Wireless communication networks between distributed autonomous systems using self-tuning extremum control

This paper represents an effective optimization approach for building high bandwidth wireless communication networks between distributed autonomous systems using unmanned aerial vehicles as airborne relay nodes. A self-tuning extremum control technique is developed to find an optimal location of the aerial vehicles to provide maximum communication throughputs. The idea behind the self-tuning control is to use an on-line gradient estimator to identify the derivative of a cost function and to use this as an input to a gradient-based hill-climbing algorithm. The on-line estimation of the gradient of a performance function is achieved by utilizing a perturbation-based peek-seeking approach which provides a quantitative gradient value of the cost function in a numerical way. Flight experiments are conducted to evaluate the performance of the proposed airborne wireless sensor networking control algorithm.