Gianluca Gatto

Second-order sliding-mode control of DC drives

One of the most recent topics in variable-structure systems theory is represented by the second-order sliding-mode control (2-SMC) methodology. This approach guarantees the same robustness and dynamic performance of traditional first-order SMC algorithms, and, at the same time, attenuates the chattering phenomenon, which is the main drawback in the actual implementation of this technique. In the present paper, a recently-proposed 2-SMC algorithm is used to synthesize a robust dc-drive control system which does not require current feedback and demands only rough information about the actual motor parameters. Stability and performance are analyzed, and an experimental comparison with a proportional-integral-based control scheme is reported.

Robust speed and torque estimation in electrical drives by second-order sliding modes

This paper presents the synthesis and practical implementation of a robust digital differentiator that provides the first and second derivative of a sampled smooth signal. The robustness of the proposed digital device, based on second-order sliding-modes (2-SMs), is analyzed with respect to measurement errors. Experimental results on an induction motor (IM) drive show that fast and accurate estimates of speed and torque can be obtained in several operating conditions by double differentiation of the encoder position measurement.

Real-Time Control Strategy of Energy Storage Systems for Renewable Energy Sources Exploitation

An optimal energy storage system (ESS) management procedure devoted to full renewable energy sources (RESs) exploitation is presented in this paper. It consists of an appropriate scheduling procedure and a real-time control strategy, which both aim to increase the RES penetration level as much as possible. In particular, the one-day-ahead scheduling procedure synthesizes the combined RES-ESS energy production profile with the aim of minimizing the RES energy production curtailments by means of ESS energy buffering. The real-time control strategy is developed in order to track the scheduled profile as well as possible by mitigating forecasting errors, thus improving RES reliability. The worth and effectiveness of the proposed management procedure is verified through a wide simulation study, which is carried out by means of the Matlab software package.

Operating Constraints Management of a Surface-Mounted PM Synchronous Machine by Means of an FPGA-Based Model Predictive Control Algorithm

A model predictive control algorithm (MPC) suitable for Surface-Mounted Permanent Magnet Synchronous Machines (SPMs) is presented in this paper. It is based upon an accurate discrete-time model of the drive, accounting for both voltage saturation and current limitation constraints. It aims to properly manage these constraints in order to guarantee a good exploitation of both transient and steady state SPM performances, especially over flux-weakening operation. The effectiveness of the proposed MPC is first validated by a simulation study, in which the sensitivity of the proposed MPC against un-compensated inverter un-idealities and parameter uncertainties is properly highlighted and discussed, as well as the effects of sudden load torque variations. Then, an experimental study is performed on a radial-flux SPM driven by a Field Programmable Gate Arrays (FPGA) control board. The performances achievable by the proposed MPC are compared with those obtained by a conventional PI-based control system in order to highlight the improvements, especially regarding transient and flux-weakening operation.

Discrete-Time Parameter Identification of a Surface-Mounted Permanent Magnet Synchronous Machine

A novel online discrete-time parameter identification algorithm suitable for surface-mounted permanent magnet synchronous machines (SPMs) is presented in this paper. It is developed by means of the model reference adaptive system technique and the Popov Hyperstability Criterion in order to identify SPM discrete-time model parameters. In particular, good accuracy of discrete-time parameters is required by digital control systems, particularly by predictive control algorithms, which present a low robustness against parameter mismatches. Hence, an extensive simulation study is first carried out in the Matlab Simulink environment with the aim of testing the effectiveness and robustness of the proposed identification algorithm against inverter unidealities. Then, the proposed identification procedure is experimentally validated on a predictive controlled radial-flux SPM, driven by a field programmable gate arrays control board.

Vehicle-to-Grid Technology: State-of-the-Art and Future Scenarios

An overview of V2G (vehicle-to-grid) technology is presented in this paper. It aims to highlight the main features, opportunities and requirements of V2G. Thus, after briefly resuming the most popular charging strategies for PEVs (plug-in electric vehicles), the V2G concept is introduced, especially highlighting its potentiality as a revenue opportunity for PEV owners; this is mainly due to the V2G ability to provide ancillary services, such as load leveling, regulation and reserve. Such solutions have been thoroughly investigated in the literature from both the economic and technical points of view and are here reported. In addition, V2G requirements such as mobility needs, charging stations availability and appropriate PEV aggregative architectures are properly taken into account. Finally, future developments and scenarios have also been reported.

Predictive Control of Synchronous Reluctance Motor Drive

A predictive digital control algorithm, suitable for synchronous reluctance motor drives, is presented in the paper. The proposed algorithm, which is a direct digital control one, is implemented in rotor coordinates. It is a recursive algorithm which allows the imposition of the reference values of d and q current components. The digital control system directly synthesizes an output vector which imposes the timing control of the inverter by means of on/off state of the switches, thus avoiding the implementation of the traditional PI controllers and PWM technique. Due to the time required for the execution of the algorithm, the vector control has to be imposed with a delay of one sampling time. This drawback can be overcome by using very fast processors like FPGAs or by introducing the observed quantities instead of the measured ones in the recursive algorithm. Both the delayed control and the latter solution are considered in the paper. A computer simulation study, using the Matlab Simulink tool, is conducted on the drive. The simulation results are compared also with those obtained by simulating the traditional drive. The simulation study and the results comparison show the good performance of the proposed control algorithm.

A multi-phase PM synchronous generator torque control for direct-drive wind turbines

In this paper, a torque control algorithm for direct drive wind turbines using a twelve-phase permanent magnet synchronous electrical machine is proposed. An electrical machine oriented to output four independent 3-phase star subsystems have been introduced in order to improve direct drive wind turbine torque control, power generation and reliability. A specific coordinate transformation for multi-phase electrical machine control that allows the independent and decoupled management of each electric three-phase subsystem has been developed. The synthesis and the simulation results of the proposed control algorithm are presented.

An improved averaged model for boost DC-DC converters

An improved averaged model suitable for boost DC-DC converters is presented in this paper. It is developed on the basis of the averaging technique with the aim of appropriately taking into account the effects of switching phenomena. Thus, two appropriate trapezoidal signals have been introduced in order to model the transient evolutions of voltages and currents of the DC-DC converter devices over both turn-on and turn-off of the switch. This enables the synthesis of an appropriate averaged model of boost DC-DC converters, which can be usefully employed in determining average voltage and current evolutions, as well as steady state average powers. The worth and effectiveness of the proposed modelling approach has been validated through a simulation study, which refers to the case of a traditional boost DC-DC converter.

Modelling and predictive control of a Buck-Boost DC-DC converter

A predictive current control algorithm for the Buck-Boost DC-DC converter is presented in this paper. The continuous time model of the system is properly introduced, then, by imposing a proper PWM modulation pattern, its discrete time model is achieved. This last one is successfully employed in determining the steady state locus of the Buck-Boost converter, both in Continuous Conduction Mode (CCM) and Discontinuous Conduction Mode (DCM). A novel continuous time equivalent circuit of the converter is introduced too, with the aim of determining a ripple free representation of the state variables of the system, both over transient and steady state operation. Then, a predictive current control algorithm, suitable in both CCM and DCM, is developed and properly checked by means of computer simulations. The corresponding results have highlighted the effectiveness of the proposed modelling and of the predictive control algorithm, both in CCM and DCM.