Language identification of controlled systems: modeling, control, and anomaly detection
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Diagnosis of quantized systems based on a timed discrete-eventmodel
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
From controlled dynamical systems to context-dependent grammars: A connectionist approach
Engineering Applications of Artificial Intelligence
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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.