Constructive Safety Control
This paper proposes a constructive approach to safety control of nonlinear cascade systems subject to multiple state constraints. New design ingredients include a unified characterization of safety and stability for systematic designs of safety controllers, and a novel technique of reshaping the feasible sets of quadratically constrained quadratic programming induced from safety control. The proposed method guarantees Lipschitz continuity of virtual control laws, enabling a stepwise constructive design. A refined nonlinear small-gain synthesis is employed to address the nonlinear uncertain interconnections between the resulting subsystems corresponding to different virtual control laws, and to guarantee the achievement of the safety control objective. When the safety constraints are removed, the proposed approach coincides with the standard constructive nonlinear control. The proposed safety-control algorithm is experimentally validated in a testbed involving a vertical takeoff and landing (VTOL) vehicle taking off in narrow spaces.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
ALTSTEER: Selective Safety Steering for Moving Beyond Hard Refusals to Constructive Alternatives
Safety alignment is essential for deploying large language models, requiring systems to prevent harmful compliance while preserving helpfulness on benign requests. Activation steering offers a training-free inference-tim…
Oyster-I: Beyond Refusal -- Constructive Safety Alignment for Responsible Language Models
Large language models (LLMs) typically deploy safety mechanisms to prevent harmful content generation. Most current approaches focus narrowly on risks posed by malicious actors, often framing risks as adversarial events …
Oyster-II: Reinforcement Learning for Constructive Safety Alignment in Large Language Models
Large language models (LLMs) have demonstrated remarkable capabilities across diverse applications, yet ensuring their simultaneous safety, helpfulness, and trustworthiness remains a persistent challenge. Conventional re…
Reinforcement LearningInput-to-State Safe Backstepping: Robust Safety-Critical Control with Unmatched Uncertainties
Guaranteeing safety in the presence of unmatched disturbances -- uncertainties that cannot be directly canceled by the control input -- remains a key challenge in nonlinear control. This paper presents a constructive app…
Constructive Safety-Critical Control: Synthesizing Control Barrier Functions for Partially Feedback Linearizable Systems
Certifying the safety of nonlinear systems, through the lens of set invariance and control barrier functions (CBFs), offers a powerful method for controller synthesis, provided a CBF can be constructed. This paper draws …