  
High Sensitivity ◽  
Initial Guess ◽  
Cruise Missile ◽  
Trajectory Design ◽  
Improved Genetic Algorithm ◽  
Vehicle Trajectory

The Optimal trajectory design for hypersonic cruise missile is an optimal control problem with strict terminal constraints and variable final time. The classical algorithms always encounter the problems of high sensitivity to initial guess and local convergence in solving this problem. Aiming at these problems, genetic algorithm (GA) which is of good global convergence is applied to designing the optimal trajectory for hypersonic cruise missile. In order to improve the convergence rate of GA and overcome its premature problems, this text introduces a predatory search (PS) strategy to speed the convergence of genetic algorithms, robust and closer to the optimal solution. This text compares the original genetic algorithm (GA) and improved genetic algorithm by the emulate experiments, and the results show that the PSGA is a more effective method to design the Optimal trajectory for hypersonic cruise missile than the original genetic algorithm.

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