Adaptive techniques for sensorless control of electric machines: with the current large scale spreading of alternatives to the traditional combustion engines, apart from the wide diffusion of generation with complex control of electric machines such as wind turbines, ever more demanding performance and reliability requests are asked to the drives. These issues make sensorless control, i.e. control without position/speed sensors, very attractive for robustness, cost and space reasons. In this context, the research activity seeks for efficient solutions capable of satisfying rigorous stability, robustness and constraint satisfaction: this is meant to be performed with adaptive system theory.
Non-linear constrained control: a theme which receives significant attention in the field of automatic controls, because of the diffusion of such issue in practical applications, is to account optimally for the constraints that affect state and control variables in the algorithm design. In this context, and especially for linear systems, a particularly popular technique is the family of Model Predictive Control strategies, among which there are also specialized types, such as Reference Governors, that entirely focus on constraint satisfaction while working as supervisors on low level controllers that neglect the operative limitations. The research activity, in this scenario, is oriented to Reference Governors for non-linear systems, with particular interest in explicit solutions: these, in fact, provide the advantage of computational efficiency, while approximately reaching the optimality of implicit optimization programs.
