63 lines
4.1 KiB
Markdown
63 lines
4.1 KiB
Markdown
The quick brown fox jumps over the lazy dog. The dog stays blissfully asleep. :)
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The goal of this project is to surpass sampling rate limitations of a successive
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approximation analog to digital converter by utilizing a modified
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observer to perform control on incomplete successive approximation data, while
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refining control based on latent sensor resolution.
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When a sensor makes an observation about a physical phenomena, the output of that
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sensor is a continuously changing value. Most modern control implementations,
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however, operate on computers that use a discrete space of values that can be
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expressed in memory. This creates an issue, where the continuous value of
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interest output by a sensor must be converted into a discrete equivalent that
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the controller can use. This step is processed by a special sensor interface
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circuit component called an analog to digital converter (ADC)
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\cite{modern_sensor_handbook}. ADCs jobs are to interpret the continuous signal
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of the sensor, and deliver the digital equivalent that can then be used for
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control.
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One type of ADC is especially common in microcontrollers today. The successive
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approximation (SAR) ADC converts analog signals to a digital equivalent by
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comparing the input voltage to a series of reference voltages controlled by
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a logical circuit. This conversion compares the input first to the most
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significant bit of the digital representation, and evaluates whether the
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input voltage is above or below the reference value. If the input voltage is
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higher than this value, the corresponding digital value must have a `1` in
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that location, while if the input voltage is less than the reference, it
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must have a `0` for that bit. The SAR ADC repeats this process for the number
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of bits required to complete a sample (usually about 12 bits). This series of
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comparisons happens one bit at a time, and must happen in the order of most
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significant bit to least significant bit.
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SAR ARC components must balance three competing design requirements: power
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usage, sampling speed, and noise rejection \cite{paper_about_adc}. The internal
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components of a SAR ADC are usually some configuration of capacitors that sample
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voltage from a certain instant, hold that sample throughout comparison, and
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perform the comparisons themselves. All of these processes take a significant
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amount of time complete, and due to the requirements of SAR ADCs to reject
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noise and limit power consumption, are difficult to speed up without incurring
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significant cost. These SAR ADC usually operate on their own internal clock
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that is much slower than the CPU clock on the broader controller. For example,
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the built-in ADC converters on the Atmel ATMega328P microcontroller commonly found
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in the Arduino Uno boards, has a maximum 10-bit analog to digital conversion
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rate of 15,000 samples per second. In comparison, the CPU on the ATmega328P can
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operate as quickly as 20 MHz when using an external clock \cite{ATmega_user_manual}.
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This means for a ATMega328P microcontroller utilizing ADC conversion, the CPU
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may spend a significant amount of time between control computations just waiting
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for an updated sensor value.
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There is potential that this waiting can be circumnavigated. If the memory
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registers of the SAR ADC can be accessed while it is actively building a
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sample, the first significant bits can be used in combination with a state
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estimation to perform control while the rest of the sample is still being
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generated. For this project, I will implement such a system.
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For this project, a simulated SAR ADC will be created. This simulated SAR ADC
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will be created to mimic the register behavior of the SAR ADC found on the
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ATMega328P, where the data registers are updated one by one on each clock cycle,
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and a flag register is utilized to indicate a conversion has finished. This
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simulated SAR ADC will be paired with a simulated controller operating
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*explain how SAR updates registers continuously for some devices. perhaps we can use first couple bits with a state estimator to make a guess what the final value will be and do control. then as we get mroe info, and with our model of the system, we can correct for how wrong we were*
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