This research aims to develop an analysis and control methodology for the multiple un-manned aerial vehicles (UAVs), connected over a communication network. The wireless communication network between the UAVs is vulnerable to errors and time delays, which may lead to performance degradation or even instability. Analysis on the effects of the potential communication constraints in the multiple UAV control is a critical issue for successful operation of multiple UAVs. Therefore, this thesis proposes a systematic method by incorporating three steps: proposing the analysis method and metrics considering the wireless communication dynamics, designing the structure of the cooperative controller for UAVs, and applying the analysis method to the proposed control in representative applications.
For simplicity and general insights on the effect of communication topology, a net-worked system is first analysed without considering the agent or communication dynamics. The network theory specifies important characteristics such as robustness, effectiveness, and synchronisability with respect to the network topology. This research not only reveals the trade-off relationship among the network properties, but also proposes a multi-objective optimisation (MOO) method to find the optimal network topology considering these trade-offs.
Extending the analysis to the networked control system with agent and communication dynamics, the effect of the network topology with respect to system dynamics and time delays should be considered. To this end, the effect of communication dynamics is then analysed in the perspective of robustness and performance of the controller. The key philosophy behind this analysis is to approximate the networked control system as a transfer function, and to apply the concepts such as stability margin and sensitivity function in the control theory.
Through the analysis, it is shown that the information sharing between the agents to determine their control input deteriorates the robustness of their stability against system uncertainties. In order to compensate the robustness and cancel out the effect of uncertainties, this thesis also develops two different adaptive control methods. The proposed adaptive control methods in this research aim to cope with unmatched uncertainty and time-varying parameter uncertainty, respectively. The effect of unmatched uncertainty is reduced on the nominal performance of the controller, using the parameter-robust linear quadratic Gaussian method and adaptive term. On the other hand, time-varying parameter uncertainty is estimated without requiring the persistent excitation using concurrent learning with the directional forgetting algorithm. The stability of the tracking and parameter estimation error is proved using Lyapunov analysis.
The proposed analysis method and control design are demonstrated in two application examples of a formation control problem without any physical interconnection between the agents, and an interconnected slung-load transportation system. The performance of the proposed controllers and the effect of topology and delay on the system performance are evaluated either analytically or numerically.PhD in Aerospac
