50 research outputs found

    Design of a Wide Area Controller Using Eigenstructure Assignment in Power Systems

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    Small signal stability has become a major concern for power system operators around the world. This has resulted from constantly evolving changes in the power system ranging from increased number of interconnections to ever increasing demand of power. In highly stressed operating conditions, even a small disturbance such as a load change can make the system unstable resulting in small signal instability. The main reason for small signal instability in power systems is an inter-area mode/s becoming unstable. Inter-area modes involve a group of generators oscillating against each other. Traditionally, power system stabilizers installed on the synchrous machines were used to damp the inter-area modes. However, they may not be very suitable to perform the job since they use local I/O signals which do not have a good controllability/observability of the inter-area modes. Recent advancements in phasor measurement technology has resulted in fast acquisition of time-synchronized measurements throughout the system. Thus, instead of using local controllers, an idea of a wide area controller (WAC) was proposed by the power systems community that would use global signals. This dissertation demonstrates the design of a WAC using eigenstructure assignment technique. This technique provides the freedom to assign a few eigenvalues and corresponding left or right eigenvectors for Multi-Input-Multi-Output (MIMO) systems. This technique forms a good match for designing a WAC since a WAC usually uses multiple I/O signals and a power system only has a few inter-area modes that might lead to instability. The last chapter of this dissertation addresses an important aspect of controller design, i.e., robustness of the controller to uncertainties in operating point and time delay of feedback signals. The operating point of a power system is highly variable in nature and thus the designed WAC should be able to damp the inter-area modes under these variations. Also, a transmission delay is associated due to routing of remote signals. This time delay is known to deteriorate the performance of the controller. A single controller will be shown to achieve robustness against both these uncertainties

    Model-based control for automotive applications

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    The number of distributed control systems in modern vehicles has increased exponentially over the past decades. Today’s performance improvements and innovations in the automotive industry are often resolved using embedded control systems. As a result, a modern vehicle can be regarded as a complex mechatronic system. However, control design for such systems, in practice, often comes down to time-consuming online tuning and calibration techniques, rather than a more systematic, model-based control design approach. The main goal of this thesis is to contribute to a corresponding paradigm shift, targeting the use of systematic, model-based control design approaches in practice. This implies the use of control-oriented modeling and the specification of corresponding performance requirements as a basis for the actual controller synthesis. Adopting a systematic, model-based control design approach, as opposed to pragmatic, online tuning and calibration techniques, is a prerequisite for the application of state-of-the-art controller synthesis methods. These methods enable to achieve guarantees regarding robustness, performance, stability, and optimality of the synthesized controller. Furthermore, from a practical point-of-view, it forms a basis for the reduction of tuning and calibration effort via automated controller synthesis, and fulfilling increasingly stringent performance demands. To demonstrate these opportunities, case studies are defined and executed. In all cases, actual implementation is pursued using test vehicles and a hardware-in-the-loop setup. ‱ Case I: Judder-induced oscillations in the driveline are resolved using a robustly stable drive-off controller. The controller prevents the need for re-tuning if the dynamics of the system change due to wear. A hardware-in-the-loop setup, including actual sensor and actuator dynamics, is used for experimental validation. ‱ Case II: A solution for variations in the closed-loop behavior of cruise control functionality is proposed, explicitly taking into account large variations in both the gear ratio and the vehicle loading of heavy duty vehicles. Experimental validation is done on a heavy duty vehicle, a DAF XF105 with and without a fully loaded trailer. ‱ Case III: A systematic approach for the design of an adaptive cruise control is proposed. The resulting parameterized design enables intuitive tuning directly related to comfort and safety of the driving behavior and significantly reduces tuning effort. The design is validated on an Audi S8, performing on-the-road experiments. ‱ Case IV: The design of a cooperative adaptive cruise control is presented, focusing on the feasibility of implementation. Correspondingly, a necessary and sufficient condition for string stability is derived. The design is experimentally tested using two CitroĂ«n C4’s, improving traffic throughput with respect to standard adaptive cruise control functionality, while guaranteeing string stability of the traffic flow. The case studies consider representative automotive control problems, in the sense that typical challenges are addressed, being variable operating conditions and global performance qualifiers. Based on the case studies, a generic classification of automotive control problems is derived, distinguishing problems at i) a full-vehicle level, ii) an in-vehicle level, and iii) a component level. The classification facilitates a characterization of automotive control problems on the basis of the required modeling and the specification of corresponding performance requirements. Full-vehicle level functionality focuses on the specification of desired vehicle behavior for the vehicle as a whole. Typically, the required modeling is limited, whereas the translation of global performance qualifiers into control-oriented performance requirements can be difficult. In-vehicle level functionality focuses on actual control of the (complex) vehicle dynamics. The modeling and the specification of performance requirements are typically influenced by a wide variety of operating conditions. Furthermore, the case studies represent practical application examples that are specifically suitable to apply a specific set of state-of-the-art controller synthesis methods, being robust control, model predictive control, and gain scheduling or linear parameter varying control. The case studies show the applicability of these methods in practice. Nevertheless, the theoretical complexity of the methods typically translates into a high computational burden, while insight in the resulting controller decreases, complicating, for example, (online) fine-tuning of the controller. Accordingly, more efficient algorithms and dedicated tools are required to improve practical implementation of controller synthesis methods

    Parameterized Model Order Reduction with Applications to Thermal Systems

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    Sets and Constraints in the Analysis Of Uncertain Systems

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    This thesis is concerned with the analysis of dynamical systems in the presence of model uncertainty. The approach of robust control theory has been to describe uncertainty in terms of a structured set of models, and has proven successful for questions, like stability, which call for a worst-case evaluation over this set. In this respect, a first contribution of this thesis is to provide robust stability tests for the situation of combined time varying, time invariant and parametric uncertainties. The worst-case setting has not been so attractive for questions of disturbance rejection, since the resulting performance criteria (e.g., ℋ∞,) treat the disturbance as an adversary and ignore important spectral structure, usually better characterized by the theory of stochastic processes. The main contribution of this thesis is to show that the set-based methodology can indeed be extended to the modeling of white noise, by employing standard statistical tests in order to identify a typical set, and performing subsequent analysis in a worst-case setting. Particularly attractive sets are those described by quadratic signal constraints, which have proven to be very powerful for the characterization of unmodeled dynamics. The combination of white noise and unmodeled dynamics constitutes the Robust ℋ2 performance problem, which is rooted in the origins of robust control theory. By extending the scope of the quadratic constraint methodology we obtain a solution to this problem in terms of a convex condition for robustness analysis, which for the first time places it on an equal footing with the ℋ∞ performance measure. A separate contribution of this thesis is the development of a framework for analysis of uncertain systems in implicit form, in terms of equations rather than input-output maps. This formulation is motivated from first principles modeling, and provides an extension of the standard input-output robustness theory. In particular, we obtain in this way a standard form for robustness analysis problems with constraints, which also provides a common setting for robustness analysis and questions of model validation and system identification

    Robust, Gain-Scheduled Control of Wind Turbines

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    Robust real-time control of an adaptive optics system

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    This research contributes to the understanding of the limitations when designing a robust control real-time system for Adaptive Optics (AO). One part of the research is a new method regarding the evaluation of a Shack-Hartmann wavefront sensor (SHWFS) to enhance the overall performance. The method is presented based on the application of a Field Programmable Gate Array (FPGA) using Connected Component Labeling (CCL) for blob detection. The FPGA has been utilized since the resulting delay is crucial for the general AO performance. In this regard, the FPGA may accelerate the evaluation largely by its parallelism. The developed algorithm does not rely on a fixed assignment of the camera sensor area to the lenslet array to maximize the dynamic range. In extension to the SHWFS evaluation, a new rapid control prototyping (RCP) system based on hard real-time RTAI-patched Linux kernel has been developed. This system includes the required hardware e.g.~the analog output cards and FPGA based frame-grabber. Based upon a Simulink model, accelerated C/C++ code is automatically generated which uses the available parallel features of the processor. A continuative contribution is the application of a robust control scheme using H-infinity methods for designing a controller while considering uncertainty of the identified model. For synthesizing the controller, a special optimization technique called non-smooth mu-synthesis is utilized which minimizes the H-infinity norm while coping with pre-specified controller schemes. Depending on the pre-specified controller scheme, the resulting controller can be computationally costly but the RCP approach is designed to cope with the problem. Based on simulations and according to experiments, the validity of the identified models of the AO setup is assured. At the same time, the enhanced performance of the new RCP setup is demonstrated.Die wissenschaftliche Arbeit trĂ€gt maßgeblich zum VerstĂ€ndnis der gĂ€ngigen Limitierungen bei robusten echtzeit-fĂ€higen Regelungssystemen fĂŒr Adaptiv Optische (AO) Systeme bei. Ein wesentlicher Teil der Arbeit befasst sich mit einer neuartigen Methode der Auswertung eines Shack-Hartmann Wellenfrontsensors (SHWFS). Die Methode basiert auf der Anwendung eines Field Programmable Gate Arrays (FPGA) zur Auswertung des SHWFS. Die zu Grunde liegende Methode ist ein Resultat der Graphentheorie zur Erkennung zusammenhĂ€ngender Bildbereiche. Der Einsatz eines FPGA ermöglicht hierbei, dass die resultierende Verzögerung durch die Auswertung des SHWFS auf ein Minimum reduziert wird. Hinzu kommt, dass die neuartige Auswertungsmethode den dynamischen Bereich des Wellenfrontsensors gegenĂŒber dem ĂŒblichen Verfahren erweitert, da fĂŒr die Methode keine feste Zuordnung der Spots zu dem Linsenarray notwendig ist. ZusĂ€tzlich zu dem neuartigen Verfahren fĂŒr die Auswertung wurde ein Rapid Control Prototyping (RCP) System entworfen, welches auf einem echtzeitfĂ€higen Linux Kernel basiert. Die EchtzeitfĂ€higkeit wird durch die Verwendung des Real-Time Application Interface for Linux (RTAI) erreicht. Der Entwurf des RCP Systems umfasst die Entwicklung spezieller Hardware wie beispielsweise eine analoge Ausgangskarte und der PCIe FPGA Framegrabber. Aus einem Simulink Modell wird automatisch C/C++ Quellcode generiert. Dieser generierte Code nutzt die vorhandenen parallelen Erweiterungen des Prozessors zur Beschleunigung der vorkommenden Berechnungen. Basierend auf diesem System wurde ein robustes Regelungsverfahren angewendet, welches auf der H_infty Entwurfsmethodik basiert. Das Entwurfverfahren des Reglers (non-smooth mu Synthese) berĂŒcksichtigt die vorhandene Unsicherheit der identifizierten Modelle bereits wĂ€hrend der Synthese. Das Verfahren ermöglicht die H_infty Norm des geschlossenen Regelkreises zu minimieren, wobei die Regler-Struktur vorgegeben werden kann. Basierend auf verschiedenen Simulationen und experimentellen Versuchen wurde die GĂŒltigkeit der identifizierten Modelle des AO Systems nachgewiesen. Zudem wird gezeigt, dass das entworfene RCP System deutlich leistungsfĂ€higer als vergleichbare Systeme ist und somit eine deutlich verbesserte Performance aufweist
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