scholarly journals Modeling and Control of Distillation Column in a Petroleum Process

2009 ◽  
Vol 2009 ◽  
pp. 1-14 ◽  
Author(s):  
Vu Trieu Minh ◽  
Ahmad Majdi Abdul Rani
Keyword(s):  
Linear Model ◽  
Distillation Column ◽  
Reference Model ◽  
Adaptive Controller ◽  
Modeling And Control ◽  
Reduced Order ◽  
Order Linear ◽  
Balance Structure ◽  
And Control ◽  
Model Reference Adaptive

This paper introduces a calculation procedure for modeling and control simulation of a condensate distillation column based on the energy balance structure. In this control, the reflux rate and the boilup rate are used as the inputs to control the outputs of the purity of the distillate overhead and the impurity of the bottom products. The modeling simulation is important for process dynamic analysis and the plant initial design. In this paper, the modeling and simulation are accomplished over three phases: the basic nonlinear model of the plant, the full-order linearised model, and the reduced-order linear model. The reduced-order linear model is then used as the reference model for a model-reference adaptive control (MRAC) system to verify the applicable ability of a conventional adaptive controller for a distillation column dealing with the disturbance and the model-plant mismatch as the influence of the plant feed disturbances.

scholarly journals Experimental Investigation of Adaptive Control Applied to HSFD Supported Rotors

1999 ◽  
Author(s):  
A. El-Shafei ◽  
M. El-Hakim
Keyword(s):  
Experimental Investigation ◽  
Adaptive Control ◽  
Reference Model ◽  
Computer Control ◽  
Adaptive Controller ◽  
Superior Performance ◽  
Order System ◽  
Squeeze Film ◽  
Run Up ◽  
Model Reference Adaptive

This paper describes the experimental application of adaptive control to Hybrid Squeeze Film Damper (HSFD) supported rotors. The HSFD has been shown to be an adaptive damper capable of providing infinite damper configurations between short and long damper configurations. Previously, theoretical investigations of the adaptive control of HSFD concentrated on the development of the model reference adaptive control (MRAC) method, as well as development of a nonlinear reference model. Simulations of the performance of the adaptive controller during run-up and coast-down indicated the superior performance of the adaptive controller. In this paper, the adaptive controller is tested on a multi-mode rotor. A test rig is designed and developed using computer control. A simple reference model is investigated consisting of a second order system. Three forms for adaptation gain are studied. The results of the experimental investigation illustrated the performance capabilities of the adaptive controller applied to the HSFD, and moreover indicated the possibility of simple design for the adaptive controller.

Decentralized Control of a Tower Crane

1999 ◽  
Author(s):  
Kiyoshi Takagi ◽  
Hidekazu Nishimura
Keyword(s):  
Decentralized Control ◽  
Three Dimensional ◽  
Reduced Order Model ◽  
Flexible Structure ◽  
Order Model ◽  
Modeling And Control ◽  
Reduced Order ◽  
Tower Crane ◽  
Three Dimensional Models ◽  
And Control

Abstract This paper deals with modeling and control of a crane mounted on a tower-like flexible structure. A fast transfer of the load causes the sway of the load rope and the vibration of the flexible structure. Our object is to control both the sway and the vibration by the inherent capability of the tower crane. This paper makes its three-dimensional models for simulation and reduced-order-model in order to design the decentralized control system. Then, we design the decentralized H∞ compensator and verify the efficiency by simulations and experiments.

scholarly journals Model Reduction Methods for Complex Network Systems

2020 ◽  
Vol 4 (1) ◽  
Author(s):  
X. Cheng ◽  
J.M.A. Scherpen
Keyword(s):  
Autonomous Systems ◽  
High Dimensional ◽  
Annual Review ◽  
Publication Date ◽  
Network Systems ◽  
Modeling And Control ◽  
Reduced Order ◽  
Reduction Methods ◽  
The Stability ◽  
And Control

Network systems consist of subsystems and their interconnections and provide a powerful framework for the analysis, modeling, and control of complex systems. However, subsystems may have high-dimensional dynamics and a large number of complex interconnections, and it is therefore relevant to study reduction methods for network systems. Here, we provide an overview of reduction methods for both the topological (interconnection) structure of a network and the dynamics of the nodes while preserving structural properties of the network. We first review topological complexity reduction methods based on graph clustering and aggregation, producing a reduced-order network model. Next, we consider reduction of the nodal dynamics using extensions of classical methods while preserving the stability and synchronization properties. Finally, we present a structure-preserving generalized balancing method for simultaneously simplifying the topological structure and the order of the nodal dynamics. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 4 is May 3, 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

scholarly journals Reduced Order Modeling and Control of Thin Film Growth in an HPCVD Reactor

2002 ◽  
Vol 62 (4) ◽  
pp. 1251-1280 ◽  
Author(s):  
G. M. Kepler ◽  
H. T. Banks ◽  
H. T. Tran ◽  
S. C. Beeler
Keyword(s):  
Thin Film ◽  
Film Growth ◽  
Reduced Order Modeling ◽  
Thin Film Growth ◽  
Modeling And Control ◽  
Reduced Order ◽  
And Control

Adapting Dynamic Braking of AC Motors to Varying Wheel/Rail Adhesion Condition

2013 ◽  
Author(s):  
Husain Ahmad ◽  
Mehdi Ahmadian
Keyword(s):  
Reference Model ◽  
Excitation Frequency ◽  
Adaptive Controller ◽  
Rolling Stock ◽  
Accurate Estimation ◽  
Model Reference ◽  
Braking Distance ◽  
Estimation And Control ◽  
Dynamic Braking ◽  
Model Reference Adaptive

Model reference adaptive control (MRAC) is developed to control the electrical excitation frequency of AC traction motors under various wheel/rail adhesion conditions during dynamic braking. More accurate estimation and control of train braking distance can allow more efficient braking of rolling stock, as well as spacing trains closer together for Positive Train Control (PTC). In order to minimize the braking distance of a train, dynamic braking forces need to be maximized for varying wheel/rail adhesion. The wheel/rail adhesion coefficient plays an important role in safe train braking. Excessively large dynamic braking can cause wheel lockup that can damage the wheels and rail, or may lead to large coupler forces, possibly causing derailment or broken components. In this study, a multibody formulation of a locomotive and three railcars is used to develop a model reference adaptive controller for adjusting the voltage excitation frequency of an AC motor such that the maximum dynamic braking is achieved, without locking up the wheels. A relationship between creep forces, creepages, and motor braking torque is established. This relationship is used to control the motor excitation frequency in order to closely follow the reference model that aims at achieving maximum allowable adhesion during dynamic braking. The results indicate that MRAC significantly improves braking distance while maintaining better wheel/rail adhesion and coupler dynamics during dynamic braking.

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