Energy-neutral operation (ENO) is a major concern for Internet of things (IoT) sensor systems. Animals can be tagged with IoT sensors to monitor their movement and behavior. These sensors wirelessly upload collected data and can receive parameters to change their operation. Typically, the behavior monitors are powered by a battery where the system relies upon harvesting solar radiation for sustainable operation. Solar panels typically are used as the harvesting mechanism and can have a level of uncertainty regarding consistent energy delivery due to factors such as adverse weather, foliage, time of day, and individual animal behavior. The variability of available energy inevitably creates a trade-off in the rate at which data can be collected with respect to incoming and stored energy. The objective of this research was to investigate and simulate methods and parameters that can control the data collection rate of an IoT behavior monitor to achieve sustained operation with unknown and random energy harvesting. Analysis and development of a control system were performed by creating a software model of energy consumption and then simulating using different initial conditions and random energy harvesting rates for evaluation. The contribution of this effort was the exploration into the usage of a discrete-time gain scheduled Proportional–Integral–Derivative (PID) that was tuned to a specific device configuration, using battery state of charge as an input, and found to maintain a battery level set-point, reject small solar harvesting energy disturbances, and maintain a consistent data collection rate throughout the day.
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