Robust Lyapunov control design for bioinspired pursuit with autonomous hovercraft

The problem of pursuit has been studied mostly in the context of missile guidance and navigation; however, it is also an essential component in biological systems ranging from prey capture to mating and in bioinspired engineering applications with small agile vehicles. This paper considers the pursuit problem with a focus on robustness to noisy sensor measurements and efficiency in the control effort. We design a pursuit law based on Lyapunov analysis and establish its robustness to unknown target acceleration and measurement errors using the concept of ultimate boundedness. Robustness to control saturation is analyzed using the phase portrait of the closed-loop system. We also present results from experiments that were conducted to study the practical challenges involved in pursuit by lightweight platforms with noisy sensors. These experiments highlight the benefit of using less control effort in the presence of large measurement errors compared with existing pursuit guidance laws.