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.

Analytical design of constraint handling optimal two parameter internal model control for dead-time processes

2019 ◽  
Vol 36 (3) ◽  
pp. 356-367 ◽  
Author(s):  
Rodrigue Tchamna ◽  
Muhammad Abdul Qyyum ◽  
Muhammad Zahoor ◽  
Camille Kamga ◽  
Ezra Kwok ◽  
...  
Keyword(s):  
Internal Model ◽  
Dead Time ◽  
Internal Model Control ◽  
Constraint Handling ◽  
Analytical Design ◽  
Model Control ◽  
Two Parameter

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 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.

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