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 There is a need for a smart-washer that can also provide environmental benefits of less pollution, less detergent used and less water usage along with energy benefits of less energy used while still maintaining a good quality of life with clean wash

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 There is a need for a smart-washer that can also provide environmental benefits of less pollution, less detergent used and less water usage along with energy benefits of less energy used while still maintaining a good quality of life with clean wash.

A one month test where an engineer watched a senior citizen do the laundry determined the following facts about a senior citizen, the engineer's mother with a slight case of Alzheimer's, doing the wash. 1.) The existing washing machine environment is full of chaos. 2.) Two detergents are used: the leading national laundry detergent and a delicate/knit/wool laundry detergent. 3.) There are way too many input settings into the washing machine: one is the cold, warm, and hot water temperature setting. The engineer found that hot was never used and that warm was only used for soiled and heavily soiled loads. Cold water produced wonderful results 95% of the time. 4.) There was a pre-wash cycle that was never used. Why would you pre-wash clothes? Why not just use two wash cycles if needed? This never proved necessary during the one month survey period. 4.) The delicate and knit cycles are basically the same cycle with the same light agitation. The delicate cycle is defined as light WEIGHT with low WATER_LEVEL. The knit/wool cycle defined as light WEIGHT with medium to very-high WATER_LEVEL just lasts longer. So just use one delicate/knit/wool cycle with a longer cycle for the heavier knits and wools. 5.) There were two heavily utilized cycles which are similar: one is cotton/sturdy with a continuous time of wash available labeled light soiled, medium soiled, and heavy soiled; while the other is permanent press with a continuous time of wash available labeled light soiled, soiled, and heavy soiled. During the one month survey, lightly soiled cotton/sturdy clothes were the most washed clothes and do not need the heavy agitation that is used on this cycle. The permanent press cycle which is identical to the cotton/sturdy cycle except for moderate agitation versus heavy agitation would suffice for lightly soiled cotton/sturdy clothes. So eliminate the permanent press cycle and make the lightly soiled cotton/sturdy clothes also a permanent press cycle with moderate agitation for both. For the odd load that is soiled or heavily soiled, have a push button on the machine that would choose soiled or heavily soiled for that one load. This cycle would be heavy agitation with warm water with more time given to the heavy soiled load. These are the only two cycles that use warm water and this is designed into the cycle and does not need to be considered in the design of the fuzzy logic controller. All other cycles use cold water. 6.) During the one month survey, only delicates/wools/knits ever took small (less than half WATER_LEVEL) quantity size washes. Permanent press and cotton/sturdy would generally take close to a full tub and never less than half a tub.

We need to invent an automatic laundry detergent feeding mechanism for the machine with two reservoirs: one for regular laundry detergent and one for delicate/knits laundry detergent. The amount of detergent fed is related to the water level. Assume this product is already invented. We need to invent a tub with a weight sensor to determine light loads per volume to identify delicate and knit loads. 

Assume this invention exists for our application. And finally we need to develop some sort of load level device that determines the height of the load once it has been loaded and gently tapped down. This will generate the water level for the wash. Assume this device exists for our smart-washer.

You are the engineer who needs to design a fuzzy logic controller for this smart-washer.

WEIGHT (Light, Medium and Heavy) is read from a sensor. WATER_LEVEL (Low, Medium, High, and Very High/FULL) is read from a sensor. The shortest complete CYCLETIME is ten minutes for delicates with a continuous time longer for more WATER_LEVEL delicates and even more time for wool and knits. The CYCLETIME is a function of the WEIGHT and the WATER_LEVEL. The longest complete cycle is fifty minutes for heavy WEIGHT, Very High WATER_LEVEL and very soiled cotton/sturdy clothes. One output is the continuous CYCLETIME setting (Short, Medium, Long, ExtraLong) of the washing machine system.  Another output is the continuous AGITATION setting (Light, Moderate, and Heavy). The final output is one of either four cycles: two of the cycles are used most of the time: delicate/knit/wools (determined by light WEIGHT), and all others which are lightly soiled cotton/sturdy/permanent press; the other two cycles require pressing a button, soiled cotton/sturdy (press soiled button), heavily-soiled cotton sturdy (press heavily soiled button). The spin/rinse/spin cycles are a dedicated function as part of each wash cycle and do not need to be considered. Assume the detergent delivery is a dedicated function of the wash cycle and water level (less water, less detergent) and does not need to be considered. Using either triangular or trapezoidal membership functions, design the fuzzy logic control system. Show your answer in three steps: 1.) Fuzzification, 2.) Rule Evaluation (Create the rule base) and 3.) Defuzzification 

Assume the WEIGHT scale goes from zero to seven pounds. Assume the CYCLETIME goes from ten to fifty minutes. Assume the AGITATION is a percentage from zero to 100% AGITATION. Assume the "WATER_LEVEL" goes from zero to 100 percent full. The push buttons are off/on, binary (zero, one) buttons and reset after the wash is complete. A "one" overrides the potential algorithm chosen cycle. So the push buttons "on" are not part of the fuzzy logic analysis. These are hard-wired logic in the machine.

Let's do two crisp input scenarios. The first is a load that is 50% full and weighs 0.90 pounds. The second is a load that is 90% full and weighs 6.8 pounds. What are the crisp outputs for these two scenarios using the fuzzy logic controller that you design based on the above information?