Scalable guidance and control laws for model-scale analysis of autonomous ship landing systems

Due to the potential to expand flight envelopes and increase flight safety for sea-based rotorcraft, there has been a drive to produce reliable autonomous ship landing systems. These systems are complex and must be validated by extensive experimentation. Experimentation at full-scale is often impractical, however, as it relies on the availability of a full-scale ship and aircraft, is expensive, and is subject to outdoor weather conditions. Experimentation at model scale, on the other hand, offers a controllable test bed that can be used to isolate the effects of individual parameter variations. With appropriate dynamic scaling considered during experiment design, the benefits of model-scale testing can be leveraged to gain insight into the limitations and vulnerabilities of a complex landing algorithm. This paper presents easily scalable guidance and control laws that account for reduction in scale via Froude scaling, making for convenient use in model-scale experimentation. The control law utilizes the explicit model following architecture and is integrated with a quadratic programming-based trajectory planner, which incorporates deck motion predictions produced by autoregressive models. The landing algorithm is tested in scaled flight tests to a virtual ship deck, verifying its feasibility and demonstrating its use in model-scale experimentation.