Robust constrained model predictive control based on parameter-dependent Lyapunov functions

The problem of robust constrained model predictive control (MPC) of systems with polytopic uncertainties is considered in this paper. New sufficient conditions for the existence of parameter-dependent Lyapunov functions are proposed in terms of linear matrix inequalities (LMIs), which will reduce the conservativeness resulting from using a single Lyapunov function. At each sampling instant, the corresponding parameter-dependent Lyapunov function is an upper bound for a worst-case objective function, which can be minimized using the LMI convex optimization approach. Based on the solution of optimization at each sampling instant, the corresponding state feedback controller is designed, which can guarantee that the resulting closed-loop system is robustly asymptotically stable. In addition, the feedback controller will meet the specifications for systems with input or output constraints, for all admissible time-varying parameter uncertainties. Numerical examples are presented to demonstrate the effectiveness of the proposed techniques

Pancreatic Exocrine Insufficiency: A Rare Cause of Nonalcoholic Steatohepatitis

This is an electronic version of an Article published in the American Journal of Gastroenterology 2008; 103(1): 245-246.ArticleAmerican journal of gastroenterology. 103(1): 245-246 (2008)journal articl

Modal analysis of an isolated nonlinear response mode using the Nyquist circle properties: Numerical case

Modal testing practitioners are well accustomed to FRFs which, nowadays, can be measured and analysed by a large variety of methods and tools. However, most of the tools for linear modal analysis are practically unusable when the frequency response is amplitude dependent. Hence, the methods based on the properties of the Nyquist circle become unavailable because of the loss of its circularity and completeness. Nevertheless, FRFs of well-isolated modes can still be processed by calculating the modal parameters for every pair of receptance points taken at equal amplitude either side the maximum response peak. The major limitation of this method is the absence of one branch of the response function due to unstable dynamics. The objective of this work is to show that incomplete FRF functions can be still processed to obtain the modal parameters. The method is benchmarked against a single degree of freedom both for linear and nonlinear response conditions