Abstract: The problem of sequential filtering of a chaotic random process is considered in the context of the general problem of controlling the state of a dynamic object in an unstable immersion environment. In conditions of chaotic dynamics, traditional sequential processing of observations either does not provide the required level of smoothing, or leads to a significant lagging shift of the estimate of the conditional average. The paper provides a numerical analysis of the effectiveness of algorithms for identifying the system component of chaotic processes based on the terminal indicator of management effectiveness. Several filtering algorithms with improved characteristics according to criteria for smoothing quality and control quality indicators based on the system component isolated from noisy observations are proposed.