Adaptive Vision-Based Guidance Law with Guaranteed Performance Bounds

摘要

This work discusses vision-based tracking of a ground vehicle moving with unknown time-varying velocity. Thernfollower unmanned aerial vehicle is equipped with a single camera. The control objective is to regulate the two-rndimensional horizontal range between the unmanned aerial vehicle and the target to a constant. The contribution ofrnthis paper has two distinct features. The developed guidance law uses the estimates of the target’s velocity obtainedrnfrom a fast-estimation scheme. It is shown that the fast-estimation scheme has guaranteed performance bounds andrnthe tracking performance bound can be explicitly derived as a function of the estimation error. The performancernbounds imply that the signals of the closed-loop adaptive system remain close to the corresponding signals of arnbounded closed-loop reference system, both in transient and steady-state responses. The reference system isrnintroduced solely for the purpose of analysis. This paper also analyzes the stability and the performance degradationrnof the closed-loop adaptive system in the presence of out-of-frame events, when continuous extraction of the target’srninformation is not feasible due to failures in the image-processingmodule. The feedback loop is then closed using thernfrozen estimates. The out-of-frame events are modeled as brief instabilities. A sufficient condition for the switchingrnsignal is derived that guarantees graceful degradation of performance during target loss. The results build upon thernearlier-developed fast-estimation scheme of the target’s velocity, the inverse-kinematics-based guidance law, andrninsights from switching systems theory.