Spline-based approach to optimal control of trajectories under inequality type constraints

S. Asmuss, N. Budkina
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Abstract

The paper is devoted to an optimal trajectory planning problem considered as a problem of constrained optimal control for dynamical systems. It is one of the fundamental problems in robotics, biomechanics, aeronautics and many other areas of application of control theory. The simplest version of this problem supposes that there are given sequences of target points and prescribed times, and we are required to be at the given point at the prescribed time. However, in most of the applications, it is enough when the trajectory passes close to the assigned point at the prescribed time. So, the location conditions could be considered as the inequality type constraints. The aim of this research is to reduce such an optimal control problem to the problem of splines in convex sets, which could be analysed and solved by methods of the general theory of splines. Dynamical systems associated with the second order linear differential equation with initial conditions are investigated in the paper (the restriction on the order of equations is not essential). We consider this system as a curve generator. The goal is to find a control law by minimization of the quadratic cost function under inequality type constraints on location conditions. A spline-based numerical scheme for some cases of such optimal control problems is proposed in this paper. In particular, the method of adding-removing spline interpolation knots is applied to the construction of its solution. The suggested technique is illustrated by numerical examples.
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基于样条的不等式约束下轨迹最优控制方法
将最优轨迹规划问题作为动力系统的约束最优控制问题进行了研究。它是机器人、生物力学、航空学和许多其他控制理论应用领域的基本问题之一。这个问题的最简单的版本假设有给定的目标点序列和规定的时间,我们被要求在规定的时间到达给定的点。然而,在大多数应用中,当轨迹在规定时间接近指定点时就足够了。因此,位置条件可以看作是不等式型约束。本研究的目的是将这类最优控制问题简化为凸集中的样条问题,用样条一般理论的方法对其进行分析和求解。本文研究了具有初始条件的二阶线性微分方程的动力系统(方程的阶数限制不重要)。我们把这个系统看作是一个曲线发生器。目标是在位置条件的不等式型约束下,通过最小化二次代价函数找到控制律。本文针对这类最优控制问题的某些情况,提出了一种基于样条的数值格式。特别地,将样条插值结点的加减法应用于其解的构造。通过数值算例说明了所建议的方法。
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