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In this paper, we present a hybrid sensorless observer for Permanent Magnet Synchronous Machines, with no a priori knowledge of the mechanical dynamics and without the typical assumption of constant or slowly-varying speed. Instead, we impose the rotor speed to have a constant (unknown) sign and a non-zero magnitude at all times. For the design of the proposed scheme, we adopt meaningful Lie group formalism to describe the rotor position as an element of the unit circle. This choice, however, leads to a non-contractible state space, and therefore it introduces topological constraints that complicate the achievement of global/semi-global and robust results. In this respect, we show that the proposed observer, which augments a recent continuous-time solution, achieves semi-global practical asymptotic stability by periodically resetting the estimates. As highlighted in the simulation results, the novel hybrid strategy leads to improved transient performance, notably without any modification of the gains employed in the continuous-time version. These features motivate to augment the observer with a discrete-time identifier, leading to significantly faster rotor flux reconstruction.

In this work, we present a novel repetitive control (RC) strategy to achieve accurate position tracking of a 1-DOF Lagrangian system. Such controller is able to cope with model uncertainties and unknown transmission delays in the control architecture. The classic repetitive structure is augmented with an observer of the residual disturbance, to be compensated by means of the RC action. The repetitive unit is updated at hybrid instants, so that the disturbance observer is close to its steady-state before a new repetitive correction is applied. In addition, communication delay is also estimated by the proposed control structure. This way, practical asymptotic stability of the overall system can be achieved with a simple proportional correction of the RC, also under perturbations of the steady-state estimate due to model uncertainties. In light of the aforementioned properties, the proposed RC-based controller is shown to be an easy-to-tune, robust solution capable of improving the tracking performance for the given case of study.

Condition monitoring of electric motor driven mechanisms is of great importance in industrial machines. The knowledge of the actual health state of such components permits to address maintenance policies which results in better exploitation of their actual operational life span and consequently in maintenance cost reduction. In this paper, we exploit the way electric cams are implemented on the vast majority of PLC/Motion controllers to develop a suitable condition monitoring procedure. This technique relies on computing the higher-order differences of the current absorbed by slave motors to get signals that do not depend on a priori knowledge of the cam trajectory and of the mechanism nominal model. Subsequently, we will use these data in the Model-of-Signals framework, to gather information on the mechanism’s health condition, which in turn can be used to perform predictive maintenance policies. The differenced signal is modelled as an ARMA process and the model capabilities in condition monitoring are then shown in simulation and experimental application. Besides, this framework allows exploiting the edge-computing capabilities of the machinery controllers by implementing recursive estimation algorithms.

In this work, we present a mixed sensorless strategy for Permanent Magnet Synchronous Machines, combining a torque/current controller and an observer for position, speed, flux, and stator resistance. The proposed co-design is motivated by the need for an appropriate signal injection technique to guarantee full state observability. Neither the typical constant or slowly-varying speed assumptions, nor a priori mechanical model information are required. Instead, the rotor speed is modeled as an unknown input disturbance with constant (unknown) sign and uniformly non-zero magnitude. With the proposed architecture, we show that the torque tracking and signal injection tasks can be achieved and asymptotically decoupled. Because of these features, we refer to this strategy as a sensorless controller-observer with no mechanical model. Employing a gradient descent resistance/back-EMF estimation, combined with the unit circle formalism to describe the rotor position, we prove regional practical asymptotic stability of the overall scheme. In particular, the domain of attraction can be arbitrarily large, without including a lower-dimensional manifold. The effectiveness of this design is further validated with numerical simulations, related to a challenging application of UAV propellers control.

This work presents the research findings of the Multithermal ERC-Advanced project, in terms of multi-scale thermal control of complex large scale computing platforms such as High Performance Computing Systems, and datacenters. In this respect, the challenges and opportunities concerning thermal control of computing systems are discussed, along with the proposed innovative solutions. Control and management problem is divided at different hierarchical, and scale, levels (compute node and system). Then, given the control knobs and sensors available at each level, advanced control and system identification techniques are proposed, to achieve a holistic thermal management of complex computing platforms, with benefits for thermal stability guarantees and energy consumption optimization. Such features are of utmost importance for advancements in next generation large scale computing solutions.

A novel control solution for Doubly-Fed Induction Machines is proposed to enable new applications of such kind of machines. This strategy guarantees a fully decoupled motion control and contactless power transfer between stator and rotor, by using controlled inverters on both stator and rotor side. For large and complex rotary apparatus with relevant electric loads and actuators placed on-board the mobile part, the proposed solution allows to exploit direct-drive versions of Doubly-Fed Induction Machines for both moving and feeding independently the rotating part, where the rotor-side converter has to be hosted. Power transfer is attained through two different working principles in order to achieve decoupling from the torque references and to suitably deal with voltage saturations on power converters. Global asymptotic stability proof is provided for this control strategy. Simulation results are reported in order to validate the promising theoretical developments.

In this work, a novel sensorless observer is proposed for Permanent Magnet Synchronous Machines, formally dealing with stator voltage actuation non-idealities. Rotor speed, position and stator fluxes, as well as the unknown parameters of the voltage perturbations are reconstructed considering a fixed reference frame for both the machine and the voltage actuator non-linear effects. Stator currents and commands for the voltage actuator are assumed to be the only known signals. The estimation scheme is proven to be Uniformly Globally Asymptotically Stable by means of rigorous results from adaptive systems theory. The effectiveness of this solution is validated by realistic simulation tests, including a detailed model of the power converter. Discretization of the presented solution is addressed accurately. A comparison is provided to show the advantages of the proposed observer against a solution which does not adopt any mechanism to compensate for the mismatch between ideal and actuated stator voltages.

In order to improve reliability of wind turbines, it is important to detect and isolate faults as fast as possible, and handle them in an optimal way. An important component in modern wind turbines is the converter, which for a wind turbine control point–of–view normally provides the torque acting on the wind turbine generator, as well as measurement of this torque. In this work, a diagnosis strategy based on fuzzy prototypes is presented, in order to detect these faults in the converter, and isolate them either to be an actuator or a sensor fault. The fuzzy system is used since the model under investigation is nonlinear, whilst the wind speed measurement is highly noisy, due to the turbulence around the rotor plane. The fuzzy system consists of a set of piecewise affine Takagi–Sugeno models, which are identified from the noisy measurements acquired from the simulated wind turbine. The fault detection and isolation strategy is thus designed based on these fuzzy models. The wind turbine simulator is finally used to validate the achieved performances of the suggested fault detection and isolation scheme.

This paper describes a modular approach to the dynamic modelling of heat exchangers (condenser and evaporator) in vapor compression cycles. The model of the heat exchangers is obtained by properly connecting a small number of generic modules where a fluid flows, exchanging heat and, possibly, changing state (from liquid to vapor and vice-versa). The dynamic model of the generic element is phase–independent and is valid in every working condition. Unlike other approaches described in the literature, the mass exchange rate from vapor to liquid is explicitly computed in order to comply with state-trajectories constraints which are defined according to the current phase condition and highlighting when a phase-transition is possible. This leads to an effective representation of constrained evolutions and smooth jumps among different phases. The proposed dynamic elements are characterized by dynamic-orientation of some interface variables; this crucial feature for correct modelling is treated carefully in composing them and a suitable standardized interface is defined.

Maximum Power Point Tracking (MPPT) algorithms are receiving particular attention to maximize the wind energy captured by medium power wind turbines (a few hundreds of kW), whose aerodynamics curves are usually not known accurately and where wind-speed sensors are missing or not reliable. Wind turbine speed control, over a wide operating range, is usually assumed to give a reliable basis for most common MPPT algorithms. In this paper a novel simple, but effective, speed controller is presented. Speed control knobs, i.e. blade pitch angles and generator torque, are suitably combined in order to take into account generator torque and power limits without using hybrid controllers, which could lead to bumps and limit cycles under variable wind and uncertain aerodynamics characteristics. In defining torque and power limits at generator side, thermal dynamics are taken into account leading to time-varying bounds adopted in the proposed control solution. This allows a better exploitation of the generator capabilities, but still preventing from shut down related to thermal problems. A full stability analysis under unknown wind speed and uncertain aerodynamics curves is carried out showing how to tune the proposed controller, with a simple PI structure, for wide stability domain. A standard MPPT algorithm is mounted on top of the proposed solution, highlighting the constrains in shaping the speed reference trajectory to avoid motor behavior of the electric generator. Finally, simulations are reported to show the effectiveness of the proposed solution.

This paper is mainly focused on the stabilization of the DC-link voltage dynamics of three-phases, three-wires Shunt Active Filters (SAF) based on AC/DC boost topology. This relevant issue is usually neglected in SAF control development. The robust solution presented by the authors in (L. Marconi, 2003) is used as a starting point to develop the internal voltage stabilization controller. A non-trivial definition of the stabilization objective is proposed and the two timescale behavior of the SAF is exploited to apply the Averaging technique and Input to State Stability arguments in the control design.

A hydraulic actuated clutch control system for commercial cars is analyzed. A physical model of the system is firstly derived: this model is then used both to define a closed loop controller, through derivation of a simplified model, and to asses the dependencies of the closed loop system performances on some plant and controller key parameters. Trade-off curves are derived that link the required performances, namely response speed and tracking error, to this key parameters. It is shown how this curves can be used to fix the specifications for both plant configuration and electronic control unit in an optimized way, in order to achieve guaranteed performances at minimum system cost.