There is some degree of separation between the development of advanced control algorithms within the research community and their use in industrial practice. Several strategies developed from experimental research into improving the efficiency of solar thermal power plants are here examined in the context of their industrial application. The techniques described and applied are the modelling and simulation of solar processes, robust control, adaptive control, model-based predictive control and fuzzy logic control. Their effectiveness is assessed and the various techniques' advantages and drawbacks are analyzed and compared. The results obtained can be readily extended to other industrial processes; in this context, the solar control process examined provides an ideal test-bed since it exhibits many of the problems found in other processes, such as nonlinearities, changing dynamics and strong external disturbances.