Engineering Commons^™

Bayesian Estimation Via Sequential Monte Carlo Sampling-Constrained Dynamic Systems, Lixin Lang, Wen-Shiang Chen, Bhavik R. Bakshi, Prem K. Goel, Sridhar Ungarala

Chemical & Biomedical Engineering Faculty Publications

Nonlinear and non-Gaussian processes with constraints are commonly encountered in dynamic estimation problems. Methods for solving such problems either ignore the constraints or rely on crude approximations of the model or probability distributions. Such approximations may reduce the accuracy of the estimates since they often fail to capture the variety of probability distributions encountered in constrained linear and nonlinear dynamic systems. This article describes a practical approach that overcomes these shortcomings via a novel extension of sequential Monte Carlo (SMC) sampling or particle filtering. Inequality constraints are imposed by accept/reject steps in the algorithm. The proposed approach provides samples representing …