A power system consists of a large number of components. The outage of a single component may lead to cascading failures and result in severe consequences. Among the other things, the outage of an individual component strongly couples with its health condition. Hence, evaluation of system cascading failure risk based on the health condition of components is crucial for power system reliable operation. This paper proposes a novel optimal control based cascading failure risk assessment method, which can obtain the last stage of cascading failures without simulating the whole dynamic process, and expresses the system damage level using intuitionistic indexes. A case study is given to demonstrate how the proposed method is used to assess power system risk level based on the health condition of components.