Autonomous systems (AS) powered by AI components are increasingly integrated into the fabric of our daily lives and society, raising concerns about their ethical and social impact. To be considered trustworthy, AS must adhere to ethical principles and values. This has led to significant research on the identification and incorporation of ethical requirements in system design. A recent development is the introduction of SLEEC rules, which offer a comprehensive framework for representing ethical and normative considerations. This paper, based on a logical representation of SLEEC rules, presents a methodology to embed them into AS using fuzzy logic and test-score semantics. The use of fuzzy logic is motivated by the view of ethics as a domain of possibilities, which offers a way to deal with (soft) ethical dilemmas that AI systems may encounter. The approach is illustrated through a case study.