A new approach to trajectory optimization based on direct transcription and differential flatness

Poustini, Mohammad Javad; Esmaelzadeh, Reza; Adami, Amirhossein

doi:10.1016/j.actaastro.2014.10.018

Cited by 20 publications

(8 citation statements)

References 11 publications

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“…The feed-forward control is used to eliminate and reduce the effect of disturbance for applications that need very fast and sensitive response (Irfan and Abdurraqeeb, 2016; Kosalay and Ozkaya, 2017; Pratilastiarso et al, 2017; Sveko and Kusi, 2015; Tsai and Tsai, 2017). Differential flatness approach (Liu et al, 2017; Poustini et al, 2015) is a mathematical method that is used to calculate the required voltage to control the piezoelectric actuator (Pahlevaninezhad et al, 2012). The idea of feed-forward control using differential flatness approach is to specify the desired motion for calculating the required voltage (Shirazi et al, 2011).…”

Section: Differential Flatness Approachmentioning

confidence: 99%

Verification of the feed-forward control for a piezoelectric actuator using differential flatness approach

Alzoubi

Alboon

Alqudah

2018

Journal of Intelligent Material Systems and Structures

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In the last decade, the applications of nano- and micro-technology are widely used in many fields. In the modern mobile devices, such as digital cameras, there is an increased demand to achieve fast and precise positioning for some parts such as the recording sensor. Therefore, a smart material (piezoelectric) is used to achieve this requirement. This article discusses the feed-forward control for a piezoelectric actuator using differential flatness approach. The differential flatness approach is used to calculate the required voltage to control the piezoelectric actuator movement. The control voltage will be applied to the real actuator. The simulation and experimental results are compared for the actuator. The aim of this article is to verify the feed-forward control for second eigenfrequency using the differential flatness approach for the piezoelectric actuator.

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Section: Differential Flatness Approachmentioning

confidence: 99%

Verification of the feed-forward control for a piezoelectric actuator using differential flatness approach

Alzoubi

Alboon

Alqudah

2018

Journal of Intelligent Material Systems and Structures

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“…Poustini et al. 46 developed a reliable method to produce an optimal trajectory in the presence of all limitations and constraints based on direct transcription and differential flatness. Steffens et al.…”

Section: Introductionmentioning

confidence: 99%

A novel metamodel management strategy for robust trajectory design of an expendable launch vehicle

Roshanian

Bataleblu

2019

Proceedings of the Institution of Mechanical Engineers, Part G:

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Uncertainty-based design optimization has been widely acknowledged as an advanced methodology to address competing objectives of aerospace vehicle design, such as reliability and robustness. Despite the usefulness of uncertainty-based design optimization, the computational burden associated with uncertainty propagation and analysis process still remains a major challenge of this field of study. The metamodeling is known as the most promising methodology for significantly reducing the computational cost of the uncertainty propagation process. On the other hand, the nonlinearity of the uncertainty-based design optimization problem's design space with multiple local optima reduces the accuracy and efficiency of the metamodels prediction. In this article, a novel metamodel management strategy, which controls the evolution during the optimization process, is proposed to alleviate these difficulties. For this purpose, a combination of improved Latin hypercube sampling and artificial neural networks are involved. The proposed strategy assesses the created metamodel accuracy and decides when a metamodel needs to be replaced with the real model. The metamodeling and metamodel management strategy are conspired to propose an augmented strategy for robust design optimization problems. The proposed strategy is applied to the multiobjective robust design optimization of an expendable launch vehicle. Finally, based on non-dominated sorting genetic algorithm-II, a compromise between optimality and robustness is illustrated through the Pareto frontier. Results illustrate that the proposed strategy could improve the computational efficiency, accuracy, and globality of optimizer convergence in uncertainty-based design optimization problems.

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“…Therefore, the pseudospectral (PS) method has the advantage of high rate of convergence and large convergence radius [7][8], and provides spectral accuracy for smooth problems, but produces much denser constraints Jacobian as compared with other methods. In order to increase the sparsity of constraints Jacobians in PS method, Ross and Fahroo introduce the concepts of the knots for the Legendre PS method [9], Poustini et al develop a trajectory optimization method based on some combination of the direct optimization method and differential flatness theory [10]. Some researchers combine the PS method and heuristic optimization method to improve trajectory method [11,12], other researchers improve the adaptive mesh refinement algorithm to obtain higher accuracy solution with less computation time [6,[13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Adaptive mesh refinement method for optimal control based on Hermite-Legendre-Gauss-Lobatto direct transcription

Lei¹,

Liu²,

Deng³

et al. 2017

J. vibroeng.

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Direct transcription has been employed to transcribe the optimal control problem into a nonlinear programming problem. This paper presents a trajectory optimization method based on a combination of the direct transcription and mesh refinement algorithm. Hermite-Simpson method has the advantage of reasonable accuracy with highly sparse Hessian matrix and constraint Jacobians, and the pseudospectral method provides spectral accuracy for optimal control problems. The optimal control problem is discretized at a series of Legendre-Gauss-Lobatto points, then the trajectory states are approximated by using local Hermite interpolating polynomials. Thus, the method produces significantly smaller mesh size with a higher accuracy tolerance solution. The derived relative error estimation is then used to trade the number of mesh polynomials degree within each mesh interval with the number of mesh intervals. As a result, the suggested method can produce more small mesh size, requires less computation solution for the same optimal control problem. The simulation experiment results show that the suggested method has many advantages.

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A new approach to trajectory optimization based on direct transcription and differential flatness

Cited by 20 publications

References 11 publications

Verification of the feed-forward control for a piezoelectric actuator using differential flatness approach

Verification of the feed-forward control for a piezoelectric actuator using differential flatness approach

A novel metamodel management strategy for robust trajectory design of an expendable launch vehicle

Adaptive mesh refinement method for optimal control based on Hermite-Legendre-Gauss-Lobatto direct transcription

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