Initial modelling and controller design for active control of spacecraft microvibrations

Microvibrations, at frequencies between 1 and 1000 Hz, generated by on board equipment, propagate throughout a spacecraft structure affecting the performance of sensitive payloads. The purpose of this work is to investigate strategies to model and reduce these dynamic disturbances by active control. Initial studies were performed by considering a mass loaded panel where the disturbance excitation source consisted of point forces, the objective being to minimise the displacement at an arbitrary output location. Piezoelectric patches acting as sensors and actuators were used. The equations of motion are derived by using Lagrange's equation with modal shapes as Ritz functions. The number of sensors/actuators and their location is variable. The set of equations obtained is then transformed into state variables and some initial controller design studies have been undertaken. These are based on feedback control implemented using a full state feedback and an observer which reconstructs the state vector from the available sensor signal. Here, the basics behind the structural modelling and controller design will be described. This preliminary analysis will also be used to identify short to medium term further work.

Augmenting depth camera output using photometric stereo

We present a system for augmenting depth camera output using multispectral photometric stereo. The technique is demonstrated using a Kinect sensor and is able to produce geometry independently for each frame. Improved reconstruction is demonstrated using the Kinect's inbuilt RGB camera and further improvements are achieved by introducing an additional high resolution camera. As well as qualitative improvements in reconstruction a quantitative reduction in temporal noise is shown. As part of the system an approach is presented for relaxing the assumption of multispectral photometric stereo that scenes are of constant chromaticity to the assumption that scenes contain multiple piecewise constant chromaticities.

Dynamical structure function identifiability conditions enabling signal structure reconstruction

Networks of controlled dynamical systems exhibit a variety of interconnection patterns that could be interpreted as the structure of the system. One such interpretation of system structure is a system's signal structure, characterized as the open-loop causal dependencies among manifest variables and represented by its dynamical structure function. Although this notion of structure is among the weakest available, previous work has shown that if no a priori structural information is known about the system, not even the Boolean structure of the dynamical structure function is identifiable. Consequently, one method previously suggested for obtaining the necessary a priori structural information is to leverage knowledge about target specificity of the controlled inputs. This work extends these results to demonstrate precisely the a priori structural information that is both necessary and sufficient to reconstruct the network from input-output data. This extension is important because it significantly broadens the applicability of the identifiability conditions, enabling the design of network reconstruction experiments that were previously impossible due to practical constraints on the types of actuation mechanisms available to the engineer or scientist. The work is motivated by the proteomics problem of reconstructing the Per-Arnt-Sim Kinase pathway used in the metabolism of sugars. © 2012 IEEE.

The incentives for supply chain collaboration to improve material efficiency in the use of steel: An analysis using input output techniques

In the face of increasing demand and limited emission reduction opportunities, the steel industry will have to look beyond its process emissions to bear its share of emission reduction targets. One option is to improve material efficiency - reducing the amount of metal required to meet services. In this context, the purpose of this paper is to explore why opportunities to improve material efficiency through upstream measures such as yield improvement and lightweighting might remain underexploited by industry. Established input-output techniques are applied to the GTAP 7 multi-regional input-output model to quantify the incentives for companies in key steel-using sectors (such as property developers and automotive companies) to seek opportunities to improve material efficiency in their upstream supply chains under different short-run carbon price scenarios. Because of the underlying assumptions, the incentives are interpreted as overestimates. The principal result of the paper is that these generous estimates of the incentives for material efficiency caused by a carbon price are offset by the disincentives to material efficiency caused by labour taxes. Reliance on a carbon price alone to deliver material efficiency would therefore be misguided and additional policy interventions to support material efficiency should be considered. © 2013 Elsevier B.V.

1.5 GHz picosecond pulse generation from a monolithic waveguide laser with a graphene-film saturable output coupler

We fabricate a saturable absorber mirror by coating a graphenefilm on an output coupler mirror. This is then used to obtain Q-switched mode-locking from a diode-pumped linear cavity channel waveguide laser inscribed in Ytterbium-doped Bismuthate Glass. The laser produces 1.06 ps pulses at ∼1039 nm, with a 1.5 GHz repetition rate, 48% slope efficiency and 202 mW average output power. This performance is due to the combination of the graphene saturable absorber and the high quality optical waveguides in the laser glass. © 2013 Optical Society of America.

Output feedback H2 model matching for decentralized systems with delays

This paper gives a new solution to the output feedback H2 model matching problem for a large class of delayed information sharing patterns. Existing methods for similar problems typically reduce the decentralized problem to a centralized problem of higher state dimension. In contrast, this paper demonstrates that the decentralized model matching solution can be constructed from the original centralized solution via quadratic programming. © 2013 AACC American Automatic Control Council.

Multi-objective optimisation of horizontal axis wind turbine structure and energy production using aerofoil and blade properties as design variables

The design of wind turbine blades is a true multi-objective engineering task. The aerodynamic effectiveness of the turbine needs to be balanced with the system loads introduced by the rotor. Moreover the problem is not dependent on a single geometric property, but besides other parameters on a combination of aerofoil family and various blade functions. The aim of this paper is therefore to present a tool which can help designers to get a deeper insight into the complexity of the design space and to find a blade design which is likely to have a low cost of energy. For the research we use a Computational Blade Optimisation and Load Deflation Tool (CoBOLDT) to investigate the three extreme point designs obtained from a multi-objective optimisation of turbine thrust, annual energy production as well as mass for a horizontal axis wind turbine blade. The optimisation algorithm utilised is based on Multi-Objective Tabu Search which constitutes the core of CoBOLDT. The methodology is capable to parametrise the spanning aerofoils with two-dimensional Free Form Deformation and blade functions with two tangentially connected cubic splines. After geometry generation we use a panel code to create aerofoil polars and a stationary Blade Element Momentum code to evaluate turbine performance. Finally, the obtained loads are fed into a structural layout module to estimate the mass and stiffness of the current blade by means of a fully stressed design. For the presented test case we chose post optimisation analysis with parallel coordinates to reveal geometrical features of the extreme point designs and to select a compromise design from the Pareto set. The research revealed that a blade with a feasible laminate layout can be obtained, that can increase the energy capture and lower steady state systems loads. The reduced aerofoil camber and an increased L/. D-ratio could be identified as the main drivers. This statement could not be made with other tools of the research community before. © 2013 Elsevier Ltd.

Designing output-feedback predictive controllers by reverse-engineering existing LTI controllers

An approach to designing a constrained output-feedback predictive controller that has the same small-signal properties as a pre-existing output-feedback linear time invariant controller is proposed. Systematic guidelines are proposed to select an appropriate (non-unique) realization of the resulting state observer. A method is proposed to transform a class of offset-free reference tracking controllers into the combination of an observer, steady-state target calculator and predictive controller. The procedure is demonstrated with a numerical example. © 2013 IEEE.

Free energy surface reconstruction from umbrella samples using Gaussian process regression II: Multiple collective variables

We demonstrate how a prior assumption of smoothness can be used to enhance the reconstruction of free energy profiles from multiple umbrella sampling simulations using the Bayesian Gaussian process regression approach. The method we derive allows the concurrent use of histograms and free energy gradients and can easily be extended to include further data. In Part I we review the necessary theory and test the method for one collective variable. We demonstrate improved performance with respect to the weighted histogram analysis method and obtain meaningful error bars without any significant additional computation. In Part II we consider the case of multiple collective variables and compare to a reconstruction using least squares fitting of radial basis functions. We find substantial improvements in the regimes of spatially sparse data or short sampling trajectories. A software implementation is made available on www.libatoms.org.

Output disturbance rejection using parallel model predictive control

The solution time of the online optimization problems inherent to Model Predictive Control (MPC) can become a critical limitation when working in embedded systems. One proposed approach to reduce the solution time is to split the optimization problem into a number of reduced order problems, solve such reduced order problems in parallel and selecting the solution which minimises a global cost function. This approach is known as Parallel MPC. The potential capabilities of disturbance rejection are introduced using a simulation example. The algorithm is implemented in a linearised model of a Boeing 747-200 under nominal flight conditions and with an induced wind disturbance. Under significant output disturbances Parallel MPC provides a significant improvement in performance when compared to Multiplexed MPC (MMPC) and Linear Quadratic Synchronous MPC (SMPC). © 2013 IEEE.