Stiffness based trajectory planning and feedforward based vibration suppression control of parallel robot machines

The dissertation proposes two control strategies, which include the trajectory planning and vibration suppression, for a kinematic redundant serial-parallel robot machine, with the aim of attaining the satisfactory machining performance. For a given prescribed trajectory of the robot's end-effector in the Cartesian space, a set of trajectories in the robot's joint space are generated based on the best stiffness performance of the robot along the prescribed trajectory. To construct the required system-wide analytical stiffness model for the serial-parallel robot machine, a variant of the virtual joint method (VJM) is proposed in the dissertation. The modified method is an evolution of Gosselin's lumped model that can account for the deformations of a flexible link in more directions. The effectiveness of this VJM variant is validated by comparing the computed stiffness results of a flexible link with the those of a matrix structural analysis (MSA) method. The comparison shows that the numerical results from both methods on an individual flexible beam are almost identical, which, in some sense, provides mutual validation. The most prominent advantage of the presented VJM variant compared with the MSA method is that it can be applied in a flexible structure system with complicated kinematics formed in terms of flexible serial links and joints. Moreover, by combining the VJM variant and the virtual work principle, a systemwide analytical stiffness model can be easily obtained for mechanisms with both serial kinematics and parallel kinematics. In the dissertation, a system-wide stiffness model of a kinematic redundant serial-parallel robot machine is constructed based on integration of the VJM variant and the virtual work principle. Numerical results of its stiffness performance are reported. For a kinematic redundant robot, to generate a set of feasible joints' trajectories for a prescribed trajectory of its end-effector, its system-wide stiffness performance is taken as the constraint in the joints trajectory planning in the dissertation. For a prescribed location of the end-effector, the robot permits an infinite number of inverse solutions, which consequently yields infinite kinds of stiffness performance. Therefore, a differential evolution (DE) algorithm in which the positions of redundant joints in the kinematics are taken as input variables was employed to search for the best stiffness performance of the robot. Numerical results of the generated joint trajectories are given for a kinematic redundant serial-parallel robot machine, IWR (Intersector Welding/Cutting Robot), when a particular trajectory of its end-effector has been prescribed. The numerical results show that the joint trajectories generated based on the stiffness optimization are feasible for realization in the control system since they are acceptably smooth. The results imply that the stiffness performance of the robot machine deviates smoothly with respect to the kinematic configuration in the adjacent domain of its best stiffness performance. To suppress the vibration of the robot machine due to varying cutting force during the machining process, this dissertation proposed a feedforward control strategy, which is constructed based on the derived inverse dynamics model of target system. The effectiveness of applying such a feedforward control in the vibration suppression has been validated in a parallel manipulator in the software environment. The experimental study of such a feedforward control has also been included in the dissertation. The difficulties of modelling the actual system due to the unknown components in its dynamics is noticed. As a solution, a back propagation (BP) neural network is proposed for identification of the unknown components of the dynamics model of the target system. To train such a BP neural network, a modified Levenberg-Marquardt algorithm that can utilize an experimental input-output data set of the entire dynamic system is introduced in the dissertation. Validation of the BP neural network and the modified Levenberg- Marquardt algorithm is done, respectively, by a sinusoidal output approximation, a second order system parameters estimation, and a friction model estimation of a parallel manipulator, which represent three different application aspects of this method.

The estimation of tuberculosis transmission parameters using ABC and MCMC methods

The aim of this work is to apply approximate Bayesian computation in combination with Marcov chain Monte Carlo methods in order to estimate the parameters of tuberculosis transmission. The methods are applied to San Francisco data and the results are compared with the outcomes of previous works. Moreover, a methodological idea with the aim to reduce computational time is also described. Despite the fact that this approach is proved to work in an appropriate way, further analysis is needed to understand and test its behaviour in different cases. Some related suggestions to its further enhancement are described in the corresponding chapter.

The effect of focal point parameters in fiber laser welding of structural steel

In this thesis the effect of focal point parameters in fiber laser welding of structural steel is studied. The goal is to establish relations between laser power, focal point diameter and focal point position with the resulting quality, weld-bead geometry and hardness of the welds. In the laboratory experiments, AB AH36 shipbuilding steel was welded in an I-butt joint configuration using IPG YLS-10000 continuous wave fiber laser. The quality of the welds produced were evaluated based on standard SFS-EN ISO 13919-1. The weld-bead geometry was defined from the weld cross-sections and Vickers hardness test was used to measure hardness's from the middle of the cross-sections. It was shown that all the studied focal point parameters have an effect on the quality, weld-bead geometry and hardness of the welds produced.

Effects of Fin Parameters on Gas-Side Heat Transfer Performance of H-Type Finned Tube Bundle in a Waste Heat Recovery Boiler

Alfa Laval Aalborg Oy designs and manufactures waste heat recovery systems utilizing extended surfaces. The waste heat recovery boiler considered in this thesis is a water-tube boiler where exhaust gas is used as the convective heat transfer medium and water or steam flowing inside the tubes is subject to cross-flow. This thesis aims to contribute to the design of waste heat recovery boiler unit by developing a numerical model of the H-type finned tube bundle currently used by Alfa Laval Aalborg Oy to evaluate the gas-side heat transfer performance. The main objective is to identify weaknesses and potential areas of development in the current H-type finned tube design. In addition, numerical simulations for a total of 15 cases with varying geometric parameters are conducted to investigate the heat transfer and pressure drop performance dependent on H-type fin geometry. The investigated geometric parameters include fin width and height, fin spacing, and fin thickness. Comparison between single and double tube type configuration is also conducted. Based on the simulation results, the local heat transfer and flow behaviour of the H-type finned tube is presented including boundary layer development between the fins, the formation of recirculation zone behind the tubes, and the local variations of flow velocity and temperature within the tube bundle and on the fin surface. Moreover, an evaluation of the effects of various fin parameters on heat transfer and pressure drop performance of H-type finned tube bundle has been provided. It was concluded that from the studied parameters fin spacing and fin width had the most significant effect on tube bundle performance and the effect of fin thickness was the least important. Furthermore, the results suggested that the heat transfer performance would increase due to enhanced turbulence if the current double tube configuration is replaced with single tube configuration, but further investigation and experimental measurements are required in order to validate the results.

Determination of the thermal parameters of high-power batteries by local heat

A new approach to the determination of the thermal parameters of high-power batteries is introduced here. Application of local heat flux measurement with a gradient heat flux sensor (GHFS) allows determination of the cell thermal parameters in di_erent surface points of the cell. The suggested methodology is not cell destructive as it does not require deep discharge of the cell or application of any charge/discharge cycles during measurements of the thermal parameters of the cell. The complete procedure is demonstrated on a high-power Li-ion pouch cell, and it is verified on a sample with well-known thermal parameters. A comparison of the experimental results with conventional thermal characterization methods shows an acceptably low error. The dependence of the cell thermal parameters on state of charge (SoC) and measurement points on the surface was studied by the proposed measurement approach.