This paper discusses various practical problems arising in the design and simulation of predictive control methods for adaptive optics. Although there has been increased attention towards optimal prediction and control methods for AO systems, they are often tested in simplified simulation environments. The use of advanced AO simulators however, is a valuable alternative to the use of real data or laboratory experiments, as they provide both a flexible environment which is ideal for testing a new algorithm and are more accessible to non-experts. Topics that are often not explicitly discussed, such as the identification of a turbulence dynamics model from data, the use of matrix structures in AO systems to decrease the computational complexity and the implementation of Kalman filters to optimally deal with realistic noise conditions are examined. All topics discussed are illustrated by an accompanying Matlab code, which is based on the existing Matlab AO toolbox OOMAO.