Ensuring the safe operation of nuclear power plants remains one of the most important tasks. An important role in ensuring the safety of nuclear power plants is played by instrumentation and control systems (ICS). Extremely high demands are made on such systems, first of all, on their reliability and functional safety. The object of research and analysis in this work is the Nuclear Island I&C Instrumentation System and Reactor Protection System, which are developed based on programmable RadICS Platform with self-diagnostic. The failure trees of such platforms and ICS based on them were developed. In the next stage, several Markov models of redundant ICS are developed. The article aims to develop and analyze the results of research on Markov models for reliability and safety assessment of ICS based on self-checking programmable platforms. The models take into account errors of checking and diagnostic tools, namely errors associated with identifying failures and failures of the corresponding components of the hardware and software/FPGA and channels of redundant structures. Models have been developed for various options of redundant structures and taking into account the diversity principle for ISC structure and failure rate caused by design defects. Multiple-fragment Markov Models of ICS were also investigated. The scientific novelty lies in the fact that the proposed models take into account an expanded set of parameters of self-diagnosing programmable platforms, ICS, the processes of their use and maintenance. Recommendations on the selection of parameters and structural ICS are formulated.