A. Perfetto

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.

Vectorial torque control: a novel approach to torque and flux control of induction motor drives

A general approach to torque and flux control of an induction motor fed by a voltage-source inverter is described in this paper. It is independent of whether rotor or stator flux is controlled. Based on this, an algorithm can be set up which allows the generation of the inverter switching patterns as a function of the reference values, both of the electromagnetic torque and of the controlled flux. Experimental comparisons with traditional direct torque control and field-oriented control techniques confirm the possibility of achieving very high dynamic performance with the proposed strategy.

Direct torque and flux control of induction motor drives

A general approach to direct torque and flux control of an induction motor fed by a VSI is presented in the paper. The inverter switching patterns are generated as a function of the reference values of both the electromagnetic torque and of the controlled flux. In particular, the proposed control algorithm is independent of which kind of flux is controlled-rotor or stator. The results obtained by means of a real-time simulation show that the proposed control strategy allows very fast and accurate response of the drive.

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 novel approach to speed and parameters estimation in induction motor drives

With reference to a speed-controlled induction motor, an algorithm which allows the online estimation either of the speed and one other motor parameter or, alternatively, of two motor parameters, is described in the paper. Simulation results fully confirm the validity of the proposed algorithm.

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.

Three-Phase Operation of Brushless DC Motor Drive Controlled by a Predictive Algorithm

A novel predictive control algorithm for the current control of brushless DC drives is presented in the paper. It allows to exploit the three phase of the motor simultaneously. The pulse width of the chain voltages are determined by means of the proposed algorithm, under the constraints of minimum Joule losses and torque ripple free operation. At maximum speed, high torque ripple appears but it is lower than that of six step operation of the traditionally controlled drive. Also the mean torque is higher than that of six step operation. Simulation results highlight the better dynamic and steady state performance of the drive controlled by the propose algorithm, with respect to the one of the traditional control

Sensorless brushless DC drive controlled by predictive algorithm

A digital speed and high resolution position identification algorithm, suitable for brushless DC (BLDC) drives, is presented in the paper. The proposed digital algorithm is synthesized by using the Popov Hyperstability Theory, by means of the current signal samples. The “a priori” and “a posteriori” current errors are introduced in the adaptation mechanism to force the estimated samples of speed and position to converge to their respective actual values, as fast as possible. A Matlab-Simulink simulation study, referred to transient and steady state operation, is conducted on a BLDC drive controlled by a predictive algorithm. The results highlight the drive performance in transient and both at low and high speed operation.

A direct torque control algorithm imposing the mechanical response of speed controlled induction motor drives

A general approach to the direct torque control of an induction motor fed by a VSI is presented in the paper, showing how the approach can be used in order to exploit both the transient and the steady-state performances of the drive. In particular, a speed control algorithm is proposed which allows the drive to track an imposed velocity-time trajectory, by making the mechanical response practically independent of load torque variations.

Performance comparison between two-phase-on and three-phase-on operation of Brushless DC drives

A comparison between two-phase-on (2PO) and three-phase-on operation (3PO) for Three-phase Brushless DC machines (BLDCs) is presented in this paper. It aims to highlight the different BLDC exploitation achievable by means of 3PO compared to that obtainable by 2PO. For this purpose, two different control strategies are considered, i.e. a traditional 2PO-based and a 3PO-based, whose main details are briefly analyzed and discussed. Subsequently, they are compared to each other referring to the case of a BLDC. The comparison reveals improved BLDC performances achievable by means of 3PO in terms of averaged torque, torque ripple and Joule losses reduction, especially at high-speed operation.