China
Africa
Explore chapters and articles related to this topic
Unraveling Data Science, Artificial Intelligence, and Autonomy
Published in Jay Liebowitz, Data Analytics and AI, 2020
Today, the topic of autonomy is usually associated with robotics. To explore the genesis of robotics and autonomy, it is worth considering the history of automatons. Merriam-Webster’s Dictionary defines automatons as “a mechanism that is relatively self-operating (especially: robot)” or “a machine or control mechanism designed to follow automatically a predetermined sequence of operations or respond to encoded instructions.”
From Function Allocation to Function Congruence
Published in Sidney Dekker, Erik Hollnagel, Coping with Computers in the Cockpit, 2018
An automaton is often described as a state-based machine or a finite state machine, meaning that its behaviour can be described by a set of possible states and the corresponding transition conditions. This is closely tied to a description of the allowable input and output for each state. In general, an automaton can be described by a set of inputs, outputs, internal states and the corresponding state transitions; a classical example of this is the Turing machine. More formally, a finite automaton is a quintuple (e.g. Arbib, 1964; Lemer, 1975): A = (I, O, S, λ, δ) Where: I is the set of inputs, O is the set of outputsS is the set of internal statesλ: S × I → S is the next state function, andδ: S × I → O is the next output function.
Fault Diagnosis of Manufacturing Systems Using Finite State Automata
Published in Javier Campos, Carla Seatzu, Xiaolan Xie, in Manufacturing, 2018
Stéphane Lafortune, Richard Hill, Andrea Paoli
As was explained in Chapters 6 and 10, the logical behaviour of discrete event systems, such as manufacturing systems, is naturally modelled by automata. Automata can be thought of as directed graphs where nodes represent physical states of the system and arcs, which are labelled by event names, and represent discrete transitions of the states upon occurrence of the corresponding events. The events can be internal events of the system (such as a command of a controller to move a part or a sensor that triggers when a part is moving along a conveyor) or exogenous events that represent the effect of the environment on the system (such as an operator pressing a switch). Automata are intuitive to use (when the number of states is small), and at the same time, they provide a mathematical formalism that is amenable to algorithmic analysis using software tools (when the number of states is large). We recall the formal definition of an automaton.
Fault-tolerant supervisory control with permanent faults
Published in International Journal of Control, 2023
Aos Mulahuwaish, Ryan J. Leduc
Supervisory control theory, introduced by Ramadge and Wonham (1987), Wonham (2014), and Wonham and Ramadge (1987), provides a formal framework for analysing discrete-event systems (DES). In this theory, automata are used to model the system to be controlled and the specification for the desired system behaviour. The theory provides methods and algorithms to obtain a supervisor that ensures the system will produce the desired behaviour. It is typically applied to systems that lend themselves to being modelled as state machines.
Modelling and temporal evaluation of networked control systems using timed automata with guards and (max,+) algebra
Published in International Journal of Systems Science, 2018
One of the advantages of automata is the composition which reduces the modelling effort. This is equivalent to represent each component of the system by an automaton and then compose all of them to express the whole behaviour of the system with generally a more complex model. Thus, the modelling of distributed and asynchronous systems, such as production lines, transport networks and other modular systems, is possible provided that the behaviour of the modules constituting it is known.