Arizona State University

Imane Lamrani

Ayan Banerjee

Sandeep Narendra Gupta

Sandeep K S Gupta

Methods and systems for utilizing co-simulation of a physical model and a self-adaptive predictive controller using hybrid automata are described. For example, there is disclosed a self-adaptive predictive control system to generate an initial patient model with initial patient model settings (k, k, . . . , k) and execute a program that takes as input, the initial patient model settings as configuration parameters that specify at least a plurality of initial states. Such a system further receives new patient inputs and generates hybrid automata as a variation of the initial states by applying the new patient inputs to the initial patient model. The system further derives reachable states from the hybrid automata and outputs all reachable states computed. The system further detects changes and responsively generates a new patient predictive model with new parameter settings (k', k&#x2032;, . . . , k&#x2032;), iteratively repeating until a termination criterion is satisfied. Other related embodiments are disclosed.

Systems, methods, and apparatuses for utilizing co-simulation of a physical model and a self-adaptive predictive controller using hybrid automata

Systems and methods for mining hybrid automata from input-output traces of cyber-physical systems are disclosed herein.

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Tempe, AZ, United States of America

Imane Lamrani