This paper presents a new strategy to detect and diagnose fault of a manipulator based on the expression with a Probabilistic Production Rule (PPR). Production Rule (PR) is widely used in the field of computer science as a tool of formal verification. In this work, first of all, PR is used to represent the mapping between highly quantized input and output signals of the dynamical system. By using PR expression, the fault detection and diagnosis algorithm can be implemented with less computational effort. In addition, we introduce a new system description with Probabilistic PR (PPR) wherein the occurrence probability of PRs is assigned to them to improve the robustness with small computational burden. The probability is derived from the statistic characteristics of the observed input and output signals. Then, the fault detection and diagnosis algorithm is developed based on calculating the log-likelihood of the measured data for the designed PPR. Finally, some experiments on a controlled manipulator are demonstrated to confirm the usefulness of the proposed method.
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