Controller Synthesis subject to Logical and Structural Constraints: A Satisfiability Modulo Theories (SMT) Approach

We report on a simple approach to use satisfiability modulo theories (SMT) solvers to synthesize stabilizing controllers subject to logical and structural constraints. Examples of logical/structural specifications allowed by our methodology include the transitive property of the connectivity of a networked system, and the mutually exclusive use of inputs or sensors, to name a few. The aforementioned structural constraints can also impose the sparsity pattern and linear dependency restrictions prevailing in the decentralized control literature. The main goal of this article is to discuss preliminary results and examples in which both the plant and the controller are linear time-invariant (LTI). Our approach consists of encoding the stability conditions as well as the logical and structural constraints as an SMT instance. We illustrate our methodology on two classes of problems: (i) full state feedback design for positive systems, with applications to combination drug therapy and transportation network design, and (ii) static output feedback (SOF) design. The article includes numerical examples for each of these applications computed using a freely available SMT solver. It is noteworthy that the examples of positive systems mentioned above, in particular, can be solved in less than four minutes even when the dimension of the state is one thousand.

[1]  Paulo Tabuada,et al.  Scalable lazy SMT-based motion planning , 2016, 2016 IEEE 55th Conference on Decision and Control (CDC).

[2]  Swarat Chaudhuri,et al.  Controller synthesis with inductive proofs for piecewise linear systems: An SMT-based algorithm , 2015, 2015 54th IEEE Conference on Decision and Control (CDC).

[3]  Nikolaj Bjørner,et al.  Z3: An Efficient SMT Solver , 2008, TACAS.

[4]  Fu Lin,et al.  Design of Optimal Sparse Feedback Gains via the Alternating Direction Method of Multipliers , 2011, IEEE Transactions on Automatic Control.

[5]  Donald W. Loveland,et al.  A machine program for theorem-proving , 2011, CACM.

[6]  Marcello Colombino,et al.  Robust and Decentralized Control of Positive Systems: A Convex Approach , 2016 .

[7]  Edward J. Davison,et al.  Characterizations of decentralized fixed modes for interconnected systems , 1981, Autom..

[8]  B. F. Caviness,et al.  Quantifier Elimination and Cylindrical Algebraic Decomposition , 2004, Texts and Monographs in Symbolic Computation.

[9]  E. J. Routh A Treatise on the Stability of a Given State of Motion: Particularly Steady Motion , 2010 .

[10]  Nuno C. Martins,et al.  Information structures in optimal decentralized control , 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).

[11]  B. Anderson,et al.  Output feedback stabilization and related problems-solution via decision methods , 1975 .

[12]  Petros G. Voulgaris,et al.  A convex characterization of distributed control problems in spatially invariant systems with communication constraints , 2005, Syst. Control. Lett..

[13]  A. Tarski A Decision Method for Elementary Algebra and Geometry , 2023 .

[14]  George E. Collins,et al.  Quantifier elimination for real closed fields by cylindrical algebraic decomposition , 1975 .

[15]  Paulo Tabuada,et al.  Secure State Estimation for Cyber-Physical Systems Under Sensor Attacks: A Satisfiability Modulo Theory Approach , 2014, IEEE Transactions on Automatic Control.

[16]  Hilary Putnam,et al.  A Computing Procedure for Quantification Theory , 1960, JACM.

[17]  Wei Yang,et al.  Robust Multi-Objective Feedback Design by Quantifier Elimination , 1997, J. Symb. Comput..

[18]  Dragoslav D. Šiljak,et al.  Decentralized control of complex systems , 2012 .

[19]  Nuno C. Martins,et al.  Youla-Like Parametrizations Subject to QI Subspace Constraints , 2014, IEEE Transactions on Automatic Control.

[20]  Nuno C. Martins,et al.  On the Nearest Quadratically Invariant Information Constraint , 2011, IEEE Transactions on Automatic Control.

[21]  Sanjay Lall,et al.  A Characterization of Convex Problems in Decentralized Control$^ast$ , 2005, IEEE Transactions on Automatic Control.

[22]  A. Stephen Morse,et al.  Decentralized control of linear multivariable systems , 1976, Autom..

[23]  Marcel Staroswiecki,et al.  Fault‐tolerant control of distributed systems by information pattern reconfiguration , 2015 .

[24]  Chaouki T. Abdallah,et al.  Quantified inequalities and robust control , 1998, Robustness in Identification and Control.

[25]  MirSaleh Bahavarnia State-Feedback Controller Sparsification via Quasi-Norms , 2019, 2019 American Control Conference (ACC).

[26]  Maxim Kristalny,et al.  On structured realizability and stabilizability of linear systems , 2013, 2013 American Control Conference.

[27]  Paulo Tabuada,et al.  SMC: Satisfiability Modulo Convex Programming , 2018, Proceedings of the IEEE.

[28]  J. Tsitsiklis,et al.  NP-hardness of some linear control design problems , 1995, Proceedings of 1995 34th IEEE Conference on Decision and Control.

[29]  Nader Motee,et al.  State feedback controller sparsification via a notion of non-fragility , 2017, 2017 IEEE 56th Annual Conference on Decision and Control (CDC).

[30]  Anders Rantzer,et al.  Distributed control of positive systems , 2011, IEEE Conference on Decision and Control and European Control Conference.

[31]  Mohammad Aldeen,et al.  Stabilization of decentralized control systems , 1997 .

[32]  Nuno C. Martins,et al.  A Convex Characterization of Multidimensional Linear Systems Subject to SQI Constraints , 2017, IEEE Transactions on Automatic Control.

[33]  Soummya Kar,et al.  A Framework for Structural Input/Output and Control Configuration Selection in Large-Scale Systems , 2013, IEEE Transactions on Automatic Control.

[34]  Hamid Reza Karimi,et al.  Static output-feedback control under information structure constraints , 2013, Autom..