Utilizing the Updated Gamma-Ray Bursts and Type Ia Supernovae to Constrain the Cardassian Expansion Model and Dark Energy

We update gamma-ray burst (GRB) luminosity relations among certain spectral and light-curve features with 139 GRBs. The distance modulus of 82 GRBs at $z>1.4$ can be calibrated with the sample at $z\leq1.4$ by using the cubic spline interpolation method from the Union2.1 Type Ia supernovae (SNe Ia) set. We investigate the joint constraints on the Cardassian expansion model and dark energy with 580 Union2.1 SNe Ia sample ($z<1.4$) and 82 calibrated GRBs data ($1.4<z\leq8.2$). In $\Lambda$CDM, we find that adding 82 high-\emph{z} GRBs to 580 SNe Ia significantly improves the constrain on $\Omega_{m}-\Omega_{\Lambda}$ plane. In the Cardassian expansion model, the best fit is $\Omega_{m}= 0.24_{-0.15}^{+0.15}$ and $n=0.16_{-0.52}^{+0.30}$ $(1\sigma)$, which is consistent with the $\Lambda$CDM cosmology $(n=0)$ in the $1\sigma$ confidence region. We also discuss two dark energy models in which the equation of state $w(z)$ is parametrized as $w(z)=w_{0}$ and $w(z)=w_{0}+w_{1}z/(1+z)$, respectively. Based on our analysis, we see that our Universe at higher redshift up to $z=8.2$ is consistent with the concordance model within $1\sigma$ confidence level.Comment: 17 pages, 6 figures, 2 tables; accepted for publication in Advances in Astronomy, special issue on Gamma-Ray Burst in Swift and Fermi Era. arXiv admin note: text overlap with arXiv:0802.4262, arXiv:0706.0938 by other author

Backstepping controller design for a class of stochastic nonlinear systems with Markovian switching

A more general class of stochastic nonlinear systems with irreducible homogenous Markovian switching are considered in this paper. As preliminaries, the stability criteria and the existence theorem of strong solutions are first presented by using the inequality of mathematic expectation of a Lyapunov function. The state-feedback controller is designed by regarding Markovian switching as constant such that the closed-loop system has a unique solution, and the equilibrium is asymptotically stable in probability in the large. The output-feedback controller is designed based on a quadratic-plus-quartic-form Lyapunov function such that the closed-loop system has a unique solution with the equilibrium being asymptotically stable in probability in the large in the unbiased case and has a unique bounded-in-probability solution in the biased case