We consider the decidability of state-to-state reachability in linear time-invariant control systems over discrete time. We analyse this problem with respect to the allowable control sets, which in general are assumed to be defined by boolean combinations of linear inequalities. Decidability of the version of the reachability problem in which control sets are affine subspaces of Rn is a fundamental result in control theory. Our first result is that reachability is undecidable if the set of controls is a finite union of affine subspaces. We also consider versions of the reachability problem in which (i) the set of controls consists of a single affine subspace together with the origin and (ii) the set of controls is a convex polytope. In these two cases we respectively show that the reachability problem is as hard as Skolem's Problem and the Positivity Problem for linear recurrence sequences (whose decidability has been open for several decades). Our main contribution is to show decidability of a version of the reachability problem in which control sets are convex polytopes, under certain spectral assumptions on the transition matrix.

We consider the decidability of the membership problem for matrix-exponential semigroups: Given k ∈ N and square matrices A 1 , … , A k , C , all of the same dimension and with real algebraic entries, decide whether C is contained in the semigroup generated by the matrix exponentials exp ( A i t ), where i ∈ { 1,… , k } and t ≥ 0. This problem can be seen as a continuous analog of Babai et al.’s and Cai et al.’s problem of solving multiplicative matrix equations and has applications to reachability analysis of linear hybrid automata and switching systems. Our main results are that the semigroup membership problem is undecidable in general, but decidable if we assume that A 1 , … , A k commute. The decidability proof is by reduction to a version of integer programming that has transcendental constants. We give a decision procedure for the latter using Baker’s theorem on linear forms in logarithms of algebraic numbers, among other tools. The undecidability result is shown by reduction from Hilbert’s Tenth Problem.

The Polytope Escape Problem for continuous linear dynamical systems consists of deciding, given an affine function f:Rd -> Rd and a convex polytope P⊆ Rd, both with rational descriptions, whether there exists an initial point x0 in P such that the trajectory of the unique solution to the differential equation: ·x(t)=f(x(t)) x 0= x0 is entirely contained in P. We show that this problem is reducible in polynomial time to the decision version of linear programming with real algebraic coefficients. The latter is a special case of the decision problem for the existential theory of real closed fields, which is known to lie between NP and PSPACE. Our algorithm makes use of spectral techniques and relies, among others, on tools from Diophantine approximation.

We consider a continuous analogue of (Babai et al. 1996)'s and (Cai et al. 2000)'s problem of solving multiplicative matrix equations. Given k + 1 square matrices A1, ..., Ak, C, all of the same dimension, whose entries are real algebraic, we examine the problem of deciding whether there exist non-negative reals t1, ..., tk such that

A fundamental problem in program verification concerns the termination of simple linear loops of the form: where x is a vector of variables, u, a, and c are integer vectors, and A and B are integer matrices. Assuming the matrix A is diagonalisable, we give a decision procedure for the problem of whether, for all initial integer vectors u, such a loop terminates. The correctness of our algorithm relies on sophisticated tools from algebraic and analytic number theory, Diophantine geometry, and real algebraic geometry. To the best of our knowledge, this is the first substantial advance on a 10-year-old open problem of Tiwari [38] and Braverman [8].