Genetic Algorithm and Indirect Method Coupling for Low-Thrust Trajectory Optimization

Sentinella, Matteo Rosa; Casalino, Lorenzo

doi:10.2514/6.2006-4468

Cited by 21 publications

(14 citation statements)

References 9 publications

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“…This boundary values problem is solved by specific numerical techniques such as shooting or relaxation methods. This method is widely used as a powerful and efficient tool in analyzing the nonlinear system and path planning of different types of systems [29][30][31][32][33]. An indirect method is a good candidate for the cases where the system has a large number of degrees of freedom or optimization of the various objectives is targeted [31,32],.…”

Section: Control Of Robotmentioning

confidence: 99%

Nonlinear dynamic analysis for elastic robotic arms

Korayem

Rahimi

2011

Front. Mech. Eng.

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The aim of the paper is to analyze the nonlinear dynamics of robotic arms with elastic links and joints. The main contribution of the paper is the comparative assessment of assumed modes and finite element methods as more convenient approaches for computing the nonlinear dynamic of robotic systems. Numerical simulations comprising both methods are carried out and results are discussed. Hence, advantages and disadvantages of each method are illustrated. Then, adding the joint flexibility to the system is dealt with and the obtained model is demonstrated. Finally, a brief description of the optimal motion generation is presented and the simulation is carried out to investigate the role of robot dynamic modeling in the control of robots.

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Section: Control Of Robotmentioning

confidence: 99%

Nonlinear dynamic analysis for elastic robotic arms

Korayem

Rahimi

2011

Front. Mech. Eng.

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“…14 This method is widely used as a powerful and efficient tool in analyzing the nonlinear systems and path planning of different types of systems. [15][16][17][18] Fotouhi et al used indirect method to obtain the time optimal trajectory of a two-link manipulator, 15 Furuno et al used this technique for trajectory planning of mobile manipulators, 19 and Nikoobin et al applied this method for trajectory planning of flexible joint, 20 flexible link, 21 and redundant manipulators. 22 In ref.…”

Section: Introductionmentioning

confidence: 99%

Optimal balancing of robot manipulators in point-to-point motion

Nikoobin

Moradi

2010

Robotica

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SUMMARYIn this paper, a new balancing approach called “optimal balancing” is presented for open-chain robot manipulators based on open-loop optimal control. In fact, an optimal trajectory planning problem is outlined in which states, controls and the values of counterweights must be determined simultaneously in order to minimize the given performance index for a predefined point-to-point task. Optimal balancing method can be propounded beside the other methods such as unbalancing, static balancing and adaptive balancing, with this superiority that the objective criterion value obtained of proposed method is very lower than the objective criterion value obtained of other methods. For this purpose, the optimal control problem is extended to the case where the performance index, the differential constraints and the prescribed final conditions contain parameters. Using the fundamental theorem of calculus of variations, the necessary conditions for optimality are derived which lead to the optimality conditions associated with the Pontryagin's minimum principle and an additional condition associated with the constant parameters. By developing the obtained optimality conditions for the two-link manipulator, a two-point boundary value problem is achieved which can be solved with bvp4c command in MATLAB®. The obtained results show that optimal balancing in comparison with the previous methods can reduce the performance index significantly. This method can be easily applied to the more complicated manipulator such as a three degrees of freedom articulated manipulator.

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“…GAs have also been used with calculus of variations (Crain et al 2000;Woo et al 2006;Rosa Sentinella and Casalino 2006) for low thrust trajectories; a combination of artificial neural networks with EAs has been applied to solar sail trajectories (Dachwand and Wie 2007). An interesting application of GAs (Conway et al 2007) concerns their use in hybrid optimization problems (i.e., those problems with both continuous and categorical variables), in conjunction with other techniques.…”

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confidence: 99%

Cooperative evolutionary algorithm for space trajectory optimization

Sentinella

Casalino

2009

Celest Mech Dyn Astr

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A hybrid evolutionary algorithm which synergistically exploits differential evolution, genetic algorithms and particle swarm optimization, has been developed and applied to spacecraft trajectory optimization. The cooperative procedure runs the three basic algorithms in parallel, while letting the best individuals migrate to the other populations at prescribed intervals. Rendezvous problems and round-trip Earth-Mars missions have been considered. The results show that the hybrid algorithm has better performance compared to the basic algorithms that are employed. In particular, for the rendezvous problem, a 100% efficiency can be obtained both by differential evolution and the genetic algorithm only when particular strategies and parameter settings are adopted. On the other hand, the hybrid algorithm always attains the global optimum, even though nonoptimal strategies and parameter settings are adopted. Also the number of function evaluations, which must be performed to attain the optimum, is reduced when the hybrid algorithm is used. In the case of Earth-Mars missions, the hybrid algorithm is successfully employed to determine mission opportunities in a large search space.

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Genetic Algorithm and Indirect Method Coupling for Low-Thrust Trajectory Optimization

Cited by 21 publications

References 9 publications

Nonlinear dynamic analysis for elastic robotic arms

Nonlinear dynamic analysis for elastic robotic arms

Optimal balancing of robot manipulators in point-to-point motion

Cooperative evolutionary algorithm for space trajectory optimization

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