Energy-efficient operation of ships is meaningful in maritime applications due to the finite nature of fossil fuel and in order to limit the impact on the environment. The development of waste heat recovery systems combined with control systems has contributed in the optimization of the onboard processes. However, in many scenarios, the processes are subject to numerous sources of uncertainties such as incomplete models, unknown system parameters / states, disturbances etc. that are to be incorporated appropriately. Two particular thermal systems on a ship are investigated, namely a freshwater cooling circuit on the one hand and a multistage flash evaporation plant on the other hand. The thesis is situated in the field of applied control theory with emphasis on the analysis of uncertain systems by means of modelling, estimation and control. Due to incomplete process models of the freshwater cooling circuit, the waste heat recovery process cannot be deduced as several parameters and states are unobserved. They are successfully estimated online by a conditionally Gaussian filter based on noisy measurements. The estimates are further utilized in the design of a model-based feedback controller that stabilizes the unobserved waste heat recovery process around its operating point. Its ensures a steady harvesting of waste heat energy as well as suppressing the propagation of disturbances to adjacent subsystems. The waste heat recovery process is proven to be conditionally Gaussian that inherits beneficial closed-loop properties such as optimal state estimates in the mean-square sense. The same observer concept is applied to a larger cooling network with many more unknown parameters and states. A sequence of two conditionally Gaussian filters estimates the unobserved variables reasonably well. The observer performance is validated against two sets of acquired data from a real ship during operation. Concerning the fresh water production in the multistage evaporation plant, a PDE model is developed for the relevant desalination processes. It presents a convenient framework to study the propagation of noises throughout the plant that are caused by the flow turbulence. The stochastic process is actuated by boundary controls that stabilize the pressure head to a defined reference profile throughout the whole subdomain in order to maintain efficient distillate production. Robust system performance is achieved by evaluating the spatial and temporal statistics of the regulation error field in terms of first four spatial moments and autocorrelation function. The regulation error could successfully maintained within tight bounds in the whole subdomain.
|Translated title of the contribution||Modelling, estimation and control of waste heat recovery and desalination processes in maritime applications|
|Publication status||Published - 2017|
|MoE publication type||G5 Doctoral dissertation (article)|
- Waste heat recovery
- process uncertainties