In this case, the current inputs, as well as current states, will decide the next states. Thus, depending on further states, this machine will generate the outputs. So, the outputs of this will be applicable simply after the conversion of the state. The Moore state machine state diagram is shown below. In the above state, the diagram includes four states like a mealy state machine namely A, B, C, and D. These states and the respective outputs are labeled inside the circles.
Here, simply the input worth is marked on every conversion. In the above figure includes two conversions from every state depending on the input value. Generally, the amount of required states in this machine is greater than otherwise equivalent to the required number of states in the mealy state machine. Generally, the number of required states in this machine is more than otherwise equivalent to the required states in MSM Mealy state machine.
For every Moore state machine, there is a corresponding Mealy state machine. Consequently, depending on the necessity we can utilize one of them. There is an equal mealy state machine for every Moore state machine. The finite state machine applications mainly include the following. FSMs are used in games; they are most recognized for being utilized in artificial intelligence , and however, they are also frequent in executions of navigating parsing text, input handling of the customer, as well as network protocols.
These are restricted in computational power; they have the good quality of being comparatively simple to recognize. So, they are frequently used by software developers as well as system designers for summarizing the performance of a difficult system. The finite state machines are applicable in vending machines, video games, traffic lights, controllers in CPU, text parsing, analysis of protocol, recognition of speech , language processing, etc.
The advantages of Finite State Machine include the following. Be aware that both state diagrams, the Moore machine above and the Mealy one, describe exactly the same system. Indeed, automata theory states that you can always translate a Moore machine into a Mealy machine and vice versa, without losing any expressiveness.
Although Mealy machines can already reduce the number of required states, for complex systems such automatons get easily unmanageable. Harel concluded that " a state approach must be modular, hierarchical and well-structured" and introduced additional concepts like state composition and orthogonality. Using composite states and sub diagrams, we are able to bring more depth into state diagrams, while keeping the diagrams clear and well-structured.
Regions help us to express orthogonality : Different substate machines that can be executed side by side.
Events allow us to achieve broadcast communication and give us a strong means to describe complex behavior. Using guards, we can state that a certain event triggers a transition only if a given condition is met. Inter-level transitions, history states, temporal logic as well as entry, exit and throughout actions are further Harel statechart elements.
Harel statecharts can define variables which can be used in input and output expressions. Regarding the light switch example, this allows us to store the brightness level in a variable instead of a number of states. In that way, we can simplify the statechart by merging all Light On states into one and executing the output actions on a self-transition. Here we just increment the brightness value each time the transition is taken.
We use the modulo expression to ensure the brightness value stays between 1 and 3. This has the benefit that we can change the number of brightness levels without adding new states.
To showcase the use of composite states we extend the light switch example by a motion detection mode. When the MOT button is pressed, the motion sensor is activated. This can be modeled with a composite state that groups the two states Motion Detected and No Motion Detected together. Extended light switch example as a Harel statechart with composite states.
Please also note that Harel statecharts combine the characteristics of Mealy and Moore machines, hence outputs can be produced by states as well as transitions as indicated in the statechart above. We can even go one step further and hide the logic of the Motion Detection Mode into a sub diagram. In that way, the system gets more comprehensive as one can directly see the different modes and how to switch between them.
Extended light switch example as a Harel statechart with sub diagrams. Further concepts like orthogonality or history states are left out here for brevity. You can read about them in our quick reference. UML state machines are based on the statechart notation introduced by David Harel. It is used to transit the any number of states for a particular input.
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