With the recent development of reliable autonomous technologies for small unmanned air vehicles (UAVs), the algorithms utilizing teams of these vehicles are becoming an increasingly important research area. Unfortunately, there is no unified framework into which all (or even most) cooperative control problems fall. Five factors that affect the development of cooperative control algorithms are objective coupling, communication, completeness, robustness, and efficiency. We classify cooperative control algorithms by these factors and then present three algorithms with application to target and perimeter surveillance and a method for decentralized algorithm design. The primary contributions of this research are the development and analysis of decentralized algorithms for perimeter and target surveillance. We pose the cooperative perimeter surveillance problem and offer a decentralized solution that accounts for perimeter growth (expanding or contracting) and insertion/deletion of team members. By identifying and sharing the critical coordination information and by exploiting the known communication topology, only a small communication range is required for accurate performance. Convergence of the algorithm to the optimal configuration is proven to occur in finite-time. Simulation and hardware results are presented that demonstrate the applicability of the solution. For single target surveillance, a team of UAVs angularly spaced (i.e. in the splay state configuration) provides the best coverage of the target in a wide variety of circumstances. We propose a decentralized algorithm to achieve the splay state configuration for a team of UAVs tracking a moving target and derive the allowable bounds on target velocity to generate a feasible solution as well as show that, near equilibrium, the overall system is exponentially stable. Monte Carlo simulations indicate that the surveillance algorithm is asymptotically stable for arbitrary initial conditions. We conclude with high fidelity simulation and actual flight tests to show the applicability of the splay state controller to unmanned air systems.

The ability to gather and process information regarding the condition of forest fires is essential to cost-effective, safe, and efficient fire fighting. Advances in sensory and autopilot technology have made miniature unmanned aerial systems (UASs) an important tool in the acquisition of information. This thesis addresses some of the challenges faced when employing UASs for forest-fire perimeter surveillance; namely, perimeter tracking, cooperative perimeter surveillance, and path planning. Solutions to the first two issues are presented and a method for understanding path planning within the context of a forest-fire environment is demonstrated. Both simulation and hardware results are provided for each solution.