Cooperative Control of Distributed Autonomous Systems with Applications to Wireless Sensor Networks

This thesis extends previously developed self-tuning adaptive control algorithms to be applied to a scenario where multiple vehicles autonomously form a communication chain which maximizes the bandwidth of a wireless sensor network. In the simulated scenario, multiple unmanned aerial vehicles are guided to positions that optimize communication links between multiple ground antennas. Guidance is provided by a self-tuning extremum controller, which uses adaptive techniques to autonomously guide a vehicle to the optimal location with respect to a cost function in an uncertain and noisy environment. In the case of high-bandwidth communication, this optimal location is the point where signal-to-noise ratio is maximized between two antennas. Using UAVs as relay nodes, an optimized communication chain allows for greater communication range and bandwidth across a network. Control system models are developed and tested using computer and hardware-in-the-loop simulations, which will be validated with a flight test at a future date.