Abstract
This paper proposes a fast and accurate solver for implicit Continuous Set Model Predictive Control for the current control loop of synchronous motor drives with input constraints, allowing for reaching the maximum voltage feasible set. The related control problem requires an iterative solver to find the optimal solution. The real-time certification of the algorithm is of paramount importance to move the technology toward industrial-scale applications. A relevant feature of the proposed solver is that the total number of operations can be computed in the worst-case scenario. Thus, the maximum computational time is known a priori. The solver is deeply illustrated, showing its feasibility for real-time applications in the microseconds range by means of experimental tests. The proposed method outperforms general-purpose algorithms in terms of computation time, while keeping the same accuracy.
Highlights
Model Predictive Control (MPC) is an advanced optimization-based control strategy that is gaining more and more popularity in the power electronics framework [1], [2]
In this work, a fast and effective method for solving in real-time the quadratic programming problem related to the MPC has been proposed
The solver was designed for the implicit current model predictive control of a synchronous motor drive
Summary
Model Predictive Control (MPC) is an advanced optimization-based control strategy that is gaining more and more popularity in the power electronics framework [1], [2]. Increasing availability of computational power [3] and enhancement of optimization strategies have made advanced control schemes, such as MPC and Digital Twins [4], [5], suitable for fast dynamic systems, as electric drives In this framework, MPC has been mostly implemented in its Finite Set (FS) form where, in each control interval, the controller applies one of the basic inverter voltage vector [6]–[10]. A second type of MPC refers to the Continuous Set (CS) technique, which requires the modulator for synthesizing the optimal voltage reference It provides a fixed switching frequency of the converter and it works efficiently with longer sampling intervals [11] with a significant increase in computational load.
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