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CSCI1600: Embedded and Real Time Software Lecture 8: Modeling III: Hybrid Systems Steven Reiss, Fall 2015
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Time and Finite State Automata We’ve added timing to our automata in an ad-hoc fashion Added timer events Indicated length of time in a state (min/max) No notion of absolute time, clocks, etc. In order to prove properties of the system With respect to time We need a cleaner, more formal representation
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Timed Automata Basic idea Extended finite state machine Add the notion of timer variables (bounded) Timer variables can be set explicitly All timer variables are periodically incremented Can think of this as every k milliseconds But in general it is considered a tick Timer variables can be used in conditions No ad-hoc time constraints
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Timed Automata
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Another example
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Extended timed automata
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Modeling and the Real World Often we want to model both the system and the world The system is a finite automata The real world is continuous & not just clocks Problems How to combine the two What can we do with the combination Understanding Proving properties
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Modeling in the Real World
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Hybrid Automata State variables reflect the real world Updates done over time automatically Updates can use continuous modeling Can specify velocity, acceleration rather than position Can specify rules for doing the update
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Bouncing Ball Example
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RC Car
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Hybrid Timed Automata The external (timed) portion is set outside the automata Rules for continuous update Model the physics of the real world
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Why Model the World? Does the code need to know the state of the real world Either precisely or approximately Does it need to compute that state Or retrieve it via sensors How accurate can you model the world? Consider speed control on a car Proving properties of the program wrt the model Does this prove the system correct
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Implementation Approach Get information from the real world What the actual speed is, change of speed Actual temperature (and change rate) Compute the difference between actual and desired This is called the error Use this to determine the action This is considered feedback
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Control Theory Why are computers called “digital computers” What is the alternative What is an analog computer It turns out that analog computers are easy to build Either mechanically or electronically Predate digital computers
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Analog Computers
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Analog Computer Can do simple math operations Some complex math operations are easy Integration, differentiation
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Controlling Physical Systems Analog computers are designed for this If you want a car to go in a straight line Use feedback from left/right to update steering Use intergrator to determine how much off and to control system Analog control is all about feedback We can do the same in digital systems Covered a week from Monday First we need to cover details for the assignment And some additional modeling concepts
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Homework Read Chapter 7.1
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