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This study considers the control problem with signal temporal logic (STL)specifications. Prior works have adopted smoothing techniques to address thisproblem within a feasible time frame and solve the problem by applyingsequential quadratic programming (SQP) methods naively. However, one of thedrawbacks of this approach is that solutions can easily become trapped in localminima that do not satisfy the specification. In this study, we propose a newoptimization method, termed CCP-based SQP, based on the convex-concaveprocedure (CCP). Our framework includes a new robustness decomposition methodthat decomposes the robustness function into a set of constraints, resulting ina form of difference of convex (DC) program that can be solved efficiently. Wesolve this DC program sequentially as a quadratic program by only approximatingthe disjunctive parts of the specifications. Our experimental resultsdemonstrate that our method has a superior performance compared to thestate-of-the-art SQP methods in terms of both robustness and computationaltime.

Signal Temporal Logic Meets Convex-Concave Programming: A Structure-Exploiting SQP Algorithm for STL Specifications