Modelling and control of nonlinear systems using Gaussian processes with partial model information

Gaussian processes are gaining increasing popularity among the control community, in particular for the modelling of discrete time state space systems. However, it has not been clear how to incorporate model information, in the form of known state relationships, when using a Gaussian process as a predictive model. An obvious example of known prior information is position and velocity related states. Incorporation of such information would be beneficial both computationally and for faster dynamics learning. This paper introduces a method of achieving this, yielding faster dynamics learning and a reduction in computational effort from O(Dn2) to O((D - F)n2) in the prediction stage for a system with D states, F known state relationships and n observations. The effectiveness of the method is demonstrated through its inclusion in the PILCO learning algorithm with application to the swing-up and balance of a torque-limited pendulum and the balancing of a robotic unicycle in simulation. © 2012 IEEE.

What kind of friction model is needed to predict brake squeal?

Predictive models of friction-induced vibration have proved elusive despite decades of research. There are many mechanisms that can cause brake squeal; friction coupled systems can be highly sensitive to small perturbations; and the dynamic properties of friction at the contact zone seem to be poorly understood. This paper describes experimental and theoretical work aimed at identifying the key ingredients of a predictive model. A large-scale experiment was carried out to identify squeal initiations using a pin-on-disc test rig: approximately 30,000 squeal initiations were recorded, covering a very wide range of frequencies. The theoretical model allows for completely general linear systems coupled at a single sliding point by friction: squeal is predicted using a linearised stability analysis. Results will be presented that show that almost all observed squeal events can be predicted within this model framework, but that some subsets require innovative friction modelling: predictions are highly dependent on the particular choice of friction model and its associated parameters. Copyright © 2012 by ASME.

What kind of friction model is needed to predict brake squeal?

Predictive models of friction-induced vibration have proved elusive despite decades of research. There are many mechanisms that can cause brake squeal; friction coupled systems can be highly sensitive to small perturbations; and the dynamic properties of friction at the contact zone seem to be poorly understood. This paper describes experimental and theoretical work aimed at identifying the key ingredients of a predictive model. A large-scale experiment was carried out to identify squeal initiations using a pin-on-disc test rig: approximately 30,000 squeal initiations were recorded, covering a very wide range of frequencies. The theoretical model allows for completely general linear systems coupled at a single sliding point by friction: squeal is predicted using a linearised stability analysis. Results will be presented that show that almost all observed squeal events can be predicted within this model framework, but that some subsets require innovative friction modelling: predictions are highly dependent on the particular choice of friction model and its associated parameters. Copyright © 2012 by ASME.

Accelerated ageing of a stabilised/solidified contaminated soil at elevated temperatures

Despite the widespread use of stabilisation/solidification (S/S) techniques, the validation and the availability of predictive modelling of the behaviour of stabilised/solidified soils in the longer-term is very limited. The authors were involved in the assessment of the behaviour of a contaminated site in the UK treated with cement-based in-situ S/S over the first five years after treatment. In parallel, two experimental methods, namely elevated temperatures and combined elevated temperatures and accelerated carbonation, were used in the laboratory to model accelerated ageing of the site soil. A graphical technique, based on the Arrhenius equation, was then used to model the laboratory observations and the in-situ five-year behaviour. The paper presents the details of the two experimental methods used for the accelerated ageing of stabilised/solidified model site soil, the numerical predictive model and a comparison between the results of the two experimental techniques and with the site results. © 2005 Taylor & Francis Group.