Mean-Square Stability of Uncertain Delayed Stochastic Systems Driven by G-Brownian Motion
Zhengqi Ma, Shoucheng Yuan, Kexin Meng, Shuli Mei
Abstract
This paper investigates the mean-square stability of uncertain time-delay stochastic systems driven by G-Brownian motion, which are commonly referred to as G-SDDEs. To derive a new set of sufficient stability conditions, we employ the linear matrix inequality (LMI) method and construct a Lyapunov–Krasovskii function under the constraint of uncertainty bounds. The resulting sufficient condition does not require any specific assumptions on the G-function, making it more practical. Additionally, we provide numerical examples to demonstrate the validity and effectiveness of the proposed approach.
Topics & Concepts
MathematicsBrownian motionStability (learning theory)Constraint (computer-aided design)Lyapunov functionSquare (algebra)Set (abstract data type)Geometric Brownian motionMean squareApplied mathematicsFunction (biology)Construct (python library)Mathematical optimizationControl theory (sociology)Computer scienceDiffusion processControl (management)StatisticsNonlinear systemInnovation diffusionEvolutionary biologyPhysicsGeometryArtificial intelligenceProgramming languageBiologyKnowledge managementQuantum mechanicsMachine learningStability and Control of Uncertain SystemsNeural Networks Stability and SynchronizationControl Systems and Identification