Johannes Autenrieb

Mark Spiller, Lennart Kracke, Johannes Autenrieb

Many unmanned aerial vehicles (UAVs) can remain aerodynamically flyable after sustaining structural or control surface damage, yet insufficient robustness in conventional autopilots often leads to mission failure. This paper proposes a robust adaptive sliding mode controller (RASMC) for fixed-wing UAVs subject to aerodynamic coefficient perturbations and partial loss of control surface effectiveness. A damage-aware flight dynamics model is developed to systematically analyze the impact of such impairments on the closed-loop behavior. The RASMC is designed to ensure reliable tracking and stabilization, while a gain adaptation law maintains low control effort under nominal conditions and increases the gains as needed in the presence of aerodynamic damage. Lyapunov-based stability guarantees are derived, and assumptions on admissible uncertainty bounds are formulated to characterize the limits within which closed-loop stability and performance can be ensured. The proposed controller is implemented within an existing UAV autopilot framework, where outer-loop guidance and speed control modules provide reference commands to the RASMC for attitude stabilization. Simulations demonstrate that, despite significant damage, all closed-loop states remain stable with bounded tracking errors.

Johannes Autenrieb

Ensuring the safe operation of aerospace systems within their prescribed flight envelope is a fundamental requirement for modern flight control systems. Flight envelope protection (FEP) prevents violations of aerodynamic, structural, and performance constraints, mitigating risks such as stall, excessive loads, and loss of control. Conventional FEP approaches, such as reference clipping via saturation functions and model-based command filtering, impose constraints at the reference input level but often fail to account for closed-loop system dynamics, potentially leading to constraint violations during transients. This paper introduces a new approach to flight envelope protection by employing a quadratic-programming-based safety filter using control barrier functions to dynamically enforce flight envelope constraints while preserving control performance. Unlike traditional reference filtering methods, the proposed control barrier function-based safety filter actively ensures forward invariance of the safe flight envelope set while seamlessly integrating with existing control architectures. The framework is implemented in a nonlinear missile flight control system and evaluated in a simulated environment. The results demonstrate its ability to prevent constraint violations while minimizing conservatism, offering a robust alternative to existing flight envelope protection methodologies.

Johannes Autenrieb, Peter A. Fisher, Anuradha Annaswamy

Adaptive control provides closed-loop stability and reference tracking for uncertain dynamical systems through online parameter adaptation. These properties alone, however, do not ensure safety in the sense of forward invariance of state constraints, particularly during transient phases of adaptation. Control barrier function (CBF)-based safety filters have been proposed to address this limitation, but existing approaches often rely on conservative constraint tightening or static safety margins within quadratic program formulations. This paper proposes a reference-based adaptive safety framework for systems with structured parametric uncertainty that explicitly accounts for transient plant-reference mismatch. Safety is enforced at the reference level using a barrier-function-based filter, while adaptive control drives the plant to track the safety-certified reference. By exploiting Lipschitz bounds on the closed-loop error dynamics, a robust CBF condition is derived and reformulated as a convex second-order cone program (SOCP). The resulting approach reduces conservatism while preserving formal guarantees of forward invariance, stability, and tracking.

Johannes Autenrieb, Mark Spiller

This paper presents a decentralized safety filter for collision avoidance in multi-agent aerospace interception scenarios. The approach leverages robust control barrier functions (RCBFs) to guarantee forward invariance of safety sets under bounded inputs and high-relative-degree dynamics. Each effector executes its nominal cooperative guidance command, while a local quadratic program (QP) modifies the input only when necessary. Event-triggered activation based on range and zero-effort miss (ZEM) criteria ensures scalability by restricting active constraints to relevant neighbors. To resolve feasibility issues from simultaneous constraints, a slack-variable relaxation scheme is introduced that prioritizes critical agents in a Pareto-optimal manner. Simulation results in many-on-many interception scenarios demonstrate that the proposed framework maintains collision-free operation with minimal deviation from nominal guidance, providing a computationally efficient and scalable solution for safety-critical multi-agent aerospace systems.