Building Distributed Control Systems Using Distributed Active Real-Time Databases

From the field of control theory, we can see that varying communication delays in a control system may be hard or even impossible to handle. From this point of view it is preferable to have these delays bounded and as small and as possible in order to adapt the control process to them. On the other hand, in some cases delays are inevitable and must be handled by the control system. A control system may for different reasons be distributed, e.g., because of a distributed environment or severe environment demands such as heat or dust at some locations. Information in such a system will suffer from delays due to transportation from one place to another. These delays often show up in a random fashion, especially if a general network is used for transportation. Another source of delays is the system environment itself. For predictability reasons a real-time database is preferable if the delays are to be controlled. A straightforward way of handling delays in a control system is to build the system such that delays are constant, i.e., to build a time invariant system. The time from sensor reading to actuation is made constant either by adding a suitable delay to achieve a total constant delay or by using time-triggered reading and actuation. These are simple ways of controlling the delays, but may be very inefficient because worst-case execution time must always be used. Other ways of handling varying delays are by using more tolerant control algorithms. There are two suitable control models proposed by Nilsson (1998) for this purpose. The tolerant algorithm approach is assumed in this work. This thesis uses a distributed active real-time database system as a basis for building control systems. One of the main objectives is to determine how active functionality can be used to express the control system, i.e., how rules in the database can be used to express the control algorithm and for handling propagation of information. Another objective is to look at how the choice of consistency level in the database affects the result of the control system, i.e. how different consistency level affects the delays. Of interest is also to characterize what type of applications each level is suited for