最大制御不変MPC：終端CBF制約による安全制御の実現可能性向上と保守性低減
Maximal Controlled Invariant-MPC: Enhancing Feasibility and Reducing Conservatism through Terminal CBF Constraint in Safety-Critical Control
制御バリア関数を終端制約として用いたMPCを提案し、予測ホライズン増加に伴う実現可能性と到達可能集合の改善を証明、非ホロノミック系のシミュレーションで有効性を検証した。
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著者: Tanmay Dokania, Yashwanth Kumar Nakka
分類: eess.SY, cs.RO, cs.SY, math.OC
原文アブストラクト
Optimal control for safety-critical systems is often dependent on the conservativeness of constraints. Control Barrier Functions (CBFs) serve as a medium to represent such constraints, but constructing a minimally conservative CBF is a computationally intractable problem. Therefore, approaches that can guarantee safety while reducing conservatism will help improve the optimality of the system under consideration. Here, we present a Model Predictive Control (MPC) formulation using CBF as a terminal constraint, which is proven to improve feasibility and reachable sets with increasing prediction horizon. The constructive nature of the proofs allows for warm-starting the nonlinear optimization problem, thereby reducing the computational time substantially. Simulations are set up for a simple nonholonomic system to numerically validate the results, and it is observed that the number of infeasible points decreased by a factor of 1.7 to 2.7. The increase in reachable state space was demonstrated by the ability of the system to track trajectories that are entirely inside the unsafe region of the control barrier function.
