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Control design for hybrid systems with TuLiP: The Temporal Logic Planning toolbox

机译:具有TuLiP的混合系统的控制设计:时间逻辑规划工具箱

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This tutorial describes TuLiP, the Temporal Logic Planning toolbox, a collection of tools for designing controllers for hybrid systems from specifications in temporal logic. The tools support a workflow that starts from a description of desired behavior, and of the system to be controlled. The system can have discrete state, or be a hybrid dynamical system with a mixed discrete and continuous state space. The desired behavior can be represented with temporal logic and discrete transition systems. The system description can include uncontrollable variables that take discrete or continuous values, and represent disturbances and other environmental factors that affect the dynamics, as well as communication signals that affect controller decisions. A control design problem is solved in phases that involve abstraction, discrete synthesis, and continuous feedback control. Abstraction yields a discrete description of system dynamics in logic. For piecewise affine dynamical systems, this abstraction is constructed automatically, guided by the geometry of the dynamics and under logical constraints from the specification. The resulting logic formulae describe admissible discrete behaviors that capture both controlled and environment variables. The discrete description resulting from abstraction is then conjoined with the desired logic specification. To find a controller, the toolbox solves a game of infinite duration. Existence of a discrete (winning) strategy for the controlled variables in this game is a proof certificate for the existence of a controller for the original problem, which guarantees satisfaction of the specification. This discrete strategy, concretized by using continuous controllers, yields a feedback controller for the original hybrid system. The toolbox frontend is written in Python, with backends in C, Python, and Cython. The tutorial starts with an overview of the theory behind TuLiP, and of its software architecture, organized into specification frontends and backends that implement algorithms for abstraction, solving games, and interfaces to other tools. Then, the main elements for writing a specification for input to TuLiP are introduced. These include logic formulae, discrete transition systems annotated with predicates, and hybrid dynamical systems, with linear or piecewise affine continuous dynamics. The working principles of the algorithms for predicate abstraction and discrete game solving using nested fixpoints are explained, by following the input specification through the various transformations that compile it to a symbolic representation that scales well to solving large games. The tutorial concludes with several design examples that demonstrate the toolbox's capabilities.
机译:本教程介绍了TuLiP,时间逻辑计划工具箱,该工具箱是用于根据时间逻辑规范为混合系统设计控制器的工具集合。这些工具支持从描述所需行为以及要控制的系统开始的工作流程。该系统可以具有离散状态,也可以是具有混合离散和连续状态空间的混合动力系统。期望的行为可以用时间逻辑和离散转换系统表示。系统描述可以包括不可控制的变量,这些变量采用离散值或连续值,并表示影响动力学的干扰和其他环境因素,以及影响控制器决策的通信信号。在涉及抽象,离散综合和连续反馈控制的阶段中解决了控制设计问题。抽象产生了逻辑上系统动力学的离散描述。对于分段仿射动力学系统,此抽象是在动力学的几何结构的指导下并在规范的逻辑约束下自动构建的。生成的逻辑公式描述了可捕获的离散行为,这些行为捕获了受控变量和环境变量。然后,将抽象引起的离散描述与所需的逻辑规范结合起来。为了找到控制器,工具箱需要解决无限长的游戏。此游戏中离散变量(获胜)策略的存在是存在原始问题的控制器的证明,这保证了对规格的满意。通过使用连续控制器具体化的这种离散策略产生了原始混合系统的反馈控制器。工具箱的前端是用Python编写的,后端是用C,Python和Cython编写的。本教程首先概述了TuLiP背后的理论及其软件体系结构,并组织了规范的前端和后端,这些前端和后端实现了用于抽象,求解游戏以及与其他工具的接口的算法。然后,介绍了编写用于输入TuLiP的规范的主要元素。这些包括逻辑公式,带有谓词的离散过渡系统以及具有线性或分段仿射连续动力学的混合动力系统。通过遵循输入规范,通过各种转换将其编译为可很好地缩放以解决大型游戏的符号表示形式,来解释使用嵌套固定点进行谓词抽象和离散游戏求解的算法的工作原理。本教程以几个设计示例作为结束,这些示例演示了工具箱的功能。

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