Advanced Building Simulation

Self-organizing models for sentient buildings 167
is distributed among the controllers must be explicitly organized. The control process
model must be created using a logical, coherent, and reproducible method, so that it
can be used for a diverse set of building control applications. Ideally, the procedure
for the generation of such a control process model should be automated, given its
complexity, and given the required flexibility, to dynamically accommodate changes
over time in the configuration of the controlled entities, control devices, and their
respective controllers.
7.3.6 Automated generation of control system representation
We have developed and tested a set of constitutive rules that allow for the automated
generation of the control system model (Mahdavi 2001a,b). Such a model can provide
a template (or framework) of distributed nodes which can contain various methods
and algorithms for control decision-making. Specifically, five model-generation rules
are applied successively to the control problem, resulting in a unique configuration of
nodes that constitute the representational framework for a given control context. The
first three rules are generative in nature, whereas rules 4 and 5 are meant to ensure
the integrity of the generated model. The rules may be stated as follows:
1 Multiple devices of the same type that are differentially controllable and that
affect the same sensor necessitate an MC.
2 More than one device of different types that affect the same sensor necessitates
an MC.
3 More than one first-order MC affecting the same device controller necessitates a
second-order (higher-level) MC.
4 If in the process a new node has been generated whose functionality duplicates
that of an existing node, then it must be removed.
5 If rule 4 has been applied, any resulting isolated nodes must be reconnected.
The following example illustrates the application of these rules (Mertz and Mahdavi
2003). The scenario includes two adjacent rooms (see Figure 7.6), each with four
luminaires and one local heating valve, which share an exterior movable louvers. Hot
water is provided by the central system, which modulates the pump and valve state
to achieve the desired water supply temperature. In each space, illuminance and temperature
is to be maintained within the set-point range. This configuration of spaces
and devices stems from an actual building, namely the Intelligent Workplace (IW) at
Carnegie Mellon University, Pittsburgh, USA (Mahdavi et al. 1999c).
One way of approaching the definition of control zones (controlled entities) is to
describe the relationship between the sensors and devices. From the control system
point of view, controlled entities are “represented” by sensors, and the influence of
devices on the controlled entities is monitored via sensory information. In the present
example, an interior illuminance sensor (E) and a temperature sensor (t) are located
in each space. The sensors for Space-1 are called E 1 and t 1, and those for Space-2 are
called E 2 and t 2. In Space-1, both the louvers and electric lights can be used to meet
the illumination requirements. As shown in Figure 7.7, sensor E 1 is influenced by the
louver state, controlled by DC-Lo1, as well as by the state of four electric lights, each