Experimental Results in the Modeling and Control of a Small Furnace

1981 ◽  
Vol 103 (4) ◽  
pp. 370-374
Author(s):  
R. S. Baheti ◽  
R. R. Mohler
Keyword(s):  
Linear Model ◽  
Binary Sequence ◽  
Power Input ◽  
Sample Temperature ◽  
Model Parameters ◽  
Input Output ◽  
Pseudorandom Binary Sequence ◽  
Modeling And Control ◽  
Small Furnace ◽  
And Control

A dynamic model is developed to control the temperature of a specimen in a laboratory furnace. The control variables are the power input to the furnace and the rate of airflow inside the chamber. For a constant airflow input, the furnace can be represented by a linear model and a static gain dependent on the sample temperature. The power input to the furnace is perturbed with a pseudorandom binary sequence and the model parameters are estimated from the input-output measurements. The controller parameters are selected to minimize the variance in the sample temperature.

Modeling and Control of a Complex Interacting Process

2011 ◽  
Vol 403-408 ◽  
pp. 3758-3762
Author(s):  
Subhajit Patra ◽  
Prabirkumar Saha
Keyword(s):  
Storage System ◽  
Linear Quadratic Regulator ◽  
Model Parameters ◽  
Linear Quadratic ◽  
Modeling And Control ◽  
Dynamic Matrix ◽  
Liquid Storage ◽  
Efficient Control ◽  
And Control

In this paper, two efficient control algorithms are discussed viz., Linear Quadratic Regulator (LQR) and Dynamic Matrix Controller (DMC) and their applicability has been demonstrated through case study with a complex interacting process viz., a laboratory based four tank liquid storage system. The process has Two Input Two Output (TITO) structure and is available for experimental study. A mathematical model of the process has been developed using first principles. Model parameters have been estimated through the experimentation results. The performance of the controllers (LQR and DMC) has been compared to that of industrially more accepted PID controller.

Input-Output Modeling and Control of the Departure Process of Busy Airports

2000 ◽  
Vol 8 (1) ◽  
pp. 1-32 ◽  
Author(s):  
Nicolas Pujet ◽  
Bertrand Delcaire ◽  
Eric Feron
Keyword(s):  
Input Output ◽  
Departure Process ◽  
Modeling And Control ◽  
And Control

Modeling and Control of an Electro-Hydraulic Poppet Valve

2004 ◽  
Author(s):  
Patrick Opdenbosch ◽  
Nader Sadegh ◽  
Wayne J. Book
Keyword(s):  
Mathematical Model ◽  
Control Valve ◽  
Model Parameters ◽  
Hydraulic Control ◽  
Nonlinear Mathematical Model ◽  
Modeling And Control ◽  
Poppet Valve ◽  
Control Scheme ◽  
Experimental Approaches ◽  
And Control

This paper explores the dynamic modeling of a novel two stage bidirectional poppet valve and proposes a control scheme that uses a Nodal Link Perceptron Network (NLPN). The dynamic nonlinear mathematical model of this Electro-Hydraulic Control Valve (EHCV) is based on the analysis of the interactions among its mechanical, hydraulic, and electromagnetic subsystems. A discussion on experimental approaches to determine the model parameters is included along with model validation results. Finally, the control scheme is developed by proposing that the states of the EHCV follow a set of desired states, which are calculated based upon the desired valve flow conductance coefficient KV. A simulation is presented at the end to verify the proposed control scheme.

scholarly journals A Novel Aerial Manipulator with Front Cutting Effector: Modeling, Control, and Evaluation

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Hao Xu ◽  
Zhong Yang ◽  
Guoxing Zhou ◽  
Luwei Liao ◽  
Changliang Xu ◽  
...  
Keyword(s):  
Control Method ◽  
External Disturbance ◽  
Model Parameters ◽  
Physical Interaction ◽  
Entire System ◽  
Modeling And Control ◽  
Aerial Manipulator ◽  
And Control ◽  
Contact Position ◽  
System Movement

This paper proposes a novel aerial manipulator with front cutting effector (AMFCE) to address the aerial physical interaction (APhI) problem. First, the system uncertainty and external disturbance during the system movement and contact operation are estimated by modeling the entire robot and contact position. Next, based on the established model, the nonlinear disturbance observer (NDO) is used to estimate and compensate the unknown external disturbance of the system and the uncertainty of the model parameters in real time. Then, the nonsingular terminal synovial membrane control method is used to suppress the part that is difficult to estimate. Finally, a controller which is suitable for the movement and operation of the entire system is designed. The controller’s performance is verified through experiments, and the results show that the design, modeling, and control of the entire system can achieve the APhI.

scholarly journals A Novel Data-Driven Modeling and Control Design Method for Autonomous Vehicles

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 517
Author(s):  
Dániel Fényes ◽  
Balázs Németh ◽  
Péter Gáspár
Keyword(s):  
Autonomous Vehicles ◽  
Design Method ◽  
Nonlinear Modeling ◽  
Autonomous Vehicle ◽  
Control Design ◽  
Path Following ◽  
Simulation Software ◽  
Model Parameters ◽  
Modeling And Control ◽  
And Control

This paper presents a novel modeling method for the control design of autonomous vehicle systems. The goal of the method is to provide a control-oriented model in a predefined Linear Parameter Varying (LPV) structure. The scheduling variables of the LPV model through machine-learning-based methods using a big dataset are selected. Moreover, the LPV model parameters through an optimization algorithm are computed, with which accurate fitting on the dataset is achieved. The proposed method is illustrated on the nonlinear modeling of the lateral vehicle dynamics. The resulting LPV-based vehicle model is used for the control design of path following functionality of autonomous vehicles. The effectiveness of the modeling and control design methods through comprehensive simulation examples based on a high-fidelity simulation software are illustrated.

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.

Modeling and Control of Swing Oscillation of Underactuated Indoor Miniature Autonomous Blimps

2020 ◽  
Vol 09 (01) ◽  
pp. 73-86
Author(s):  
Qiuyang Tao ◽  
Tun Jian Tan ◽  
Jaeseok Cha ◽  
Ye Yuan ◽  
Fumin Zhang
Keyword(s):  
Control System ◽  
Center Of Mass ◽  
Position Estimation ◽  
Model Parameters ◽  
Control System Design ◽  
Georgia Tech ◽  
Hovering Flight ◽  
Modeling And Control ◽  
Physical Measurements ◽  
And Control

Swing oscillation is widely observed among indoor miniature autonomous blimps (MABs) due to their underactuated design and unique aerodynamic shape. This paper presents the modeling, identification and control system design that reduce the swing oscillation of an MAB during hovering flight. We establish a dynamic model to describe the swing motion of the MAB. The model parameters are identified from both physical measurements, computer modeling and experimental data captured during flight. A control system is designed to stabilize the swing motion with features including low latency and center-of-mass (CM) position estimation. The modeling and control methods are verified with the Georgia-Tech Miniature Autonomous Blimp (GT-MAB) during hovering flight. The experimental results show that the proposed methods can effectively reduce the swing oscillation of GT-MAB.

scholarly journals Application of monod two-substrate kinetics with an intermediate for anaerobic co-digestion of distillery wastewater and molasses/glycerol waste in batch experiments

2020 ◽  
Vol 15 (4) ◽  
pp. 1068-1082
Author(s):  
K. Phayungphan ◽  
N. Rakmak ◽  
A. Promraksa
Keyword(s):  
Model Parameters ◽  
Batch Experiments ◽  
Microbial Activities ◽  
Monod Kinetics ◽  
Modeling And Control ◽  
Multiple Substrates ◽  
Complex Process ◽  
Distillery Wastewater ◽  
And Control ◽  
Substrate Kinetics

Abstract Anaerobic digestion is a highly complex process, particularly in co-digestion between poorly-defined, complex co-substrates like distillery wastewater, molasses, and crude glycerine. Thus, in this article, the authors tackled the problems by using Monod two-substrate with an intermediate (M2SI) model to represent accumulated biomethane evolution (ABE) obtained from the co-substrates, including easily degradable, slowly degradable substrates and intermediate. The M2SI model predictions were compared with the traditional Monod model's simulation results to clarify an outstanding of the present model in the aspect of modeling and control. Different behaviors of ABE curves from batch experiments were used to calibrate the M2SI model prediction with sensitivity analysis of the model parameters. It was found that the M2SI model gives a correct trend to describe the co-digestion process with multiple substrates and complex microbial activities with satisfactory fitting accuracy. At the same time, simple Monod kinetics have a good fit for dilute pure distillery wastewater, but the estimated microbial growth kinetics were counterintuitive. Therefore, the M2SI Model has a broader range of applications for co-digestion dealing with the complexity of multiple microbial activities to consume inherently complex or artificial co-substrates.

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