Adaptive optimal operation of a parallel robotic liquid handling station

Results are presented from the optimal operation of a fully automated robotic liquid handling station where parallel experiments are performed for calibrating a kinetic fermentation model. To increase the robustness against uncertainties and/or wrong assumptions about the parameter values, an iterative calibration and experiment design approach is adopted. Its implementation yields a stepwise reduction of parameter uncertainties together with an adaptive redesign of reactor feeding strategies whenever new measurement information is available. The case study considers the adaptive optimal design of 4 parallel fed-batch strategies implemented in 8 mini-bioreactors. Details are given on the size and complexity of the problem and the challenges related to calibration of over-parameterized models and scarce and non-informative measurement data. It is shown how methods for parameter identifiability analysis and numerical regularization can be used for monitoring the progress of the experimental campaigns in terms of generated information regarding parameters and selection of the best fitting parameter subset.BMBF, 02PJ1150, Verbundprojekt: Plattformtechnologien für automatisierte Bioprozessentwicklung (AutoBio); Teilprojekt: Automatisierte Bioprozessentwicklung am Beispiel von neuen Nukleosidphosphorylase

New control for two mass positioning system using nominal characteristic trajectory following controller

In this study, a nominal characteristic trajectory following (NCTF) controller for point-to-point (PTP) positioning system is introduced for two mass systems and its performance is evaluated.The NCTF controller consists of a nominal characteristic trajectory (NCT) and a compensator. The objective of the NCTF controller is to make the object motion follow the NCT and end at its origin.Therefore, the NCT is used as an intended object motion and the compensator is used to make the motion of the controlled object follow the NCT.The NCTF controller is designed based on a simple open-loop experiment of the object and no information except the NCT is necessary for controller design. The effectiveness of the NCTF controller is evaluated and discussed through simulations.The effect of the design parameters on the robustness of the NCTF controller to inertia and friction variations is evaluated and the influence of saturation on the positioning performance is examined

Modeling and analysis of semiconductor manufacturing processes using petri nets

This thesis addresses the issues in modeling and analysis of multichip module (MCM) manufacturing processes using Petri nets. Building such graphical and mathematical models is a crucial step to understand MCM technologies and to enhance their application scope. In this thesis, the application of Petri nets is presented with top-down and bottom-up approaches. The theory of Petri nets is summarized with its basic notations and properties at first. After that, the capability of calculating and analyzing Petri nets with deterministic timing information is extended to meet the requirements of the MCM models. Then, using top-down refining and system decomposition, MCM models are built from an abstract point to concrete systems with timing information. In this process, reduction theory based on a multiple-input-single-output modules for deterministic Petri nets is applied to analyze the cycle time of Petri net models. Besides, this thesis is of significance in its use of the reduction theory which is derived for timed marked graphs - an important class of Petri nets

JOINING SEQUENCE ANALYSIS AND OPTIMIZATION FOR IMPROVED GEOMETRICAL QUALITY

Disturbances in the manufacturing and assembly processes cause geometrical variation from the ideal geometry. This variation eventually results in functional and aesthetic problems in the final product. Being able to control the disturbances is the desire of the manufacturing industry. \ua0 Joining sequences impact the final geometrical outcome in an assembly considerably. To optimize the sequence for improved geometrical outcome is both experimentally and computationally expensive. In the simulation-based approaches, based on the finite element method, a large number of sequences need to be evaluated.\ua0 In this thesis, the simulation-based joining sequence optimization using non-rigid variation simulation is studied. Initially, the limitation of the applied algorithms in the literature has been addressed. A rule-based optimization approach based on meta-heuristic algorithms and heuristic search methods is introduced to increase the previously applied algorithms\u27 time-efficiency and accuracy. Based on the identified rules and heuristics, a reduced formulation of the sequence optimization is introduced by identifying the critical points for geometrical quality. A subset of the sequence problem is identified and solved in this formulation.\ua0 For real-time optimization of the joining sequence problem, time-efficiency needs to be further enhanced by parallel computations. By identifying the sequence-deformation behavior in the assemblies, black-box surrogate models are introduced, enabling parallel evaluations and accurate approximation of the geometrical quality. Based on this finding, a deterministic stepwise search algorithm for rapid identification of the optimal sequence is introduced.\ua0 Furthermore, a numerical approach to identify the number, location from a set of alternatives, and sequence of the critical joining points for geometrical quality is introduced. Finally, the cause of the various deformations achieved by joining sequences is identified. A time-efficient non-rigid variation simulation approach for evaluating the geometrical quality with respect to the sequences is proposed. \ua0 The results achieved from the studies presented indicate that the simulation-based real-time optimization of the joining sequences is achievable through a parallelized search algorithm and a rapid evaluation of the sequences. The critical joining points for geometrical quality are identified while the sequence is optimized. The results help control the assembly process with respect to the joining operation, improve the geometrical quality, and save significant computational time

Information Exchange in Global Production Networks: Increasing Transparency by Simulation, Statistical Experiments and Selection of Digitalization Activities

Today, companies of all industries are part of global production networks. They have a variety of performance relationships with suppliers and customers. Digitalization offers the potential to exchange more information between the partners of global production networks. This may improve operational performance. Especially within the three business processes order management, quality problem solving and engineering change management, a targeted increase in transparency promises a better handling of disruptions and an increase in robustness. This paper presents a simulation-based methodology for modeling production and business processes as well as information exchange in global production networks. Following the principles of Design of Experiment (DoE), screening test plans first carve out the impact of disruptions and information exchange on the performance of the production network. This is followed by the determination of the disruption-robust information exchange using Taguchi-experiments. Starting from the actual state of information exchange, digitalization activities to increase transparency are finally determined. The activities consist of the implementation of digitalization technologies and the stronger linkage of information systems. The paper ends with an application of the methodology to a global production network for plastic-metal components in the automotive supplier industry

Self-Sensing Control for Soft-Material Actuators Based on Dielectric Elastomers

Due to their energy density and softness that are comparable to human muscles dielectric elastomer (DE) transducers are well-suited for soft-robotic applications. This kind of transducer combines actuator and sensor functionality within one transducer so that no external senors to measure the deformation or to detect collisions are required. Within this contribution we present a novel self-sensing control for a DE stack-transducer that allows to control several different quantities of the DE transducer with the same controller. This flexibility is advantageous e.g., for the development of human machine interfaces with soft-bodied robots. After introducing the DE stack-transducer that is driven by a bidirectional flyback converter, the development of the self-sensing state and disturbance estimator based on an extended Kalman-filter is explained. Compared to known estimators designed for DE transducers supplied by bulky high-voltage amplifiers this one does not require any superimposed excitation to enable the sensor capability so that it also can be used with economic and competitive power electronics like the flyback converter. Due to the behavior of this converter a sliding mode energy controller is designed afterwards. By introducing different feed-forward controls the voltage, force or deformation can be controlled. The validation proofs that both the developed self-sensing estimator as well as the self-sensing control yield comparable results as previously published sensor-based approaches.TU Berlin, Open-Access-Mittel - 201

PI/PID Controller Relay Experiment Auto-Tuning with Extended Kalman Filter and Second-Order Generalized Integrator as Parameter Estimators

This paper presents a method for the estimation of key parameters of limit cycle oscillations (amplitude and frequency) during a relay experiment used for automatic tuning of proportional-integral (PI) and proportional-integral-derivative (PID) feedback controllers. The limit cycle parameter estimator is based on the first-order extended Kalman filter (EKF) for resonance frequency estimation, to which a second-order generalized integrator (SOGI) is cascaded for the purpose of limit cycle amplitude estimation. Based on thus-obtained parameters of the limit cycle oscillations, the ultimate gain and the ultimate period of the limit cycle oscillations are estimated. These are subsequently used for the tuning of PI and PID controller according to Takahashi modifications of Ziegler-Nichols tuning rules. The proposed PI and PID controller auto-tuning method is verified by means of simulations and experimentally on the heat and air-flow experimental setup for the case of air temperature feedback control. The results have shown that the proposed auto-tuning system based on relay control experiment for the heat and air-flow process PI/PID temperature control can capture the ultimate gain and period parameters fairly quickly in simulations and in experiments. Subsequent controller tuning according to Takahashi modifications of Ziegler-Nichols rules using thus-obtained ultimate point parameters can provide favourable closed-loop load disturbance rejection, particularly in the case of PID controller

Parameter identification and model based control of direct drive robots

Imperial Users onl