A comparative study on a novel model-based PID tuning and control mechanism for nonlinear systems

2009 ◽  
Vol 20 (13) ◽  
pp. 1483-1501 ◽  
Author(s):  
S. Iplikci
Keyword(s):  
Nonlinear Systems ◽  
Comparative Study ◽  
Control Mechanism ◽  
Pid Tuning ◽  
Model Based ◽  
And Control ◽  
Novel Model

scholarly journals A Model-Based Method for Estimating the Attitude of Underground Articulated Vehicles

Sensors ◽  
2019 ◽  
Vol 19 (23) ◽  
pp. 5245 ◽  
Author(s):  
Lulu Gao ◽  
Fei Ma ◽  
Chun Jin
Keyword(s):  
Field Test ◽  
Degrees Of Freedom ◽  
Kinematic Model ◽  
Measurement Unit ◽  
Model Based ◽  
Proposed Model ◽  
Articulated Vehicles ◽  
Free Environment ◽  
And Control ◽  
Novel Model

This paper presents a novel model-based method for estimating the attitude of underground articulated vehicles (UAV). We selected the Load–Haul–Dump (LHD) vehicle as our application object, as it is a typical UAV. First, we established the involved models of the LHD vehicle, including a kinematic model, the linear and angular constraints of a center articulation model, and a dynamic four degrees-of-freedom (DOF) yaw model. Second, we designed a Kalman filter (KF) to integrate the kinematic and constraint models with the data from an inertial measurement unit (IMU), overcoming gyroscope drift and disturbances in external acceleration. In addition, we designed another KF to estimate the yaw based on the dynamic yaw model. The accuracy of the estimations was further enhanced by data fusion. Then, the proposed method was validated by a simulation and a field test under different dynamic conditions. The errors in the estimation of roll, pitch, and yaw were 3.8%, 2.4%, and 4.2%, respectively, in the field test. The estimated longitudinal acceleration was used to obtain the velocity of the LHD vehicle; the error was found to be 1.2%. A comparison of these results to those of other methods showed that the proposed method has high precision. The proposed model-based method will greatly benefit the location, navigation, and control of UAVs without any artificial infrastructure in a global positioning system (GPS)-free environment.

A model-based methodology to predict the compressor behaviour for the simulation of turbocharged engines

2011 ◽  
Vol 226 (4) ◽  
pp. 560-574 ◽  
Author(s):  
M Taburri ◽  
F Chiara ◽  
M Canova ◽  
Y-Y Wang
Keyword(s):  
System Simulation ◽  
Predictive Ability ◽  
Model Based ◽  
Modelling Techniques ◽  
Compressor Performance ◽  
Conservation Principles ◽  
Engine System ◽  
And Control ◽  
Novel Model ◽  
Efficiency Data

Modelling the flow and efficiency of turbochargers for engine system simulation and control applications is an established practice that relies on the steady-state maps provided by manufacturer suppliers. However, as often occurs in practice, only a limited fraction of data is available in the compressor and turbine operating domain. For this reason, several modelling techniques have been proposed to interpolate and extrapolate flow and efficiency data. Most of the modelling approaches, based on black- or grey-box approaches, have limited predictive ability and typically low accuracy in off-design conditions, such as at engine idle or low engine speed. The current paper presents a novel model-based approach for overcoming the sparse nature of the available compressor maps, characterizing the flow and efficiency outputs of automotive centrifugal compressors by using extrapolation methods that are physically consistent with the conservation principles and actual behaviour of the system. The approach relies on a predictive model based on the thermodynamic analysis of a centrifugal compressor stage. The model builds upon the mass, energy, and entropy balance equations for compressible fluids. Specific sub-models are then introduced to account for the effects of slip phenomena, incidence losses, friction, and heat transfer losses, leading to high fidelity and predictive ability in off-design conditions. A detailed analysis of the model calibration and validation process is presented, utilizing data from two different automotive compressors. Finally, the procedure described is applied to characterize the compressor performance in engine system simulation, in comparison with a conventional (data-driven) model.

Development of a Jacobian Module for Advanced Pulp and Paper Simulation and Control

TAPPI Journal ◽  
2009 ◽  
Vol 8 (1) ◽  
pp. 4-11
Author(s):  
MOHAMED CHBEL ◽  
LUC LAPERRIÈRE
Keyword(s):  
Control System ◽  
Nonlinear Behavior ◽  
Simulation Software ◽  
Pulp And Paper ◽  
Pid Controllers ◽  
Tuning Parameters ◽  
Pid Tuning ◽  
Fixed Set ◽  
And Control ◽  
Operating Points

Pulp and paper processes frequently present nonlinear behavior, which means that process dynam-ics change with the operating points. These nonlinearities can challenge process control. PID controllers are the most popular controllers because they are simple and robust. However, a fixed set of PID tuning parameters is gen-erally not sufficient to optimize control of the process. Problems related to nonlinearities such as sluggish or oscilla-tory response can arise in different operating regions. Gain scheduling is a potential solution. In processes with mul-tiple control objectives, the control strategy must further evaluate loop interactions to decide on the pairing of manipulated and controlled variables that minimize the effect of such interactions and hence, optimize controller’s performance and stability. Using the CADSIM Plus™ commercial simulation software, we developed a Jacobian sim-ulation module that enables automatic bumps on the manipulated variables to calculate process gains at different operating points. These gains can be used in controller tuning. The module also enables the control system designer to evaluate loop interactions in a multivariable control system by calculating the Relative Gain Array (RGA) matrix, of which the Jacobian is an essential part.

Model-based programming tools for integrated monitoring, simulation, diagnosis and control

1993 ◽  
Author(s):  
Gabor Karsai ◽  
Samir Padalkar ◽  
Hubertus Franke ◽  
Janos Sztipanovits
Keyword(s):  
Integrated Monitoring ◽  
Model Based ◽  
Programming Tools ◽  
And Control
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