When implementing Markov Chain Monte Carlo (MCMC) algorithms, perturbation caused by numerical errors is sometimes inevitable. This paper studies how the perturbation of MCMC affects the convergence speed and approximation accuracy. Our results show that when the original Markov chain converges to stationarity fast enough and the perturbed transition kernel is a good approximation to the original transition kernel, the corresponding perturbed sampler has fast convergence speed and high approximation accuracy as well. Our convergence analysis is conducted under either the Wasserstein metric or the $\chi^2$ metric, both are widely used in the literature. The results can be extended to obtain non-asymptotic error bounds for MCMC estimators. We demonstrate how to apply our convergence and approximation results to the analysis of specific sampling algorithms, including Random walk Metropolis, Metropolis adjusted Langevin algorithm with perturbed target densities, and parallel tempering Monte Carlo with perturbed densities. Finally, we present some simple numerical examples to verify our theoretical claims.

Aiming at the issue of missiles attacking on-ground maneuvering targets in three-dimensional space, a three-dimensional finite-time guidance law with impact-angle constraints is proposed. In order to improve convergence speed and restrain chattering phenomenon, the nonsingular fast terminal three-dimensional second-order sliding mode guidance law with coupling terms is designed based on the theory of nonhomogeneous fast terminal sliding surface and second-order sliding mode control. The system model need not be linearized during the design process, and the singular problem is avoided. A nonhomogeneous disturbance observer is designed to estimate and compensate the total disturbance, which is caused by target maneuvering information and coupling terms of line of sight. And the stability and finite-time convergence of the guidance law are proved strictly and mathematically. Finally, simulation results have verified the effectiveness and superiority of the proposed guidance law.