Robust Safety Tracking Control of UAHs via Control Barrier Function-Based Self-Adjustable Prescribed Performance and Disturbance Observer

Abstract

This paper develops a robust safety tracking control framework for unmanned aerial helicopter (UAH) systems subject to output constraints, input saturation, and external disturbances. To achieve this objective, a prescribed-time disturbance observer (PTDO) is first designed to estimate and compensate for unknown disturbances within a designer-specified time. Then, dynamic high-order control barrier functions (DHOCBFs) are constructed using positive system theory, where time-varying parameters are introduced to enhance feasibility under multiple safety constraints and input saturation. Building on the DHOCBF mechanism, auxiliary positive systems are employed to generate self-adjustable prescribed-performance bounds, allowing the performance envelope to expand adaptively when safety, performance, and input constraints conflict. The resulting optimization-based controller integrates robust DHOCBF constraints, prescribed-performance constraints, input bounds, and a relaxed control Lyapunov function condition to ensure safe and practical tracking. Numerical simulations on a UAH model validate the effectiveness of the proposed method. Note to Practitioners—This paper is motivated by safety-critical UAH operations in low-altitude inspection, infrastructure monitoring, and emergency response, where the aircraft is required to track a desired trajectory while output and input constraints are satisfied under disturbances. To meet these requirements, a robust safety tracking framework is developed by integrating the PTDO, DHOCBF, and self-adjustable prescribed performance. Unknown disturbances are estimated and compensated within a designer-specified time by the PTDO, thereby improving robustness against wind-like disturbances. Multiple output and input constraints are incorporated by the DHOCBF into a unified quadratic program, and online feasibility is enhanced under actuator saturation. Self-adjustable performance bounds are further generated by auxiliary positive systems, so that the performance envelope is allowed to relax according to operating conditions rather than being fixed conservatively in advance. The resulting controller can be implemented as an optimization-based safety filter for UAH and can be extended to related safety-critical aerial platforms.