Structure learning in action.

'Learning to learn' phenomena have been widely investigated in cognition, perception and more recently also in action. During concept learning tasks, for example, it has been suggested that characteristic features are abstracted from a set of examples with the consequence that learning of similar tasks is facilitated-a process termed 'learning to learn'. From a computational point of view such an extraction of invariants can be regarded as learning of an underlying structure. Here we review the evidence for structure learning as a 'learning to learn' mechanism, especially in sensorimotor control where the motor system has to adapt to variable environments. We review studies demonstrating that common features of variable environments are extracted during sensorimotor learning and exploited for efficient adaptation in novel tasks. We conclude that structure learning plays a fundamental role in skill learning and may underlie the unsurpassed flexibility and adaptability of the motor system.

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.

Optimal constraint tightening policies for robust variable horizon model predictive control

This paper develops a technique for improving the region of attraction of a robust variable horizon model predictive controller. It considers a constrained discrete-time linear system acted upon by a bounded, but unknown time-varying state disturbance. Using constraint tightening for robustness, it is shown how the tightening policy, parameterised as direct feedback on the disturbance, can be optimised to increase the volume of an inner approximation to the controller's true region of attraction. Numerical examples demonstrate the benefits of the policy in increasing region of attraction volume and decreasing the maximum prediction horizon length. © 2012 IEEE.

Simulating dynamic covariance structures for testing the adaptive behavior of variable selection algorithms (Invited Paper)

Variable selection for regression is a classical statistical problem, motivated by concerns that too large a number of covariates may bring about overfitting and unnecessarily high measurement costs. Novel difficulties arise in streaming contexts, where the correlation structure of the process may be drifting, in which case it must be constantly tracked so that selections may be revised accordingly. A particularly interesting phenomenon is that non-selected covariates become missing variables, inducing bias on subsequent decisions. This raises an intricate exploration-exploitation tradeoff, whose dependence on the covariance tracking algorithm and the choice of variable selection scheme is too complex to be dealt with analytically. We hence capitalise on the strength of simulations to explore this problem, taking the opportunity to tackle the difficult task of simulating dynamic correlation structures. © 2008 IEEE.

Electronic structure of the layered ferroelectric perovskite SrBi2Ta2O9

The band structure of the Bi layered perovskite SrBi2Ta2O9 (SBT) has been calculated by the tight binding method. We find both the valence and conduction band edges to consist of states primarily derived from the Bi-O layer rather than the perovskite Sr-Ta-O block. The valence band maximum arises from O p and some Bi s states, while the conduction band minimum consists of Bi p states, with a band gap of 5.1 eV. It is argued that the Bi-O layers largely control the electronic response of SBT while the ferroelectric response originates from the perovskite Sr-Ta-O block. Bi and Ta centered traps are calculated to be shallow, which may account in part for the excellent fatigue properties of SBT.

Electronic structure of the ferroelectric layered perovskite SrBi2Ta2O9

The band structure of the layered perovskite SrBi2Ta2O9 (SBT) was calculated by tight binding and the valence band density of states was measured by x-ray photoemission spectroscopy. We find both the valence and conduction band edges to consist of states primarily derived from the Bi-O layer rather than the perovskite Sr-Ta-O blocks. The valence band maximum arises from O p and some Bi s states, while the conduction band minimum consists of Bi p states, with a wide band gap of 5.1 eV. It is argued that the Bi-O layers largely control the electronic response whereas the ferroelectric response originates mainly from the perovskite Sr-Ta-O block. Bi and Ta centered traps are calculated to be shallow, which may account in part for its excellent fatigue properties. © 1996 American Institute of Physics.

Experimental investigation of a control method for SI-HCCI-SI transition in a multi-cylinder gasoline engine

In HCCI engines, the Air/Fuel Ratio (AFR) and Residual Gas Fraction (RGF) are difficult to control during the SI-HCCI-SI transition, and this may result in incomplete combustion and/or high pressure raise rates. As a result, there may be undesirably high engine load fluctuations. The objectives of this work are to further understand this process and develop control methods to minimize these load fluctuations. This paper presents data on instantaneous AFR and RGF measurements, both taken by novel experimental techniques. The data provides an insight into the cyclic AFR and RGF fluctuations during the switch. These results suggest that the relatively slow change in the intake Manifold Air Pressure (MAP) and actuation time of the Variable Valve Timing (VVT) are the main causes of undesired AFR and RGF fluctuations, and hence an unacceptable Net IMEP (NIMEP) fluctuation. We also found large cylinder-to-cylinder AFR variations during the transition. Therefore, besides throttle opening control and VVT shifting, cyclic and individual cylinder fuel injection control is necessary to achieve a smooth transition. The control method was developed and implemented in a test engine, and the result was a considerably reduced NIMEP fluctuation during the mode switch. The instantaneous AFR and RGF measurements could furthermore be adopted to develop more sophisticated control methods for SI-HCCI-SI transitions. © 2010 SAE International.