Safe Controller Synthesis for Data-Driven Differential Inclusions

被引:16
|
作者
Ahmadi, Mohamadreza [1 ]
Israel, Arie [2 ]
Topcu, Ufuk [2 ]
机构
[1] CALTECH, Pasadena, CA 91125 USA
[2] Univ Texas Austin, Austin, TX 78712 USA
关键词
Safety; Splines (mathematics); Trajectory; Computational modeling; Data models; Mathematical model; Aerospace control; control system synthesis; learning; safety; ONLINE SYSTEM-IDENTIFICATION; BARRIER FUNCTIONS; FEEDBACK-CONTROL; VERIFICATION; POLYNOMIALS; FORM;
D O I
10.1109/TAC.2020.2969713
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 consider the problem of designing finite-horizon safe controllers for a dynamical system for which no explicit analytical model exists and limited data only along a single trajectory of the system are available. Given samples of the states and inputs of the system, and additional side information in terms of regularity of the evolution of the states, we synthesize a controller such that the evolution of the states avoid some prespecified unsafe set over a given finite horizon. Motivated by recent results on Whitneys extension theorem, we use piecewise-polynomial approximations of the trajectories based on the data along with the regularity side information to formulate a data-driven differential inclusion model that can predict the evolution of the trajectories. For these classes of data-driven differential inclusions, we propose a safety analysis theorem based on barrier certificates. As a corollary of this theorem, we demonstrate that we can design controllers ensuring safety of the solutions to the data-driven differential inclusion over a finite horizon. From a computational standpoint, our results are cast into a set of sum-of-squares programs whenever the certificates are parametrized by polynomials of fixed degree and the sets are semialgebraic.
引用
收藏
页码:4934 / 4940
页数:7
相关论文
共 50 条
  • [31] Controller Synthesis for Unknown Polynomial-Type Systems: A Data-Driven Approach
    Nejati, Ameneh
    Zhong, Bingzhuo
    Caccamo, Marco
    Zamani, Majid
    [J]. 2ND INTERNATIONAL WORKSHOP ON COMPUTATION-AWARE ALGORITHMIC DESIGN FOR CYBER-PHYSICAL SYSTEMS (CAADCPS 2022), 2022, : 11 - 12
  • [32] Data-driven criteria synthesis of system with two-degree-of-freedom controller
    Zhai, Ding
    Zhang, Qing-Ling
    Liu, Guo-Yi
    [J]. INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 2014, 45 (11) : 2275 - 2281
  • [33] Towards Data-Driven LPV Controller Synthesis Based on Frequency Response Functions
    Bloemers, Tom
    Toth, Roland
    Oomen, Tom
    [J]. 2019 IEEE 58TH CONFERENCE ON DECISION AND CONTROL (CDC), 2019, : 5680 - 5685
  • [34] Data-driven multimodal synthesis
    Carlson, R
    Granström, B
    [J]. SPEECH COMMUNICATION, 2005, 47 (1-2) : 182 - 193
  • [35] Simultaneous Updating of a Model and a Controller Based on the Data-Driven Fictitious Controller
    Kaneko, Osamu
    Miyachi, Makoto
    Fujii, Takao
    [J]. 47TH IEEE CONFERENCE ON DECISION AND CONTROL, 2008 (CDC 2008), 2008, : 1358 - 1363
  • [36] Online Stochastic Optimization for Unknown Linear Systems: Data-Driven Controller Synthesis and Analysis
    Bianchin, Gianluca
    Vaquero, Miguel
    Cortes, Jorge
    Dall'Anese, Emiliano
    [J]. IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2024, 69 (07) : 4411 - 4426
  • [37] Constrained Data-Driven Controller Tuning for Nonlinear Systems
    Radac, Mircea-Bogdan
    Precup, Radu-Emil
    Preitl, Stefan
    Dragos, Claudia-Adina
    Petriu, Emil M.
    [J]. 39TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY (IECON 2013), 2013, : 3404 - 3409
  • [38] On identification methods for direct data-driven controller tuning
    van Heusden, Klaske
    Karimi, Alireza
    Soderstrom, Torsten
    [J]. INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, 2011, 25 (05) : 448 - 465
  • [39] Design of a Data-driven Predictive-PI Controller
    Ashida, Yoichiro
    Wakitani, Shin
    Yamamoto, Toru
    [J]. ICAROB 2019: PROCEEDINGS OF THE 2019 INTERNATIONAL CONFERENCE ON ARTIFICIAL LIFE AND ROBOTICS, 2019, : 451 - 454
  • [40] Synthesis of ILC-MPC Controller With Data-Driven Approach for Constrained Batch Processes
    Li, Dewei
    He, Shaoying
    Xi, Yugeng
    Liu, Tao
    Gao, Furong
    Wang, Youqing
    Lu, Jingyi
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2020, 67 (04) : 3116 - 3125