Internal Model Control Design for Autothermal Reforming System

2014 ◽  
Vol 627 ◽  
pp. 236-240 ◽  
Author(s):  
Chananchai Wutthithanyawat ◽  
Nawadee Srisiriwat
Keyword(s):  
Control System ◽  
Temperature Control ◽  
Reaction Temperature ◽  
Internal Model ◽  
Controller Design ◽  
Autothermal Reforming ◽  
Internal Model Control ◽  
Cold Weather ◽  
Model Control ◽  
Feed Temperature

This paper focuses on the control system design for a process of autothermal reforming (ATR) of ethanol. The targeted application is within an on-board fuel processor of ATR operating at the adiabatic reaction temperature for hydrogen production. An internal model control (IMC) method is designed for controlling the adiabatic reaction temperature of ATR reactor by manipulating the input air flow rate. Two strategies of controller design with and without the feed temperature control of the preheater unit are proposed in order to determine the suitable controller system as the surrounding temperature is a major disturbance for cold weather. Theoretical analysis demonstrates that IMC strategy can achieve desired performance. Two loops of control system of the ATR process combined with the feed temperature control can compensate the surrounding temperature better than without the feed temperature control.

Robust Controllers for Pulse-Width-Modulated D.C./D.C. Converters Using Internal-Model-Control Design

1993 ◽  
Vol 207 (3) ◽  
pp. 127-134 ◽  
Author(s):  
D Garabandić ◽  
T Petrović
Keyword(s):  
Model Uncertainty ◽  
Pulse Width ◽  
Internal Model ◽  
Controller Design ◽  
Optimization Method ◽  
Internal Model Control ◽  
Linear Feedback ◽  
Pulse Width Modulated ◽  
Linear Feedback Controller ◽  
Model Control

A linear feedback controller for pulse-width-modulated d.c./d.c. regulator is designed using a frequency domain optimization method based on internal-model-control theory. This method aims to produce suboptimal low-order controllers which are ‘robust’, in the sense that the closed-loop system is guaranteed to meet stability objectives in the presence of model uncertainty. The small-signal model of a d.c./d.c. converter is used for the controller design. The model uncertainty description derived here is based on experiments and non-linear modelling. The result of the synthesis is a family of controllers, and each member of this family satisfies the robust control objectives. All controllers have a multi-loop structure including two feedback loops and one feedforward loop. A detailed design of the controller, including experimental results, is presented.

Attitude Controller Design of Multiple Independently Targeted Reentry Vehicle Based on Internal Model Control

2013 ◽  
Vol 462-463 ◽  
pp. 809-814
Author(s):  
Fei Zhao ◽  
Fan Li ◽  
Jian Hui Zhao
Keyword(s):  
Control System ◽  
Attitude Control ◽  
Internal Model ◽  
Internal Model Control ◽  
Attitude Dynamics ◽  
Attitude Control System ◽  
Reentry Vehicle ◽  
Model Control ◽  
Internal Model Controller ◽  
Attitude Controller

A Multiple Independently Targeted Reentry Vehicle (MIRV) is a ballistic missile payload containing several warheads each capable of hitting one of a group of targets. In the process of missile flight control, the release of warheads brings about coupling to the missile attitude control system which will lower the flight stability. In order to solve this problem, a missile attitude controller, which combined the α-order integral inverse system with internal model principle, was presented. Firstly, determine the Post Boost Vehicle (PBV) attitude dynamics model. Then, combine the linearization of attitude dynamics equation with feed-forward decoupling method to implement the attitude decoupling. Finally, a two-degree of freedom (TOF) multivariable internal model controller was set up to optimize the control system performance. Simulation results show that the coupling of attitude control system has been eliminated. Compared with the original system, the internal model controller provides the control system better input-tracking performance, robust stability and interference suppression capacity.

scholarly journals Design of Internal Model Control Based on an Optimal Control for a Servo System

2015 ◽  
Vol 2015 ◽  
pp. 1-5 ◽  
Author(s):  
Hiromitsu Ogawa ◽  
Ryo Tanaka ◽  
Takahiro Murakami ◽  
Yoshihisa Ishida
Keyword(s):  
Optimal Control ◽  
Control System ◽  
Transfer Function ◽  
Internal Model ◽  
Dead Time ◽  
Servo System ◽  
Previous Method ◽  
Internal Model Control ◽  
Model Control ◽  
Disturbance Response

This paper describes a design of internal model control based on an optimal control for a servo system. The control system has the feedback based on the proposed disturbance compensator in the disturbance response. The compensator is designed to become the denominator of the transfer function without a dead time in the disturbance responses. The disturbance response of the proposed method is faster than that of the previous method.

scholarly journals An Internal Model Controller for Three-Phase APF Based on LS-Extreme Learning Machine

2014 ◽  
Vol 8 (1) ◽  
pp. 717-722
Author(s):  
Zhenhua Shao ◽  
Tianxiang Chen ◽  
Li-an Chen ◽  
Hong Tian
Keyword(s):  
Control System ◽  
Least Squares ◽  
Extreme Learning Machine ◽  
Internal Model ◽  
Internal Model Control ◽  
Support Vector ◽  
Three Phase ◽  
Model Control ◽  
Internal Model Controller ◽  
Learning Machine

Aiming at the problem that the three-phase APF’s dynamic model is a multi-variable, nonlinear and strong coupling system, an internal model controller for three-phase APF based on LS-Extreme Learning Machine is studied in this paper. As a novel single hidden layer feed-forward neural networks, extreme learning machine (ELM) has several advantages: simple net structural, fast learning speed, good generalization performance and so on. In order to improve the controller’s dynamic responses, a least squares extreme learning machine for internal model control is proposed. A least squares ELM regression (LS-ELMR) model for the three-phase APFS on-line monitoring was built from external factors with in-out datum. Moreover, the relative stable error is presented to evaluate the system performance and the features for the internal model control system based on extreme learning machine, neural network, kernel ridge regress and support vector machine. The experimental results show that the LS-internal model control system based on extreme learning machine has good dynamic performance and strong filtering result.

Sign in / Sign up

Export Citation Format

Share Document