Embedded Model Control Research Articles

Embedded Model Control: Outline of the theory

Embedded Model Control allows one to proceed systematically from fine plant dynamics and control requirements to the Embedded Model (EM), which is the core of control design and algorithms. The model defines three interconnected parts: the controllable dynamics, the disturbance class to be rejected and the neglected dynamics. Controllable and disturbance dynamics must be observable from the plant measurements. Control algorithms are designed around the first two parts, while stability and performance are constrained by the third one. The key design issue is discriminating between driving noise and neglected dynamics, to guarantee updating disturbance in view of its rejection. To this end, concept and equations of the ‘error loop’ are outlined: it maps error sources to performance and shows how to discriminate destabilizing sources, while meeting performance requirements. An introductory example with analytical and simulated results illustrates the design steps.

Embedded model control: Application to web winding

Embedded Model Control (EMC) methodology is applied to web-winding control problems. These require time-varying Embedded Model and adaptive control law, because of a variable winder radius; disturbance estimation and rejection, because of friction and variable web speed and acceleration; sensorless reel radius estimation; and robust stability and performance in the presence of web and gear vibrations. The goal is to solve these key issues in the framework of EMC, which amounts to (i) designing a time-varying Control Law capable of disturbance rejection, (ii) designing Noise Estimators capable of keeping live and accurate disturbance and radius estimates, and (iii) tuning their eigenvalues to guarantee stability and performance. Tuning takes advantage of an ‘error loop’ formulation, which explicitly relates neglected dynamics to eigenvalues, stability and performance. Simulated runs from a fine winder model are compared to published results.

Automation and Control of Fabry–Pérot Interferometers

Fabry-Peacuterot interferometry (FPI), which was originally invented for spectroscopy, is now evolving as a basic technology for ultrafine dimensional stabilization and measurement. To this end, the light path length of an optical cavity and the wavelength of a laser source injected into the cavity have to be tuned to each other through a set of frequency and/or displacement actuators driven by a sharp and narrow signal-encoding total-cavity detuning. Digital control is essential in facilitating and automating FPI use in view of space applications and routine instrumentation. This paper shows how embedded model control (EMC) technology, which was developed by one of the authors, allows to systematically proceed from fine dynamics and requirements to the EM, which is the core of control design and algorithms. In this framework, all critical control issues have a coordinated solution: disturbance estimation and rejection, command constraints and multiplicity, hybrid dynamics, constraints due to unmodeled dynamics, and performance analysis. Several experimental results are illustrated and discussed in the light of the methodology