📝 SummarXiv

Abstract

This paper proposes a novel framework for safety-critical optimal trajectory tracking in nonlinear systems based on the state-dependent Riccati equation (SDRE) methodology. By embedding barrier states into the system dynamics, the proposed strategy simultaneously ensures safety and tracking requirements, even in scenarios where these objectives may be inherently conflicting. A discounted pseudo-quadratic cost function is formulated to achieve a suboptimal trade-off between tracking accuracy, control effort, and safety objective. We present two distinct controller designs: one utilizing a single barrier state to enforce overall safety constraints, and another employing multiple barrier states to individually tuning the system's conservatism with respect to each safety constraint, providing enhanced flexibility in tuning the system's conservatism toward individual constraints. We establish sufficient conditions to ensure the solvability of the associated Riccati equations. The proposed safe controller is well-suited for real-time implementation in practical systems, given its reasonable computational requirements and compatibility with widely available embedded microprocessors. This is supported by simulation studies involving a mechanical system and a mobile robot collision avoidance scenario, where the safe SDRE controller consistently maintained safety while achieving trajectory tracking objectives in challenging conditions. Additionally, experimental results on a cable-driven parallel robot further demonstrate the practical applicability and effectiveness of the proposed method in real-world control tasks.