Nonlinear Stochastic Adaptive Control: a New Approach

Abstract

Abstract The paper presents new methods for nonlinear filtering, nonlinear parameter estimation and nonlinear prediction through a new concept named “intersample linearization”. The nonlinear filtering and parameter estimation methods shown in the paper are based on the algorithm of nonlinear prediction, which applies multi intersample linearization and approximates the nonlinear state evolution in increments computed with linear equations. Through multi-step ahead prediction, nonlinear model predictive control problems and optimum stochastic tracking problems may be solved.