Abstract: This paper presents a supervisory control theory based offline method for calculating restart states in a manufacturing control system. Given these precalculated restart states, an operator can be given correct instructions for how to resynchronize the control system and the manufacturing resources during the online restart process. The proposed method enables restart after unforeseen errors. It is assumed that the control system is modeled by operations and that possible operation sequences emerge through dependencies between the operations. The paper shows how reexecution requirements may be included in the calculation to obtain a correct behavior for the restarted system. In addition, it is shown how to filter out restart states that require less effort for the operator during the online restart, and how to adapt the nominal production to always enable restart in desired restart states.
Abstract: Friction is mostly unwanted in rotating machines. In order to reduce its impact on the system, the integration of magnetic bearings is frequently regarded as a valid solution. In rotating systems like flywheel energy storage systems (FESS), mechanical losses created by mechanical bearings greatly reduce the overall performance. Magnetic bearings are thus frequently integrated in FESS to eliminate mechanical losses. The simple design of passive magnetic bearings (PMBs), their inherent security, and their very low friction make them perfect candidates for FESS. The main objective, and most important contribution of this paper, is to document an innovative PMB that minimizes energy losses induced by the axial thrust bearing, and to document the methodology used to measure its stiffness and damping. Although PMBs are fairly well documented in literature, no other PMB is designed to reduce the friction generated by the thrust bearing. In order to promote their integration, it is critical to identify their mechanical properties such as stiffness and damping. Hence, another contribution of this paper is to propose a new way to easily characterize any magnetic bearing topology to replace available techniques that only provided the properties for a precise configuration of the bearing. The new technique provides an unprecedented mapping of the forces generated by complex combinations of permanent magnets. Experimental results show that the new PMB can be configured to effectively reduce the force applied to the thrust bearing, resulting in lower friction. This friction reduction is achieved while allowing the proper operation of the bearing. Results also show that the measured stiffness is different from those obtained analytically, suggesting that a magnetic bearing should always be characterized prior to its use.
Abstract: 3D numerical combustion simulation in a can burner fed with methane was carried out in order to evaluate pollutant emissions and the temperature field. As a case study, the General Electric Frame 6001B system was considered. The numerical investigation has been performed using the CFD code named ACE+ Multiphysics (by Esi-Group). The model was validated against the experimental data provided by Cofely GDF SUEZ and related to a real power plant. To completely investigate the stability of the model, several operating conditions were taken into account, at both nominal and partial load. In particular, the influence on emissions of some important parameters, such as air temperature at compressor intake and steam to fuel mass ratio, have been evaluated. The flamelet model and Zeldovich’s mechanism were employed for combustion modeling and NOx emissions, respectively. With regard to CO estimation, an innovative approach was used to compute the Rizk and Mongia relationship through a user-defined function. Numerical results showed good agreement with experimental data in most of the cases: the best results were obtained in the NOx prediction, while unburned fuel was slightly overestimated.
Abstract: Industrial automation has been recognized as a fundamental key to build and keep manufacturing industries in developed countries. In most automation tasks, knowing the exact position of the objects to handle is essential. This is often done using a positional calibration system, such as a camera-based vision system. In this article, an alternative six-degrees-of-freedom work object positional calibration method using a robot-held proximity sensor, is presented. A general trigonometry-based measurement and calculation procedure, which, step-by-step, adjusts a work object coordinate system to the actual work object position, is explained. For suitable robot tasks and work object geometries, the benefits with the presented method include its robustness, large work area and low investment cost. Some drawbacks can be longer cycle time and its limited capacity to handle unsorted and complicated objects. To validate the presented method, it was implemented in an experimental robot setup. In this robot cell, it was used to calibrate the position of a stator section work object, which is used in the Uppsala University Wave Energy Converter generator. Hereby the function of the positional calibration procedure was validated. Sufficient positioning accuracy for the stator winding task was achieved and theoretically validated based on the experiments.
Abstract: Economic exploitation of lunar resources may be more efficient with a non-rocket approach to launch from the lunar surface. The launch system cost will depend on its design, and on the number of launches from Earth to deliver the system to the Moon. Both of these will depend on the launcher system mass. Properties of an electromagnetic resource launcher are derived from two mature terrestrial electromagnetic launchers. A mass model is derived and used to estimate launch costs for a developmental launch vehicle. A rough manufacturing cost for the system is suggested.
Abstract: Adaptive mixing control (AMC) is a recently developed control scheme for uncertain plants, where the control action coming from a bank of precomputed controller is mixed based on the parameter estimates generated by an on-line parameter estimator. Even if the stability of the control scheme, also in the presence of modeling errors and disturbances, has been shown analytically, its transient performance might be sensitive to the initial conditions of the parameter estimator. In particular, for some initial conditions, transient oscillations may not be acceptable in practical applications. In order to account for such a possible phenomenon and to improve the learning capability of the adaptive scheme, in this paper a new mixing architecture is developed, involving the use of parallel parameter estimators, or multi-estimators, each one working on a small subset of the uncertainty set. A supervisory logic, using performance signals based on the past and present estimation error, selects the parameter estimate to determine the mixing of the controllers. The stability and robustness properties of the resulting approach, referred to as multi-estimator adaptive mixing control (Multi-AMC), are analytically established. Besides, extensive simulations demonstrate that the scheme improves the transient performance of the original AMC with a single estimator. The control scheme and the analysis are carried out in a discrete-time framework, for easier implementation of the method in digital control.