Optimizing fuzzy control of energy harvesting remote monitoring systems

The operational lifetime of remote monitoring systems can be extended using energy harvesting techniques. Environmental energy is limited and intermittent so energy management is necessary for effective implementation and optimal performance. The objective of remote monitoring is to acquire the highest quality data possible within this energy-constrained environment. A simulator is used to facilitate the exploration and optimization of energy management strategies for environmental monitoring stations in the Canadian Arctic. The original simulator was designed to facilitate testing and demonstrate proof of concept; now that the original simulator has proven effective, the fuzzy control system used for energy management within the simulator can be improved with data quality in mind. By shifting the focus of the controller from the time domain to the state domain, improving the detail of the load model, increasing the flexibility of the control scheme, and implementing a data-centric approach to the optimization, the simulator and its controller can be significantly improved. Future work will restructure the fuzzy controller to address these improvements and work towards implementing the controller in a practical setting.