Control Design for Risk-Based Signal Temporal Logic Specifications

被引:10
|
作者
Safaoui, Sleiman [1 ]
Lindemann, Lars [2 ]
Dimarogonas, Dimos, V [2 ]
Shames, Iman [3 ]
Summers, Tyler H. [4 ]
机构
[1] Univ Texas Dallas, Dept Elect Engn, Richardson, TX 75080 USA
[2] KTH Royal Inst Technol, Div Decis & Control Syst, S-10044 Stockholm, Sweden
[3] Univ Melbourne, Dept Elect & Elect Engn, Parkville, Vic 3010, Australia
[4] Univ Texas Dallas, Dept Mech Engn, Richardson, TX 75080 USA
来源
IEEE CONTROL SYSTEMS LETTERS | 2020年 / 4卷 / 04期
基金
瑞典研究理事会;
关键词
Semantics; Robustness; Atomic measurements; Stochastic systems; Random variables; Distortion measurement; Autonomous systems; optimization; constrained control; MODEL-PREDICTIVE CONTROL; FRAMEWORK;
D O I
10.1109/LCSYS.2020.2998543
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
We present a general framework for risk semantics on Signal Temporal Logic (STL) specifications for stochastic dynamical systems using axiomatic risk theory. We show that under our recursive risk semantics, risk constraints on STL formulas can be expressed in terms of risk constraints on atomic predicates. We then show how this allows a (stochastic) STL risk constraint to be transformed into a risk-tightened deterministic STL constraint on a related deterministic nominal system, enabling the application of existing STL methods. For affine predicate functions and a (coherent) Distributionally Robust Value at Risk measure, we show how risk constraints on atomic predicates can be reformulated as tightened deterministic affine constraints. We demonstrate the framework using a Model Predictive Control (MPC) design with an STL risk constraint.
引用
收藏
页码:1000 / 1005
页数:6
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