Complexity of ten decision problems in continuous time dynamical systems

We show that for continuous time dynamical systems described by polynomial differential equations of modest degree (typically equal to three), the following decision problems which arise in numerous areas of systems and control theory cannot have a polynomial time (or even pseudo-polynomial time) algorithm unless P=NP: local attractivity of an equilibrium point, stability of an equilibrium point in the sense of Lyapunov, boundedness of trajectories, convergence of all trajectories in a ball to a given equilibrium point, existence of a quadratic Lyapunov function, invariance of a ball, invariance of a quartic semialgebraic set under linear dynamics, local collision avoidance, and existence of a stabilizing control law. We also extend our earlier NP-hardness proof of testing local asymptotic stability for polynomial vector fields to the case of trigonometric differential equations of degree four.

[1]  M. Vidyasagar,et al.  Lagrange stability and higher order derivatives of Liapunov functions , 1970 .

[2]  L. Shampine,et al.  Numerical Solution of Ordinary Differential Equations. , 1995 .

[3]  Martin Braun Differential Equations and Their Applications: An Introduction to Applied Mathematics , 1977 .

[4]  H. I. Freedman Deterministic mathematical models in population ecology , 1982 .

[5]  Katta G. Murty,et al.  Some NP-complete problems in quadratic and nonlinear programming , 1987, Math. Program..

[6]  Newton C. A. da Costa,et al.  On Arnold's Hilbert Symposium Problems , 1993, Kurt Gödel Colloquium.

[7]  Richard M. Murray,et al.  A Mathematical Introduction to Robotic Manipulation , 1994 .

[8]  Eduardo Sontag From linear to nonlinear: some complexity comparisons , 1995, Proceedings of 1995 34th IEEE Conference on Decision and Control.

[9]  B. Bequette Process Dynamics: Modeling, Analysis and Simulation , 1998 .

[10]  J. Tsitsiklis,et al.  Overview of complexity and decidability results for three classes of elementary nonlinear systems , 1999 .

[11]  John N. Tsitsiklis,et al.  A survey of computational complexity results in systems and control , 2000, Autom..

[12]  Etienne de Klerk,et al.  Approximation of the Stability Number of a Graph via Copositive Programming , 2002, SIAM J. Optim..

[13]  Paul C. Bell,et al.  The Continuous Skolem-Pisot Problem: On the Complexity of Reachability for Linear Ordinary Differential Equations , 2008, 0809.2189.

[14]  Emmanuel Hainry Decidability and Undecidability in Dynamical Systems , 2009 .

[15]  Olivier Bournez,et al.  A Survey on Continuous Time Computations , 2009, ArXiv.

[16]  E. Süli,et al.  Numerical Solution of Ordinary Differential Equations , 2021, Foundations of Space Dynamics.

[17]  P. Moin NUMERICAL SOLUTION OF ORDINARY DIFFERENTIAL EQUATIONS , 2010 .

[18]  Jean-Charles Delvenne,et al.  The continuous Skolem-Pisot problem , 2010, Theor. Comput. Sci..

[19]  Miroslav Krstic,et al.  A globally asymptotically stable polynomial vector field with no polynomial Lyapunov function , 2011, IEEE Conference on Decision and Control and European Control Conference.

[20]  Amir Ali Ahmadi Algebraic relaxations and hardness results in polynomial optimization and Lyapunov analysis , 2012, ArXiv.

[21]  Amir Ali Ahmadi On the difficulty of deciding asymptotic stability of cubic homogeneous vector fields , 2011, 2012 American Control Conference (ACC).

[22]  P. Olver Nonlinear Systems , 2013 .