Acoustic Modeling and Control of Conical Enclosures

2003 ◽  
Vol 125 (1) ◽  
pp. 2-11 ◽  
Author(s):  
Kevin M. Farinholt ◽  
Donald J. Leo
Keyword(s):  
Boundary Condition ◽  
System Analysis ◽  
State Space Model ◽  
Acoustic Modeling ◽  
Conic Section ◽  
Feedback Channel ◽  
Actuator Dynamics ◽  
Modeling And Control ◽  
Resonance Frequencies ◽  
And Control

Acoustic modeling and control of conical enclosures with an actuator boundary condition is presented. Acoustic impedances are coupled with electrical and mechanical actuator dynamics to generate a coupled state-space model of the system. Analysis of the acoustic impedance illustrates that pole-zero cancellation occurs when the length of the conic section becomes large compared to the distance from the apex to the actuator boundary condition. Used as a platform for control design, positive position feedback is applied for acoustic attenuation. The model predicts the first four resonance frequencies to within 1.75 percent of experimentally measured values. Standing waveforms are presented and related to the effects of the actuator boundary condition. A feedback controller is implemented on an experimental testbed with global reductions of 38.4 percent or 4.2 dB observed over a 50-400 Hz frequency range. Experimental results demonstrate that global sound attenuation is possible with a single feedback channel.

Multivariable modeling and control of an activated sludge process

1998 ◽  
Vol 37 (12) ◽  
pp. 149-156 ◽  
Author(s):  
Carl-Fredrik Lindberg
Keyword(s):  
Activated Sludge ◽  
Nitrate Concentration ◽  
State Space Model ◽  
Activated Sludge Process ◽  
Invariant State ◽  
Linear Quadratic ◽  
Modeling And Control ◽  
Space Model ◽  
And Control ◽  
Time Invariant

This paper contains two contributions. First it is shown, in a simulation study using the IAWQ model, that a linear multivariable time-invariant state-space model can be used to predict the ammonium and nitrate concentration in the last aerated zone in a pre-denitrifying activated sludge process. Secondly, using the estimated linear model, a multivariable linear quadratic (LQ) controller is designed and used to control the ammonium and nitrate concentration.

scholarly journals Modeling and Control of Cutter Vibration in the Presence of Random Distribution of Microhardness of Workpiece and Nonlinear Cutting Forces in Lathe Process

2011 ◽  
Vol 2011 ◽  
pp. 1-11 ◽  
Author(s):  
A. H. El-Sinawi
Keyword(s):  
Cutting Force ◽  
Cutting Forces ◽  
Random Distribution ◽  
Orthogonal Cutting ◽  
Nonlinear Dynamic Model ◽  
Linear Quadratic ◽  
Workpiece Material ◽  
Actuator Dynamics ◽  
Modeling And Control ◽  
And Control

This work presents a comprehensive approach to the control of tool's position, in the presence of machine tool structure vibration, nonlinear cutting force, and random tool vibration due to random distribution of microhardness of workpiece material. The controller is combination of Proportional and linear quadratic gaussian- (P-LQG-) type constructed from an augmented model of both tool-actuator dynamics and a nonlinear dynamic model relating tool displacement to cutting forces. The latter model is obtained using black-box system identification of experimental orthogonal cutting data in which tool displacement is the input and cutting force is the output. The controller is evaluated and its performance is demonstrated.

Modeling and Control of Biochemical Reactor

2013 ◽  
Vol 791-793 ◽  
pp. 818-821
Author(s):  
Shi Li ◽  
Xi Ju Zong ◽  
Yan Hu
Keyword(s):  
Transfer Function ◽  
State Space ◽  
State Space Model ◽  
Internal Model Control ◽  
Transfer Function Model ◽  
Function Model ◽  
Modeling And Control ◽  
Space Model ◽  
Biochemical Reactor ◽  
And Control

This paper is concerns with the study of modeling and control of biochemical reactor. Firstly, a mathematical model is established for a typical biochemical reactor, the mass balance equations are established individually for substrate concentration and biomass concentration. Then, the model is linearized at the steady-state point, two linear models are derived: state space model and transfer function model. The transfer function model is used in internal model control (IMC), where the filter parameter is selected and discussed. The state space model is applied in model predictive control (MPC), where controller parameters of control prediction horizon length and constraint of control variable variation are discussed.

Modeling and Control of Sludge Pyrolysis in a Fluidized Bed Reactor

2013 ◽  
Vol 846-847 ◽  
pp. 69-72
Author(s):  
Shi Li ◽  
Xi Ju Zong ◽  
Yan Hu
Keyword(s):  
Transfer Function ◽  
State Space ◽  
Fluidized Bed ◽  
State Space Model ◽  
Fluidized Bed Reactor ◽  
Transfer Function Model ◽  
Function Model ◽  
Modeling And Control ◽  
Space Model ◽  
And Control

This paper is concerns with the study of modeling and control of sludge pyrolysis in a fluidized bed reactor. Firstly, a mathematical model is established for sludge pyrolysis in a fluidized bed furnace, mass balance and energy equations are established. Then, the model is linearized at the steady-state point, two linear models are derived: state space model and transfer function model. The transfer function model is used in internal model control (IMC), where the filter parameter is selected and discussed. The state space model is applied in model predictive control (MPC), where controller parameters of prediction horizon length and control horizon length are discussed.

Research of Modeling and Control Method for Electromagnetic Levitation System

2014 ◽  
Vol 651-653 ◽  
pp. 812-817 ◽  
Author(s):  
Jian Guo Zheng ◽  
Zhi Gang Zou ◽  
Hui Zeng ◽  
Tian Peng He
Keyword(s):  
Control Method ◽  
State Space Model ◽  
Electromagnetic Levitation ◽  
Open Loop ◽  
Modeling And Control ◽  
Control Approach ◽  
Control Scheme ◽  
Levitation System ◽  
And Control ◽  
Assignment Scheme

There has been wide interest in the control scheme of the electromagnetic levitation system due to its disadvantages of nonlinearity and open-loop uncertainty. A typical coil-ball levitation system is used in research. The forces of the ball are analyzed and a dynamic model of the whole electromagnetic levitation system is established. Based on the nonlinear state-space model, the coil-ball system is linearized and then a LQR control approach is proposed. Simulation results show that, compared with conventional pole assignment scheme, the electromagnetic levitation system under the proposed control approach gets a better performance, including smaller overshot and faster response.

MODELING AND CONTROL OF DIMENSIONAL QUALITY OF A SERIAL MULTI-STATION MACHINING SYSTEM

2006 ◽  
Vol 13 (05) ◽  
pp. 399-419 ◽  
Author(s):  
SHICHANG DU ◽  
LIFENG XI ◽  
ERSHUN PAN ◽  
JIANJUN SHI ◽  
C. RICHARD LIU
Keyword(s):  
State Space ◽  
State Space Model ◽  
Machining Processes ◽  
Modeling And Control ◽  
Engineering Theory ◽  
Machining Errors ◽  
Proposed Model ◽  
Machining System ◽  
Linear State ◽  
And Control

Modeling and control of dimensional quality is one of deciding factors in current manufacturing competitions, and has always presented a great challenge to both scientists and engineers since for a multi-station machining system, the final product variation is an accumulation from all stations, and the complex non-linear relationship exits between dimensional quality and machining errors. This paper develops a linear state space model using homogeneous transformation to capture the influence of machined errors on dimensional quality, and the explicit expressions for system matrices of the model are explored. The proposed model employs a linear state space form, facilitating the use of the achievements of control theory, information technology and system engineering theory to support engineers supervisory control of physical machining processes, and it also can be used as an analytical engineering tool for efficient and effective faults diagnosis, system plan and design, and optimal sensors allocation. A real machining case illustrates the proposed model.

State-Space Modeling and Control of Acoustic Systems

2001 ◽  
Author(s):  
Reza Kashani ◽  
Asim S. Mohammad
Keyword(s):  
State Space ◽  
State Space Model ◽  
Feedback Controller ◽  
Mode Shapes ◽  
Acoustic System ◽  
Modeling And Control ◽  
Space Modeling ◽  
State Space Modeling ◽  
Space Formulation ◽  
And Control

Abstract Synthesis and analysis of model-based controllers for an acoustic system require the state-space formulation of the system. The use of modal data, i.e. resonant frequencies, model damping ratios, and mode shapes, in constructing state-space model of an aoucstic system is described in this paper. Moreover, a simple, low-order feedback controller for adding damping to and/or cancelling offending noise in an acoustic system is introduced. State-space modeling, as well as the effectiveness of the proposed feedback controller are demonstrated through numerical and experimental, illustrative examples.

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