کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8051758 | 1519375 | 2018 | 40 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A sequential computational approach to optimal control problems for differential-algebraic systems based on efficient implicit Runge-Kutta integration
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مکانیک محاسباتی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: A sequential computational approach to optimal control problems for differential-algebraic systems based on efficient implicit Runge-Kutta integration A sequential computational approach to optimal control problems for differential-algebraic systems based on efficient implicit Runge-Kutta integration](/preview/png/8051758.png)
چکیده انگلیسی
Efficient and reliable integrators are indispensable for the design of sequential solvers for optimal control problems involving continuous dynamics, especially for real-time applications. In this paper, optimal control problems for systems represented by index-1 differential-algebraic equations are investigated. On the basis of a time-scaling transformation, the control is parameterized as a piecewise constant function with variable heights and switching time instants. Compared with control parameterization with fixed time grids, the flexibility of adjusting switching time instants increases the chance of finding the optimal solution. Furthermore, error constraints are introduced in the optimization procedure such that the optimal control obtained has a guarantee of integration accuracy. For the derived approximate nonlinear programming problem, a function evaluation and forward sensitivity propagation algorithm is proposed with an embedded implicit Runge-Kutta integrator, which executes one Newton iteration in the limit by employing a predictor-corrector strategy. This algorithm is combined with a nonlinear programming solver Ipopt to construct the optimal control solver. Numerical experiments for the solution of the optimal control problem for a Delta robot demonstrate that the computational speed of this solver is increased by a factor of 0.5-2 when compared with the same solver without the predictor-corrector strategy, and increased by a factor of 20-40 when compared with solver embedding IDAS, the Implicit Differential-Algebraic solver with Sensitivity capabilities developed by Lawrence Livermore National Laboratory. Meanwhile, the accuracy loss compared with the one using IDAS is small and admissible.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Applied Mathematical Modelling - Volume 58, June 2018, Pages 313-330
Journal: Applied Mathematical Modelling - Volume 58, June 2018, Pages 313-330
نویسندگان
Canghua Jiang, Kun Xie, Changjun Yu, Ming Yu, Hai Wang, Yigang He, Kok Lay Teo,