1,798 research outputs found
Synthesizing Switching Controllers for Hybrid Systems by Continuous Invariant Generation
We extend a template-based approach for synthesizing switching controllers
for semi-algebraic hybrid systems, in which all expressions are polynomials.
This is achieved by combining a QE (quantifier elimination)-based method for
generating continuous invariants with a qualitative approach for predefining
templates. Our synthesis method is relatively complete with regard to a given
family of predefined templates. Using qualitative analysis, we discuss
heuristics to reduce the numbers of parameters appearing in the templates. To
avoid too much human interaction in choosing templates as well as the high
computational complexity caused by QE, we further investigate applications of
the SOS (sum-of-squares) relaxation approach and the template polyhedra
approach in continuous invariant generation, which are both well supported by
efficient numerical solvers
Some Applications of Polynomial Optimization in Operations Research and Real-Time Decision Making
We demonstrate applications of algebraic techniques that optimize and certify
polynomial inequalities to problems of interest in the operations research and
transportation engineering communities. Three problems are considered: (i)
wireless coverage of targeted geographical regions with guaranteed signal
quality and minimum transmission power, (ii) computing real-time certificates
of collision avoidance for a simple model of an unmanned vehicle (UV)
navigating through a cluttered environment, and (iii) designing a nonlinear
hovering controller for a quadrotor UV, which has recently been used for load
transportation. On our smaller-scale applications, we apply the sum of squares
(SOS) relaxation and solve the underlying problems with semidefinite
programming. On the larger-scale or real-time applications, we use our recently
introduced "SDSOS Optimization" techniques which result in second order cone
programs. To the best of our knowledge, this is the first study of real-time
applications of sum of squares techniques in optimization and control. No
knowledge in dynamics and control is assumed from the reader
Encoding inductive invariants as barrier certificates: synthesis via difference-of-convex programming
A barrier certificate often serves as an inductive invariant that isolates an
unsafe region from the reachable set of states, and hence is widely used in
proving safety of hybrid systems possibly over an infinite time horizon. We
present a novel condition on barrier certificates, termed the invariant
barrier-certificate condition, that witnesses unbounded-time safety of
differential dynamical systems. The proposed condition is the weakest possible
one to attain inductive invariance. We show that discharging the invariant
barrier-certificate condition -- thereby synthesizing invariant barrier
certificates -- can be encoded as solving an optimization problem subject to
bilinear matrix inequalities (BMIs). We further propose a synthesis algorithm
based on difference-of-convex programming, which approaches a local optimum of
the BMI problem via solving a series of convex optimization problems. This
algorithm is incorporated in a branch-and-bound framework that searches for the
global optimum in a divide-and-conquer fashion. We present a weak completeness
result of our method, namely, a barrier certificate is guaranteed to be found
(under some mild assumptions) whenever there exists an inductive invariant (in
the form of a given template) that suffices to certify safety of the system.
Experimental results on benchmarks demonstrate the effectiveness and efficiency
of our approach.Comment: To be published in Inf. Comput. arXiv admin note: substantial text
overlap with arXiv:2105.1431
- …