ETD Collection

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Subject: search.filters.subject.Parameter estimation

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    Calibration of discrete element modelling parameters for bulk materials handling applications
    (2018) Guya, Solomon Ramas
    The Discrete Element Method (DEM) models and simulates the flow of gran ular material through confining geometry. The method has the potential to significantly reduce the costs associated with the design and operation of bulk materials handling equipment. The challenge, however, is the difficulty of determining the required input parameters. Previous calibration approaches involved direct measurements and random parameter search. The aim of this research was to develop a sequential DEM calibration framework, identify ap propriate calibration experiments and validate the framework on real flows in a laboratory-scale silo and chute. A systematic and sequential DEM calibration framework was developed. The framework consists of categorising the DEM input parameters into three cat egories of determining the directly measured input parameters, obtaining the literature acquired input parameters, and linking physical experiments with DEM simulations to obtain the calibrated parameter values. The direct mea surement parameters comprised the coefficients of restitution and the particle to wall surface coefficient of rolling friction. Literature obtained parameters were the Young’s Modulus and Poisson’s ratio. The calibrated parameters comprised the particle to wall surface coefficient of sliding friction calibrated from the wall fiction angle, the particle to particle friction coefficients (sliding and rolling) calibrated from two independent angles of repose, particle den sity calibrated from bulk density, and adhesion and cohesion energy densities. The framework was then tested using iron ore with a particle size distribution between +2mm and - 4.75 mm in LIGGGHTS DEM software. i Validation of the obtained input parameter values in the silo and chute showed very good qualitative comparisons between the measured and simulated flows. Quantitative predictions of flow rate were found to be particularly sensitive to variations in the particle to particle coefficient of sliding friction. It was concluded that due to their inherent limitations, angle of repose tests were not totally reliable to calibrate the particle to particle coefficient of sliding friction. Sensitivity tests conducted showed that in the quasi-static flow regime, only the frictional parameters were dominant, while both the frictional and colli sional parameters were dominant in the dynamic flow regime. These results are expected to lay a solid foundation for further research in systematic DEM cali bration and greatly increase the effectiveness of DEM models in bulk materials handling applications.
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    An automatic controller tuning algorithm.
    (1991) Christodoulou, Michael, A.
    The report describes the design of an algorithm which can be used for automatic controller tuning purposes. It uses an on-line parameter estimator and a pole assignrnent design method. The resulting control law is formulated to approximate a proportional-integral (PI) industrial controller. The development ofthe algorithm is based on the delta-operator, Some implementation aspects such as covariance resetting, dead zone, and signal conditioning are also discussed. Robust stability and performance are two issues that govern the design approach. Additionally transient and steady state system response criteria are utilized from the time and frequency domains. The design work is substantiated with the use of simulation and real plant tests.
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    Aerodynamic parameter identification for an unmanned aerial vehicle
    (2016) Padayachee, Kreelan
    The present work describes the practical implementation of systems identification techniques to the development of a linear aerodynamic model for a small low-cost UAV equipped with a basic navigational and inertial measurement systems. The assessment of the applicability of the techniques were based on determining whether adequate aerodynamic models could be developed to aid in the reduction of wind tunnel testing when characterising new UAVs. The identification process consisted of postulating a model structure, flight test manoeuvre design, data reconstruction, aerodynamic parameter estimation, and model validation. The estimators that were used for the post-flight identification were the output error maximum likelihood method and an iterated extended Kalman filter with a global smoother. SIDPAC and FVSysID systems identification toolboxes were utilised and modified where appropriate. The instrumentation system on board the UAV consisted of three-axis accelerometers and gyroscopes, a three-axis vector magnetometer and GPS tracking while data was logged at 25 Hz. The angle of attack and angle of sideslip were not measured directly and were estimated using tailored data reconstruction methods. Adequate time domain lateral model correlation with flight data was achieved for the cruise flight condition. Adequacy was assessed against Theil’s inequality coefficients and Theil’s covariance. It was found that the simplified estimation algorithms based on the linearized equations of motion yielded the most promising model matches. Due to the high correlation between the pitch damping derivatives, the longitudinal analysis did not yield valid model parameter estimates. Even though the accuracy of the resulting models was below initial expectations, the detailed data compatibility analysis provided valuable insight into estimator limitations, instrumentation requirements and test procedures for systems identification on low-cost UAVs.