Multiple Model Identification in Systems with Variable Dynamics

In this paper we present an example of an application to control a nonlinear system using the multiple models approach. The system has variable dynamics that can be externally manipulated but cannot be directly measured. For each dynamic we identify a local model corresponding to a specific operating point, with the ARMAX structure. We design a controller that is formed by the patching of local controllers, each one designed for a corresponding local model. A supervisor is used to detect which model is similar to the behavior of the current system and chooses the corresponding controller. An original supervisor algorithm that tackles the presence of unknown offsets is purposed and demonstrated experimentally. We also implement adaptive control to this system, which enables the update of the models and controllers when the currently observed behavior does not match any of the known models.

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