Modeling plant relations
After modeling the plant, for instance the individual sensors and actuators, the relations between the plant automata are to be considered. These relations should be physical relations, representing behavioral restrictions present in the actual uncontrolled system.
For instance, consider a movement with two limit sensors:
plant UpSensor:
uncontrollable u_on, u_off;
location Off:
initial; marked;
edge u_on goto On;
location On:
edge u_off goto Off;
end
plant DownSensor:
uncontrollable u_on, u_off;
location Off:
initial; marked;
edge u_on goto On;
location On:
edge u_off goto Off;
end
Most likely the two sensors physically can’t both be on at the same time. The individual plant automata of the two digital sensors however, can both be in their On
states, as they are not yet in any way related. The easiest way to specify such a relation is to use a state plant invariant:
plant invariant not (UpSensor.On and DownSensor.On);
Alternatively, you may combine multiple plants into a single plant. To merge some plants, manually compute/model the product of the plants, and remove the original plant automata. Then, to express the relationship, remove the behavior that is not physically possible. However, typically using a plant invariant is easier.
An alternative physical relationship, is the relation between sensors and actuators. In such cases, the relationship with the sensor(s) can usually be added directly to the actuator plant(s).
By correctly incorporating all the physical restrictions present in the actual system, the tools can use this knowledge during synthesis. Essentially, by modeling the physical relations/restrictions, the uncontrollable events are enabled in much less (combinations of) locations of the plant automata. This means that the requirements are much less likely to block uncontrollable events.
In other words, the modeled relationships of the plants restrict the behavior of the plant automata. However, these restrictions are also present in the physical system. Hence, without modeling such relationships, the plant model has more behavior than the physical system. Once the plant relations are correctly modeled, you may assume this relationship in the requirements, meaning you may assume that certain uncontrollable events can physically not occur in certain locations. The tools will then have enough knowledge of the system to come to the same conclusions.
For instance, assume a certain sensor signal can only occur when the corresponding actuator is enabled. A movement limit sensor may for instance only be able to go on once a movement completes, which in turn can only happen by enabling the corresponding movement actuator. Modeling this relation ensures that 'blocking' such sensor signals in the requirements, when the actuator is off, is no longer considered 'illegal' behavior.
The next step in the process to apply synthesis-based engineering in practice is to model the requirements.