Sample Length-adaptive Prediction Scheme for Parameter Estimation in Multi-dimensional Rate Control

Observer-Side Parameter Estimation For Adaptive Control

of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science OBSERVER-SIDE PARAMETER ESTIMATION FOR ADAPTIVE CONTROL By Jason Nezvadovitz August 2017 Chair: Warren Dixon Major: Mechanical Engineering In adaptive control, a controller is precisely designed for a certain model of the system, but that model’s...

Parameter estimation aspects in adaptive control

This paper provides a solution to the convergence of the parameter estimates to their true values in an ideal adaptive regulation context. The key design feature consists in the use of an asymptotically vanishing internally generated exciting sequence. 1. Introduction IN THIS paper, the following question is addressed: given a known order linear time invariant system, how does one design an ada...

Stochastic Adaptive Control via Consistent Parameter Estimation

The paper introduces novel techniques for achieving global convergence results and improving transient performance in stochastic adaptive control. For example, there is introduced switching between a least squares and an extended least squares parameter estimation algorithm according to an ill-conditioning measure, and there is appropriate selection of external persistently exciting signals, th...

Distributed Incremental Least Mean-Square for Parameter Estimation using Heterogeneous Adaptive Networks in Unreliable Measurements

Adaptive networks include a set of nodes with adaptation and learning abilities for modeling various types of self-organized and complex activities encountered in the real world. This paper presents the effect of heterogeneously distributed incremental LMS algorithm with ideal links on the quality of unknown parameter estimation. In heterogeneous adaptive networks, a fraction of the nodes, defi...

Parameter Estimation for Multi-dimensional Filtered Poisson Processes