Algorithms for adaptive stochastic control for a class of linear systems

Control of linear, discrete time, stochastic systems with unknown control gain parameters is discussed. Two suboptimal adaptive control schemes are derived: one is based on underestimating future control and the other is based on overestimating future control. Both schemes require little on-line computation and incorporate in their control laws some information on estimation errors. The performance of these laws is studied by Monte Carlo simulations on a computer. Two single input, third order systems are considered, one stable and the other unstable, and the performance of the two adaptive control schemes is compared with that of the scheme based on enforced certainty equivalence and the scheme where the control gain parameters are known

A multi-spacecraft reanalysis of the atmosphere of Mars

We have conducted a nine-Mars Year (MY) consistent reanalysis of the martian atmosphere covering the period MY 24–32 and making use of data from three different spacecraft. Remotely-sensed measurements of temperature, dust opacity, water ice and ozone from NASA’s Mars Global Surveyor (MGS) and Mars Recconaisance Orbiter (MRO) and ESA’s Mars Express (MEx) were assimilated [1] into a single model simulation, sampled two-hourly over the whole period. This forms a large, regular reanalysis dataset that is being made publicly available as an output of the EU UPWARDS project. The same analysis technique, with an improved model and higher resolution will be conducted with ESA Trace Gas Orbiter (TGO) data as it becomes available

Assimilating the Martian water cycle

Water ice clouds have been shown to alter the thermal structure of the Martian atmosphere. Here we discuss the assimilation of total column water vapour and dust optical depth data from the Thermal Emission Spectrometer (TES) into the UK/LMD MGCM, and compare the predictions of cloud and temperature in the assimilation with observations

Trace gas assimilation of Mars orbiter observations

Ozone, water vapour and argon are minor constituents in the Martian atmosphere, observations of which can be of use in constraining atmospheric dynamical and physical processes. This is especially true in the winter season of each hemisphere, when the bulk of the main constituent in the atmosphere (CO2 ) condenses in the polar regions shifting the balance of atmospheric composition to a more trace gas rich air mass. Current Mars Global Circulation Models (MGCMs) are able to represent the photochemistry occuring in the atmosphere, with constraints being imposed by comparisons with observations. However, a long term comparison using data assimilation provides a more robust constraint on the model. We aim to provide a technique for trace gas data assimilation for the analysis of observations from current and future satellite missions (such as ExoMars) which observe the spatial and temporal distribution of trace gases on Mars

The circulatory impact of dust from dust profile assimilation

We present results from a reanalysis of temperatures, dust columns and dust vertical profiles focussing on the assimilation, distribution and transport of dust in the martian atmosphere. The assimilation of dust vertical information in particular is a valuable technique which has been shown to be of vital importance to a successful assimilation of the martian atmosphere, with the vertical representation of the dust distribution having a critical effect on assimilation results generally. Atmospheric dust is a key driver of the martian circulation. Dust-induced heating and cooling is a potential feedback mechanism for dust lifting, for example, and can modify the circulation to either enhance or suppress dust storm activity. Accurately representing its complex spatial and temporal distribution is therefore crucial for understanding Mars’ atmospheric dynamics and transport