Embedded Model Control urges disturbance modelling and rejection

Robust control design is devoted to guarantee closed-loop stability of a model-based control law in presence of parametric uncertainties. The control law is usually a static feedback law which is derived from a model. Under this view stability can only be guarantee by introducing some ignorance coefficients and restricting the feedback control effort with respect to the model-based design. Embedded Model Control shows that under certain conditions, the model-based control law must and can be kept intact under uncertainty, if the controllable dynamics is complemented by a suitable disturbance dynamics capable of real-time encoding the different uncertainties affecting the `embedded model´, i.e. the model which is both the design source and the core of the control unit. To be real-time updated the disturbance state is driven by an unpredictable input vector, called noise, which can be only estimated from the model error. The uncertainty-based design concerns the noise estimator, as the model error conveys into the embedded model uncertainty components which are command-dependent and thus prone to destabilize the plant. Separation of the components in the low and high frequency domain by the noise estimator itself allows to recover and guarantee stability. A simple example will help to understand the key assets of the methodology.