State Estimation Using Microprocessors for Process Supervision and Control

Author(s):  
Andrea Holmberg ◽  
Jussi Orava
1978 ◽  
Vol 27 (4) ◽  
pp. 621-637 ◽  
Author(s):  
YOSHIKAZU SAWARAGI ◽  
TAKASHI SOEDA ◽  
YUTAKA TOMITA ◽  
ISAO IMAI

Author(s):  
Adamu Yebi ◽  
Beshah Ayalew ◽  
Satadru Dey

This article discusses the challenges of non-intrusive state measurement for the purposes of online monitoring and control of Ultraviolet (UV) curing processes. It then proposes a two-step observer design scheme involving the estimation of distributed temperature from boundary sensing cascaded with nonlinear cure state observers. For the temperature observer, backstepping techniques are applied to derive the observer partial differential equations along with the gain kernels. For subsequent cure state estimation, a nonlinear observer is derived along with analysis of its convergence characteristics. While illustrative simulation results are included for a composite laminate curing application, it is apparent that the approach can also be adopted for other UV processing applications in advanced manufacturing.


2022 ◽  
Author(s):  
Chengwei Wu ◽  
Weiran Yao ◽  
Guanghui Sun ◽  
Ligang Wu

Author(s):  
S. G. Tzafestas ◽  
S. Abu El Ata-Doss ◽  
G. Papakonstantinou

2015 ◽  
Vol 15 (5) ◽  
pp. 5-16
Author(s):  
H. Abouaïssa ◽  
H. Majid

Abstract The studies presented in this paper deal with traffic control in case of missing data and/or when the loop detectors are faulty. We show that the traffic state estimation plays an important role in traffic prediction and control. Two approaches are presented for the estimation of the main traffic variables (traffic density and mean speed). The state constructors obtained are then used for traffic flow control. Several numerical simulations show very promising results for both traffic state estimation and control.


2018 ◽  
Vol 56 (2) ◽  
pp. 105-123 ◽  
Author(s):  
EA Zamora-Cárdenas ◽  
A Pizano-Martínez ◽  
JM Lozano-García ◽  
VJ Gutiérrez-Martínez ◽  
R Cisneros-Magaña

State estimation is one of the most important processes to perform a reliable monitoring and control of the steady-state operating condition of modern electric power systems; thus, it is currently a fundamental part in the development of research to enhance the monitoring and security of the smart grids operation. This important topic is taught in advanced courses of operation and control of power systems, for graduate and undergraduate power engineering students. However, the most used software packages for simulation and analysis of power systems by researchers, students, and educators have put little attention on the state estimation module. Due to this fact, this paper proposes an approach to develop the computational implementation of a practical educational tool for state estimation of electric power systems using the MATLAB optimization toolbox. In this proposal, the formulation of the state estimation problem consists of developing a general digital code to implement an objective function based on the weighted least squares method. While the lsqnonlin function of the MATLAB optimization toolbox solves the formulated state estimation problem. Simplifying both research and educational processes, this tool helps graduate and undergraduate students to improve learning, understanding, and the times of implementation and development of research in state estimation. Simulations of an equivalent model of the Mexican interconnected power system consisting of 190 buses and 46 machines are used to test and validate the proposal performance.


1993 ◽  
Vol 38 (5) ◽  
pp. 873-890 ◽  
Author(s):  
Nicholas M. Avouris ◽  
Marc H. Van Liedekerke ◽  
Georgios P. Lekkas ◽  
Lynne E. Hall

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