Direct method to solve linear-quadratic optimal control problems

IF 1.1 Q2 MATHEMATICS, APPLIED
M. Aliane, Mohand Bentobache, N. Moussouni, P. Marthon
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引用次数: 3

Abstract

In this work, we have proposed a new approach for solving the linear-quadratic optimal control problem, where the quality criterion is a quadratic function, which can be convex or non-convex. In this approach, we transform the continuous optimal control problem into a quadratic optimization problem using the Cauchy discretization technique, then we solve it with the active-set method. In order to study the efficiency and the accuracy of the proposed approach, we developed an implementation with MATLAB, and we performed numerical experiments on several convex and non-convex linear-quadratic optimal control problems. The obtained simulation results show that our method is more accurate and more efficient than the method using the classical Euler discretization technique. Furthermore, it was shown that our method fastly converges to the optimal control of the continuous problem found analytically using the Pontryagin's maximum principle.
直接法求解线性二次最优控制问题
在这项工作中,我们提出了一种新的方法来解决线性二次最优控制问题,其中质量准则是一个二次函数,它可以是凸的或非凸的。该方法首先利用柯西离散化技术将连续最优控制问题转化为二次优化问题,然后利用活动集方法求解。为了研究该方法的效率和精度,我们开发了MATLAB实现,并对几个凸和非凸线性二次最优控制问题进行了数值实验。仿真结果表明,该方法比传统的欧拉离散化方法具有更高的精度和效率。进一步证明了该方法能快速收敛到用庞特里亚金极大值原理解析得到的连续问题的最优控制。
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来源期刊
CiteScore
3.10
自引率
0.00%
发文量
62
期刊介绍: Numerical Algebra, Control and Optimization (NACO) aims at publishing original papers on any non-trivial interplay between control and optimization, and numerical techniques for their underlying linear and nonlinear algebraic systems. Topics of interest to NACO include the following: original research in theory, algorithms and applications of optimization; numerical methods for linear and nonlinear algebraic systems arising in modelling, control and optimisation; and original theoretical and applied research and development in the control of systems including all facets of control theory and its applications. In the application areas, special interests are on artificial intelligence and data sciences. The journal also welcomes expository submissions on subjects of current relevance to readers of the journal. The publication of papers in NACO is free of charge.
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