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This makes the closed-loop control system a stochastic switching system.
We introduce an impulsive observer-based controller, which makes the closed-loop system a stochastic hybrid system that consists of a stochastic nonlinear system and a stochastic impulsive differential system.
Assuming that the system can be modeled as a linear system, a stochastic approach was used to analyze the motion response (heave, surge and pitch) characteristics of the fish cage and the load (tension) response in an anchor line to wave forcing.
A predator-prey model with Beddington-DeAngelis functional response and disease in the predator population is proposed, corresponding to the deterministic system, a stochastic model is investigated with parameter perturbation.
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First, by deriving the infinitesimal generator for stochastic Lyapunov functional of descriptor semi-Markov jump systems, a stochastic stability condition is established, which guarantees this kind of systems are regular, impulse-free, have a unique solution, and are stochastically stable.
By augmenting the system vector, a stochastic augmented system is obtained.
The system is modeled in the framework of linear fractional transformation with a deterministic nominal system and a stochastic model uncertainty.
The objective is to combine a finite element numerical model describing the physical behavior of a mechatronic system with a stochastic model of its behavior.
The white noise is derived from the Wiener process, so the resulted system is a stochastic differential equation and is modeled by an Ito differential form.
The generalization of the MDP problem to a multiagent system is a stochastic game.
For example, Mao [18] provided a sufficient condition such that the exponentially stable nonlinear system with a stochastic delay perturbation remains exponentially stable.
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