Freeze Dried Fuzzy Logic

 

My hobby is backpacking. When you backpack you carry everything on your back, so you quickly become obsessed with how much everything weighs. One of the biggest challenges I typically face is meal planning – food is heavy, bulky and often perishable.  As a result of this challenge, backpackers typically carry freeze dried food.

Freeze-drying is a complex and amazing process.  Food is frozen to between -30 to -50 degrees Fahrenheit. Once frozen, the freeze dryer creates a vacuum in the food chamber. The food is gradually warmed and since water in a vacuum cannot exist in a liquid state, any water in the food sublimates turning directly from a solid to a gas. The gas accumulates as ice on the sides of the food chamber.

Recently I purchased a home freeze dryer so I could freeze dry a wide variety of foods to take on our trips. It is a simple to use, yet complex piece of technology. I place the food in the machine, push the start button and it lets me know when the food is ready. The entire process is automatic and controlled by a computer all thanks to fuzzy logic.

Fuzzy logic is an approach to computing based on “degrees of truth” rather than the Deanna-Wenstrupusual “true or false” (1 or 0) Boolean logic on which the modern computer is based.

The fuzzy sets theory was first proposed by UC Berkeley professor Lotfi Zadeh in 1965. This led to fuzzy logic, which was proposed in 1973. Fuzzy sets theory has to do with mathematical sets or groups of items known as elements. In most mathematical sets, an element either belongs to the set or it doesn’t. For example, a Blue Jay would belong to a set of birds, but a bat would not since it is a mammal. In fuzzy logic, elements can belong to sets in varying degrees. So since a bat has wings, it might belong to a set of birds — but only to a certain extent.

Fuzzy logic is a way to program machines so they look at the world in a more human way, with degrees of truth. Instead of hard parameters and strict data sets where the answer is either true or false (1 or 0), fuzzy logic assumes a more practical approach. Using numbers, it incorporates non-definitive words like “slightly” or “almost” into its decision-making processes.

As a result, the use of fuzzy logic in freeze dryers helps to ensure properly freeze dried food because it gives the appliance the ability to make judgment calls similar to those a person might make. Rather than just running for a fixed period of time like 12 hours, the freeze dryer adjusts drying time and vacuum pressure based on factors such as rate of sublimation and moisture content in the food

Although we probably don’t realize it, fuzzy logic is all around us and used in a variety of everyday items:

  • Air Conditioners: Old AC’s used simple on-off mechanism. When the temperature dropped below a preset level, the AC was turned off. When it rose above a preset level, the AC was turned on. There was a slight gap between the two preset values to avoid high-frequency on-off cycling. An example would be “When the temperature rises above 70 F, turn on the unit, and when the temperature falls below 69 F, turn off the unit”. Using Fuzzy Rules like “If the ambient air is getting warmer, turn the cooling power up a little; if the air is getting chilly, turn the cooling power down moderately” etc. The machine will become smoother as a result of this and give more consistent comfortable room temperatures.
  • Automatic Gear Transmission System: It uses several variables like speed, acceleration, throttle opening, the rate of change of throttle opening, engine load and assigns a weight to each of these. A Fuzzy aggregate is calculated from these weights and is used to decide whether to shift gears.
  • Washing Machine: Sense the load size, detergent amount etc. Keep a track of the water clarity. At the start of the cycle, the water will be clean and will allow light to pass through it easily. As the wash cycle proceeds, the water becomes discolored and allows less light to pass through it. This information is used and control decisions are made.
  • Reading: Hand-written input and interpreting the characters for data entry.
  • Cell phone texting uses previously sent texts to determine the probable next word in the sentence you are typing
  • Television: A Fuzzy logic scheme uses sensed variables such as ambient lighting, time of the day and user profile to adjust parameters such as screen brightness, color, contrast, and sound.
  • Criminal Search System: Helps in a criminal investigation by analyzing photos of the suspects along with their characteristics like “tall, young-looking..” from witnesses to determine the most likely criminals.
  • Online Disease Diagnostic System: Analyses the user’s symptoms and tries to identify the disease he/she may be suffering from.

So the next time you look at an appliance and ponder how it works, it might be looking at you and thinking the same thing.

 

About Deanna Wenstrup

Deanna has 28 years of experience in production scheduling and planning, linear program and expert systems design, development, implementation, and interfacing to external databases.

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