Simulation-based reachability analysis for nonlinear systems using componentwise contraction properties

A shortcoming of existing reachability approaches for nonlinear systems is the poor scalability with the number of continuous state variables. To mitigate this problem we present a simulation-based approach where we first sample a number of trajectories of the system and next establish bounds on the convergence or divergence between the samples and neighboring trajectories. We compute these bounds using contraction theory and reduce the conservatism by partitioning the state vector into several components and analyzing contraction properties separately in each direction. Among other benefits this allows us to analyze the effect of constant but uncertain parameters by treating them as state variables and partitioning them into a separate direction. We next present a numerical procedure to search for weighted norms that yield a prescribed contraction rate, which can be incorporated in the reachability algorithm to adjust the weights to minimize the growth of the reachable set

Algorithmic Verification of Continuous and Hybrid Systems

We provide a tutorial introduction to reachability computation, a class of computational techniques that exports verification technology toward continuous and hybrid systems. For open under-determined systems, this technique can sometimes replace an infinite number of simulations.Comment: In Proceedings INFINITY 2013, arXiv:1402.661

Control mechanisms for stochastic biochemical systems via computation of reachable sets.

Controlling the behaviour of cells by rationally guiding molecular processes is an overarching aim of much of synthetic biology. Molecular processes, however, are notoriously noisy and frequently nonlinear. We present an approach to studying the impact of control measures on motifs of molecular interactions that addresses the problems faced in many biological systems: stochasticity, parameter uncertainty and nonlinearity. We show that our reachability analysis formalism can describe the potential behaviour of biological (naturally evolved as well as engineered) systems, and provides a set of bounds on their dynamics at the level of population statistics: for example, we can obtain the possible ranges of means and variances of mRNA and protein expression levels, even in the presence of uncertainty about model parameters

A linear time-varying approach for robustness analyses of a re-entry flight technology demonstrator

A novel robustness analysis technique is proposed for atmospheric re-entry applications. The problem is stated as a finite time stability (FTS) analysis of linear time-varying (LTV) systems on a compact time domain, subject to bounded variations in initial state and unknown parameters. The FTS property is formulated as the inclusion of all the possible system trajectories into a pre-specified time-varying subset of the state space. Based on assuming the involved sets are polytopes, the proposed approach allows deducing the system FTS from the property verification on a limited number of numerically computed system trajectories. An additional result is presented which allows determination of a conservative estimate of the maximum norm-bound of time-varying perturbations under which the LTV system remains finite time stable. Results of the application of the proposed technique to a re-entry technology demonstrator are presented which demonstrate its effectiveness in complementing conventional linear time invariant-based analyses. Results also show that it is computationally viable and allows linking the system robustness to a quantitative analysis of the system trajectory dispersion around the nominal one due to concurrent initial state dispersion and uncertain parameters effects, which aids in evaluating mission objectives fulfillment

Robust sliding mode design for uncertain stochastic systems based on H∞ control method

The official published version can be found at the link below.In this paper, the design problem of sliding mode control (SMC) is addressed for uncertain stochastic systems modeled by Itô differential equations. There exist the parameter uncertainties in both the state and input matrices, as well as the unmatched external disturbance. The key feature of this work is the integration of SMC method with H∞ technique such that the robust stochastic stability with a prescribed disturbance attenuation level can be achieved. A sufficient condition for the existence of the desired sliding mode controller is obtained via linear matrix inequalities. The reachability of the specified sliding surface is proven. Finally, a numerical simulation example is presented to illustrate the proposed method.This work was funded by The Royal Society of the U.K.;NNSF of China. Grant Numbers: 60674015, 60674089;The Technology Innovation Key Foundation of Shanghai Municipal Education Commission. Grant Number: 09ZZ60;Shanghai Leading Academic Discipline Project. Grant Number: B50

ARCH-COMP19 Category Report: Continuous and hybrid systems with nonlinear dynamics

We present the results of a friendly competition for formal verification of continuous and hybrid systems with nonlinear continuous dynamics. The friendly competition took place as part of the workshop Applied Verification for Continuous and Hybrid Systems (ARCH) in 2019. In this year, 6 tools Ariadne, CORA, DynIbex, Flow*, Isabelle/HOL, and JuliaReach (in alphabetic order) participated. They are applied to solve reachability analysis problems on four benchmark problems, one of them with hybrid dynamics. We do not rank the tools based on the results, but show the current status and discover the potential advantages of different tools