This study considers the control problem with signal temporal logic (STL) specifications. Prior works have adopted smoothing techniques to address this problem within a feasible time frame and solve the problem by applying sequential quadratic programming (SQP) methods naively. However, one of the drawbacks of this approach is that solutions can easily become trapped in local minima that do not satisfy the specification. In this study, we propose a new optimization method, termed CCP-based SQP, based on the convex-concave procedure (CCP). Our framework includes a new robustness decomposition method that decomposes the robustness function into a set of constraints, resulting in a form of difference of convex (DC) program that can be solved efficiently. We solve this DC program sequentially as a quadratic program by only approximating the disjunctive parts of the specifications. Our experimental results demonstrate that our method has a superior performance compared to the state-of-the-art SQP methods in terms of both robustness and computational time.
翻译:本研究考虑具有信号时序逻辑 (STL) 规程的控制问题。之前的工作采用平滑技术在可行的时间范围内解决该问题,并通过朴素地应用顺序二次规划 (SQP) 方法来解决问题。然而,这种方法的缺点之一是解决方案很容易陷入不满足规程的局部极小值中。在本研究中,我们提出了一种新的优化方法,称为基于凸凹过程 (CCP) 的 SQP 方法。我们的框架包括一种新的健壮性分解方法,可以将健壮性函数分解为一组约束,导致一种差分凸 (DC) 程序的形式,可以有效地解决。我们仅通过近似规格的分隔部分,将此 DC 程序顺序解决为二次规划。我们的实验结果表明,我们的方法在健壮性和计算时间方面都优于最先进的 SQP 方法。