Method for monitoring a nonlinear dynamic process and a computing system

A computing system, comprising:

• at least one processor;
• a non-transitory computer-readable storage medium coupled to the at least one processor and storing programming instructions for execution by the at least one processor, the programming instructions instruct the at least one processor to:
• train a model based on sample data, wherein the model comprises:
• a first layer, wherein the first layer is configured to linearize the sample data using one or more dimension lifting techniques;
• a second layer, wherein the second layer is configured to extract reduced-dimension dynamic latent variables (DLVs) from the linearized sample data using a reduced-dimension model;
• and
• a third layer, wherein the third layer is configured to parameterize the extracted reduced-dimension DLVs using a latent state space model;
• and
• input data from the nonlinear dynamic process into the trained model for monitoring the nonlinear dynamic process.