Dominic Buchstaller's research while affiliated with Rolls-Royce Power Systems and other places

It is known that the Kalman filter has both stochastic and deterministic interpretations, whereby the deterministic interpretation relates the prediction of the filter to the response of the plant driven by the minimizing least squares disturbances acting thereon. Whilst the deterministic interpretation is known, the contribution of this note is to provide an alternative, simple and self-contained proof of these properties in the discrete case. The presentation allows an efficient derivation of the key deterministic properties, i.e., that the residuals computed by the Kalman filter (both forwards and backwards) are identical to the least squares disturbances. Results with variations are given for both zero and non-zero initial conditions. Finally, a numerical example is given to illustrate the deterministic properties.

It is known that the Kalman Filter has both stochastic and deterministic interpretations, whereby the deterministic interpretation relates the prediction of the filter to the response of the plant driven by the minimizing least squares disturbances acting thereon. Whilst the deterministic interpretation is known, the contribution of this note is to provide an alternative, simple and self-contained proof of these properties in the discrete case. The presentation allows an efficient derivation of the key deterministic properties. Results are given for both zero and non-zero initial conditions

This paper discusses the robustness properties of a novel, model-based HVDC fault localization algorithm. The approach utilizes a bank of Kalman filters to rank the fit of a discrete set of line fault models to measured data. The best fitting model indicates the fault position and fault type. The robustness of the algorithm in the presence of disturbances and unmodeled dynamics is demonstrated using synthetic data from high fidelity simulations as well as field data from a real HVDC transmission system.

This paper discusses a novel protection technique for DC line faults in multi-terminal HVDC (MTDC) systems. Hereby a bank of Kalman filters ranks the fit of a discrete set of line fault models to measured data. The best fitting model indicates the fault location and fault type. The suitability of the technique is discussed for fast on-line fault localization and exact off-line fault localization and fault identification. Experimental results are shown to validate the approach based on data from a high fidelity simulation of a 3-terminal HVDC system.

The focus of the German federal government’s energy agenda is an environmental friendly, reliable and affordable energy supply with the emphasis on renewable energy sources. The projected increase in renewable energy production requires new concepts for suitable grid and energy market integration. The installation of an ever increasing capacity of renewable energy sources goes in hand with increasingly stringent system requirements on the distribution grid. These challenges require novel operational strategies to hold the gird state within a permissible region, ensuring the supply security of the end customer. One possible solution-approach in this context pose managed micro-grids. Micro-grids have the property that on the one hand they are able to form electrical islands for a limited amount of time (e.g. in case of failure) and on the other hand they can deliver grid services to the (connected) overlaying electricity grid – a functionality that we denote ‘topological power plant’. In the context of IREN2 (Sustainable Grids for the Integration of Renewable Energy Systems) we will evaluate the technological and economical aspects of real-world micro grid operation. IREN2 builds on the insights gained from IRENE (project term 2011 – 2013) which was concerned with the integration of renewable energy sources as well as electric mobility. Since July 2014, the project partners are in the process of realizing an island grid capable micro-grid in the center of Wildpoldsried. Key components are tab changing transformers, a battery storage system, a number of (controllable) PV-systems, load/PV emulators, diesel generators with vegetable oil as well as an elaborate measurement and communication infrastructure. AÜW GmbH is responsible for all grid-related tasks within IREN2 and will be supported by their subsidiary egrid applications & consulting GmbH offers consulting services in respect to smart grid expansion.

An axiomatic framework providing robust stability and performance bounds for a wide class of Estimation based Multiple Model Switched Adaptive Control (EMMSAC) algorithms is developed. The approach decouples development of both the atomic control designs and the estimation processes thus permitting the usage of standard controller design and optimisation approaches for these components. The framework is shown to give tractable algorithms for MIMO LTI plants, and also for some classes of nonlinear systems (for example, an integrator with input saturation). The gain bounds obtained have the key feature that they are functions of the complexity of the underlying uncertainty as described by metric entropy measures. For certain important geometries, such as a compact parametric uncertainties, the gain bounds are independent of the number of plant models (above a certain threshold) which are utilized in the implementation. Design processes are described for achieving a suitable sampling of the plant uncertainty set to create a finite candidate plant model set (whose size is also determined by a metric entropy measure) which achieves a guaranteed robustness/performance.

The axiomatic development of a wide class of Estimation based Multiple Model Switched Adaptive Control (EMMSAC) algorithms considered in the first part of this two part contribution forms the basis for the proof of the gain bounds given in this paper. The bounds are determined in terms of a cover of the uncertainty set, and in particular, in many instances, are independent of the number of candidate plant models under consideration.The full interpretation, implications and usage of these bounds within design synthesis are discussed in part I. Here in part II, key features of the bounds are also discussed and a simulation example is considered. It is shown that a dynamic EMMSAC design can be universal and hence non-conservative and hence outperforms static EMMSAC and other conservative designs. A wide range of possible dynamic algorithms are outlined, motivated by both performance and implementation considerations.

For a sampled-data control system, the authors propose to choose the time between samples to be shorter than the computational delay involved in computing the control signal, an approach called as intra-delay sampling. It is shown that, utilising a parallel computing architecture, this is indeed feasible and that intra-delay sampling schemes yield better performance than their slower sampling counterparts.

For a sampled-data control system, the sampling period is chosen smaller than the computational delay, an approach we call intra-delay sampling. Utilising parallel computing architectures, it is shown that intra-delay sampling schemes are feasible and that they yield better performance than their slower sampling counterparts.

For an estimation based multiple model switched adaptive control (EMMSAC) algorithm controlling a MIMO minimal LTI plant, l_p, 1 ¿ p ¿ ¿ bounds on the gain from the input and output disturbances to the internal signals are obtained which are invariant to the number of models in the plant model set. For a compact uncertainty set it is shown that a realisable EMMSAC algorithm achieves robust stability for any plant within the uncertainty set.