Robust Anti-Windup Control Considering Multiple Design Objectives

A new saturation control technique is proposed to design multiobjective and robust anti-windup controllers for linear systems with input saturations. Based on the characterization of saturation nonlinearities and modeling uncertainties via integral quadratic constraints (IQCs), this method considers a mixed H2/H∞ performance indexes while maintaining dynamic constraints on the controller. The analysis and synthesis conditions are presented in terms of scaled linear matrix inequalities (LMIs). The proposed control algorithm can improve the performance of the input-constrained system while also guaranteeing robustness with respect to the modeling uncertainties. Finally, a numerical example is given to illustrate the effectiveness of the developed techniques

Uniform Approximate Estimation for Nonlinear Nonhomogenous Stochastic System with Unknown Parameter

The error bound in probability between the approximate maximum likelihood estimator (AMLE) and the continuous maximum likelihood estimator (MLE) is investigated for nonlinear nonhomogenous stochastic system with unknown parameter. The rates of convergence of the approximations for Itô and ordinary integral are introduced under some regular assumptions. Based on these results, the in probability rate of convergence of the approximate log-likelihood function to the true continuous log-likelihood function is studied for the nonlinear nonhomogenous stochastic system involving unknown parameter. Finally, the main result which gives the error bound in probability between the ALME and the continuous MLE is established