Sufficient conditions for feasibility of optimal control problems using Control Barrier Functions

It has been shown that satisfying state and control constraints while optimizing quadratic costs subject to desired (sets of) convergence for affine systems can be reduced a sequence of programs (QPs) by using Control Barrier Functions (CBFs) Lyapunov (CLFs). One the main challenges in this approach is ensuring feasibility these QPs, especially under tight bounds safety high relative degree. The contribution paper provide sufficient conditions guaranteed feasibility. are captured single constraint enforced CBF, which added QPs such their always guaranteed. additional designed compatible with existing constraints, therefore, it cannot make feasible set infeasible — only increase overall We illustrate effectiveness proposed on an adaptive cruise problem.