Adaptive Formation Control and Bio-inspired Optimization of a Cluster-based Satellite Wireless Sensor Network

In this paper, adaptive formation control and bio-inspired optimization are jointly addressed for a cluster-based satellite wireless sensor network in which there are multiple satellites flying in formation (MSFF) in the presence of unknown disturbances. The full nonlinear dynamics model describing the relative positioning of the MSFF system is used to develop an adaptive formation controller. First, the original nonlinear system is transformed into a linear controllable system with aperturbation term by invoking the input-output feedback linearization technique. Second, by using the integral feedback design scheme, the adaptive formation controller is presented for improving the steady-state performance of the MSFF system in the presence of unknown disturbances. Third, as a currently popular bio-inspired algorithm, PSO (particle swarm optimizer) is employed to minimize the total energy consumption under the required quality of service by jointly optimizing the transmission power and rate for each satellite. Simulation results are provided to demonstrate the effectiveness of the adaptive formation controller and the PSO-based optimization for saving the total communication energy.