Operating point selection in multimodel controller design

2004 ◽  
Author(s):  
Wen Tan ◽  
H.J. Marquez ◽  
Tongwen Chen
Keyword(s):  
Controller Design ◽  
Operating Point ◽  
Point Selection

Operating point selection for primary and secondary users in cognitive radio networks

2009 ◽  
Vol 53 (8) ◽  
pp. 1158-1170 ◽  
Author(s):  
Xavier Gelabert ◽  
Ian F. Akyildiz ◽  
Oriol Sallent ◽  
Ramon Agustí
Keyword(s):  
Cognitive Radio ◽  
Cognitive Radio Networks ◽  
Radio Networks ◽  
Operating Point ◽  
Point Selection ◽  
Secondary Users ◽  
Selection For ◽  
Primary And Secondary Users

The Importance of Nominal Operating Point Selection in Self-Optimizing Control

2016 ◽  
Vol 55 (27) ◽  
pp. 7381-7393 ◽  
Author(s):  
Eduardo S. Schultz ◽  
Jorge O. Trierweiler ◽  
Marcelo Farenzena
Keyword(s):  
Operating Point ◽  
Point Selection ◽  
Optimizing Control

Controller design point selection for linearized gain scheduling

2017 ◽  
Author(s):  
Sebastian Fleischmann ◽  
Spilios Theodoulis ◽  
Edouard Laroche ◽  
Elmar Wallner ◽  
Jean-Philippe Harcaut
Keyword(s):  
Controller Design ◽  
Gain Scheduling ◽  
Point Selection ◽  
Design Point ◽  
Selection For

Design of State Space Controllers for Industrial Twin Shaft Gas Turbines

2005 ◽  
Author(s):  
Markus Beukenberg ◽  
Michael Brodmann ◽  
Hans Weibel ◽  
Detlef Mu¨ller
Keyword(s):  
State Space ◽  
Gas Turbines ◽  
Controller Design ◽  
Mathematic Model ◽  
Pole Placement ◽  
Operating Point ◽  
Design Procedures ◽  
Industrial Gas Turbines ◽  
Linear State ◽  
Complex Mathematical Model

This paper depicts the development of a new control strategy for industrial gas turbines to improve the control accuracy in the entire operating range. In the first step, a complex mathematical model has been developed, which is implemented into the controller dynamic simulation. An automatic operating point dependent linearization process permits the model to be displayed in a linear state space description. Three established controller design procedures have been applied to the process. In the past, only a small number of state space control designs have been presented for industrial gas turbines. These approaches use low order mathematical descriptions, which often do not describe the system behavior in detail. This paper presents a controller design for a more detailed mathematic model of the 15th order. It is indicated, that certain controller designs are difficult to realize or even fail. These effects result from unfavourable numerical conditions (depending on the operating point) in combination with the high order of the approximated linear system description. The tested pole placement designs show favorable closed loop system dynamic behavior and were improved by adding an integrating part to the controller.

scholarly journals Systematic Controller Design Methodology for Variable-Speed Wind Turbines

2000 ◽  
Vol 24 (3) ◽  
pp. 169-187 ◽  
Author(s):  
M. Maureen Hand ◽  
Mark J. Balas
Keyword(s):  
Linear Model ◽  
Wind Turbines ◽  
Controller Design ◽  
Design Approach ◽  
Systematic Design ◽  
Variable Speed ◽  
Point Selection ◽  
Model Based ◽  
Non Linear ◽  
Linearization Point

Variable-speed, horizontal axis wind turbines use blade-pitch control to meet specified objectives for three regions of operation. This paper provides a guide for controller design for the constant power production regime. A simple, rigid, non-linear turbine model was used to systematically perform trade-off studies between two performance metrics. Minimization of both the deviation of the rotor speed from the desired speed and the motion of the actuator is desired. The robust nature of the proportional-integral-derivative controller is illustrated, and optimal operating conditions are determined. Because numerous simulation runs may be completed in a short time, the relationship between the two opposing metrics is easily visualized. Traditional controller design generally consists of linearizing a model about an operating point. This step was taken for two different operating points, and the systematic design approach was used. The surfaces generated by the systematic design approach using the two linear models are similar to those generated using the non-linear model. The gain values selected using either linear model-based design are similar to those selected using the non-linear model-based design. The linearization point selection does, however, affect the turbine performance. Inclusion of complex dynamics in the simulation may exacerbate the small differences evident in this study. Thus, knowledge of the design variation due to linearization point selection is important.

Sign in / Sign up

Export Citation Format

Share Document