Hierarchical Decomposition of LTL Synthesis Problem for Nonlinear Control Systems

This paper deals with the control synthesis problem for a continuous nonlinear dynamical system under a linear temporal logic (LTL) formula. The proposed solution is a top-down hierarchical decomposition of the control problem involving three abstraction layers of the problem, iteratively solved from the coarsest to the finest. The LTL planning is first solved on a small transition system only describing the regions of interest involved in the LTL formula. For each pair of consecutive regions of interest in the resulting accepting path satisfying the LTL formula, a discrete plan is then constructed in the partitioned workspace to connect these two regions while avoiding unsafe regions. Finally, an abstraction refinement approach is applied to synthesize a controller for the dynamical system to follow each discrete plan. The second main contribution, used in the third abstraction layer, is a new monotonicity-based method to overapproximate the finite-time reachable set of any continuously differentiable system. The proposed framework is demonstrated in simulation for a motion planning problem of a mobile robot modeled as a disturbed unicycle.

[1]  Peter Norvig,et al.  Artificial Intelligence: A Modern Approach , 1995 .

[2]  Dimos V. Dimarogonas,et al.  Decentralized Abstractions For Multi-Agent Systems Under Coupled Constraints , 2015, Eur. J. Control.

[3]  Murat Arcak,et al.  Efficient finite abstraction of mixed monotone systems , 2015, HSCC.

[4]  Antoine Girard,et al.  Hierarchical Synthesis of Hybrid Controllers from Temporal Logic Specifications , 2007, HSCC.

[5]  Sriram Sankaranarayanan,et al.  On the minimal revision problem of specification automata , 2014, Int. J. Robotics Res..

[6]  Ufuk Topcu,et al.  TuLiP: a software toolbox for receding horizon temporal logic planning , 2011, HSCC '11.

[7]  Ufuk Topcu,et al.  Receding horizon temporal logic planning for dynamical systems , 2009, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference.

[8]  Dimos V. Dimarogonas,et al.  Compositional abstraction refinement for control synthesis , 2017, ArXiv.

[9]  Manuel Mazo,et al.  PESSOA: A Tool for Embedded Controller Synthesis , 2010, CAV.

[10]  Murat Arcak,et al.  Stability of traffic flow networks with a polytree topology , 2016, Autom..

[11]  Majid Zamani,et al.  SCOTS: A Tool for the Synthesis of Symbolic Controllers , 2016, HSCC.

[12]  Dimos V. Dimarogonas,et al.  Multi-agent plan reconfiguration under local LTL specifications , 2015, Int. J. Robotics Res..

[13]  Hal L. Smith,et al.  Monotone Dynamical Systems: An Introduction To The Theory Of Competitive And Cooperative Systems (Mathematical Surveys And Monographs) By Hal L. Smith , 1995 .

[14]  David Angeli,et al.  Monotone control systems , 2003, IEEE Trans. Autom. Control..

[15]  Hadas Kress-Gazit,et al.  LTLMoP: Experimenting with language, Temporal Logic and robot control , 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[16]  Hadas Kress-Gazit,et al.  Temporal-Logic-Based Reactive Mission and Motion Planning , 2009, IEEE Transactions on Robotics.

[17]  Calin Belta,et al.  A symbolic approach to controlling piecewise affine systems , 2010, 49th IEEE Conference on Decision and Control (CDC).

[18]  Xin-She Yang,et al.  Introduction to Algorithms , 2021, Nature-Inspired Optimization Algorithms.

[19]  Dimos V. Dimarogonas,et al.  Abstraction refinement and plan revision for control synthesis under high level specifications , 2017 .

[20]  Amey Y. Karnik,et al.  Fuel Cell Thermal Management: Modeling, Specifications, and Correct-by-Construction Control Synthesis , 2020, IEEE Transactions on Control Systems Technology.

[21]  Paulo Tabuada,et al.  Verification and Control of Hybrid Systems - A Symbolic Approach , 2009 .

[22]  Calin Belta,et al.  Time-Constrained Temporal Logic Control of Multi-Affine Systems , 2012, ADHS.

[23]  Dimos V. Dimarogonas,et al.  Compositional abstraction refinement for control synthesis under lasso-shaped specifications , 2017, 2017 American Control Conference (ACC).

[24]  Petter Nilsson,et al.  Incremental synthesis of switching protocols via abstraction refinement , 2014, 53rd IEEE Conference on Decision and Control.

[25]  P. Cochat,et al.  Et al , 2008, Archives de pediatrie : organe officiel de la Societe francaise de pediatrie.

[26]  Amey Y. Karnik,et al.  Fuel cell thermal management: Modeling, specifications and correct-by-construction control synthesis , 2017, 2017 American Control Conference (ACC).

[27]  Antoine Girard,et al.  CoSyMA: a tool for controller synthesis using multi-scale abstractions , 2013, HSCC '13.

[28]  Necmiye Ozay,et al.  A note on some sufficient conditions for mixed monotone systems , 2017 .

[29]  Antonio Bicchi,et al.  Symbolic planning and control of robot motion [Grand Challenges of Robotics] , 2007, IEEE Robotics & Automation Magazine.

[30]  Jörg Raisch,et al.  Abstraction based supervisory controller synthesis for high order monotone continuous systems , 2002 .

[31]  Gunther Reissig,et al.  Feedback Refinement Relations for the Synthesis of Symbolic Controllers , 2015, IEEE Transactions on Automatic Control.

[32]  Gerard J. Holzmann,et al.  The SPIN Model Checker - primer and reference manual , 2003 .