Engineering handbook

1995 handbook for the faculty of Engineerin

Predictive control using an FPGA with application to aircraft control

Alternative and more efficient computational methods can extend the applicability of MPC to systems with tight real-time requirements. This paper presents a ``system-on-a-chip'' MPC system, implemented on a field programmable gate array (FPGA), consisting of a sparse structure-exploiting primal dual interior point (PDIP) QP solver for MPC reference tracking and a fast gradient QP solver for steady-state target calculation. A parallel reduced precision iterative solver is used to accelerate the solution of the set of linear equations forming the computational bottleneck of the PDIP algorithm. A numerical study of the effect of reducing the number of iterations highlights the effectiveness of the approach. The system is demonstrated with an FPGA-in-the-loop testbench controlling a nonlinear simulation of a large airliner. This study considers many more manipulated inputs than any previous FPGA-based MPC implementation to date, yet the implementation comfortably fits into a mid-range FPGA, and the controller compares well in terms of solution quality and latency to state-of-the-art QP solvers running on a standard PC.This work was supported by EPSRC (Grants EP/G030308/1, EP/G031576/1 and EP/I012036/1) and the EU FP7 Project EMBOCON grant agreement number FP7-ICT-2009-4 248940, as well as industrial support from Xilinx, the Mathworks, and the European Space Agency.This is the author's version of an article that has been published in this journal. Changes were made to this version by the publisher prior to publication. The final version of record is available at: http://dx.doi.org/10.1109/TCST.2013.2271791. Copyright (c) 2014 IEEE. Personal use is permitted. For any other purposes, permission must be obtained from the IEEE by emailing [email protected]

Engineering handbook

1996 handbook for the faculty of Engineerin

Resilience of data centre power system: modelling of sustained operation under outage, definition of metrics, and application

A novel criterion for quantifying the resilience of power systems supplying data centres is formulated to measure the system's ability to sustain functionality even during an outage. By comparative analysis of two alternative data centre power systems covering apparatus of electrical power supply and environmental control, it is shown that reliability and availability alone are insufficient as metrics to gauge different designs. The gap is bridged by the proposed resilience analysis to further evaluate situations of single and double outages. As a complement to the indicators of single point of failure and double point of failure, respectively, N−1 and N−2 security criteria, the novel metrics of a single point of reduced availability and double point of reduced availability are proposed. These criteria identify those single subsystems or subsystem pairs causing system availability to drop below requested levels in periods when they are out of service. The metrics so offer information on the overall system's availability during times of maintenance and failures. Thanks to this understanding, it is shown that a guided reduction of the number of subsystems considering their relative importance can lead to designs offering desirable trade-offs in terms of complexity, reliability, availability, and resilience.DFG, 414044773, Open Access Publizieren 2019 - 2020 / Technische Universität Berli

VaR and Liquidity Risk.Impact on Market Behaviour and Measurement Issues.

Current trends in international banking supervision following the 1996 Amendment to the Basel Accord emphasise market risk control based upon internal Value-at-risk (VaR) models. This paper discusses the merits and drawbacks of VaR models in the light of their impact on market liquidity. After a preliminary review of basic concepts and measures regarding market risk, market friction and liquidity risk, the arguments supporting the internal models approach to supervision on market risk are discussed, in the light of the debate on the limitations and possible enhancements of VaR models. In particular, adverse systemic effects of widespread risk management practices are considered. Risk measurement models dealing with liquidity risk are then examined in detail, in order to verify their potential for application in the field. We conclude that VaR models are still far from effectively treating market and liquidity risk in their multi-faceted aspects. Regulatory guidelines are right in recognising the importance of internal risk control systems. Implementation of those guidelines might inadvertently encourage mechanic application of VaR models, with adverse systemic effects.