Modulated predictive control for indirect matrix converter

Finite State Model Predictive Control (MPC) has been recently applied to several converter topologies as it can provide many advantages over other MPC techniques. The advantages of MPC include fast dynamics, multi-target control capability and relatively easy implementation on digital control platforms. However, its inherent variable switching frequency and lower steady state waveform quality, with respect to standard control which includes an appropriate modulation technique, represent a limitation to its applicability. Modulated Model Predictive Control (M2PC) combines all the advantages of MPC with the fixed switching frequency characteristic of PWM algorithms. The work presented in this paper focuses on the Indirect Matrix Converter (IMC), where the tight coupling between rectifier stage and inverter stage has to be taken into account in the M2PC design. This paper proposes an M2PC solution, suitable for IMC, with a switching pattern which emulates the desired waveform quality features of Space Vector Modulation (SVM) for matrix converters. The switching sequences of the rectifier stage and inverter stage are rearranged in order to always achieve zero-current switching on the rectifier stage, thus simplifying the current commutation strategy

A Low-Complexity Optimal Switching Time-Modulated Model-Predictive Control for PMSM With Three-Level NPC Converter

Conventional finite control set model-predictive control (FCS-MPC) presents a high computational burden, especially in three-level neutral-point-clamped (NPC) converters. This article proposes a low-complexity optimal switching time-modulated model-predictive control (OST-M2PC) method for a three-level NPC converter. In the proposed OST-M2PC method, the optimal switching time is calculated using a cost function. Compared with the conventional FCS-MPC, the proposed OST-M2PC method has a fixed switching frequency as well as better power quality. The proposed OST-M2PC can operate at a 20-kHz sampling frequency, reducing the computational burden of the processor. Simulation and experimental results validate the operation of the proposed method

More electric aircraft starter-generator system with utilization of hybrid modulated model predictive control

The current trend for future aircraft is the adoption of the More Electric Aircraft (MEA) concept. The electrical based starter-generator (S/G) system is one of the core ideas from the MEA concept. The PI based control scheme has been investigated in various papers for the permanent magnet based S/G system. Different control schemes are to be considered to improve the control performance of the S/G system. A type of non-linear control called Model Predictive Control (MPC) is considered for its capability to accomplish fast dynamic control performance. The Modulated Model Predictive Control (variant of MPC with an intrinsic modulator) was presented that showed considerably better control performance than the standard MPC. A control scheme is presented in this paper that utilises PI controllers for the outer loop and Modulated Model Predictive Control for the inner loop that covers operation for both starter and generator modes. Simulation analyses are carried out to compare between the proposed control and a full cascaded PI control scheme. The proposed control is also subjected to parameter variation tests for performance evaluation

Modulated model predictive control for a 7-level cascaded h-bridge back-to-back converter

Multilevel Converters are known to have many advantages for electricity network applications. In particular Cascaded H-Bridge Converters are attractive because of their inherent modularity and scalability. Predictive control for power converters is advantageous as a result of its applicability to discrete system and fast response. In this paper a novel control technique, named Modulated Model Predictive Control, is introduced with the aim to increase the performance of Model Predictive Control. The proposed controller address a modulation scheme as part of the minimization process. The proposed control technique is described in detail, validated through simulation and experimental testing and compared with Dead-Beat and traditional Model Predictive Control. The results show the increased performance of the Modulated Model Predictive Control with respect to the classic Finite Control Set Model Predictive Control, in terms ofcurrent waveform THD. Moreover the proposed controller allows a multi-objective control, with respect to Dead-Beat Control that does not present this capability

Permanent magnet machine based starter-generator system with modulated model predictive control

The paper describes a hybrid control scheme for a permanent magnet machine based starter-generator (S/G) system. There has been increased usage of electric drive systems in the transportation sector for increased efficiency and reduced emissions. One of the advantages of utilising suitable electric drives is the capability to operate as a starter or generator. The control design of such a system should be considered due to the operating requirements and fast load changes. Different control approaches should therefore be considered in order to achieve these goals, which are a current trend in the transportation sector. Model Predictive Control (MPC) is considered due to its very fast dynamic performance. In particular, Modulated Model Predictive Control (M²PC) was recently introduced and showed significantly better performance than the standard MPC. The control scheme used in this paper utilises M²PC for the current inner loop and PI controllers for the outer loop. The use of M²PC allows very fast transient current response for the S/G system. The proposed overall control benefits from reduced current ripple when compared with a full cascaded PI control scheme. Simulation analyses and experimental results show the capability and performance of the designed controller across both starter and generator modes

Multi-objective modulated Model Predictive Control for a multilevel solid state transformer

Finite Control Set Model Predictive Control (FCS-MPC) offers many advantages over more traditional control techniques, such as the ability to avoid cascaded control loops, easy inclusion of constraint and fast transient response of the control system. This control scheme has been recently applied to several power conversion systems, such as two, three or more level converters, Matrix converters, etc. Unfortunately, because of the lack of presence of a modulation strategy, this approach produces spread spectrum harmonics which are difficult to filter effectively. This may results in a degraded power quality when compared to more traditional control schemes. Furthermore, high switching frequencies may be needed, considering the limited number of switching states in the converter. This paper presents a novel multi-objective Modulated predictive control strategy, which preserves the desired characteristics of FCS-MPC but produces superior waveform quality. The proposed method is validated by experimental tests on a seven level Cascaded H-Bridge Back-To-Back converter and compared to a classic MPC scheme

A modulated model predictive control scheme for the brushless doubly-fed induction machine

This paper proposes a modulated model predictive control (MMPC) algorithm for a brushless double-fed induction machine. The Brushless Doubly-Fed Induction Machine has some important advantages over alternative solutions for brushless machine applications. The proposed modulation technique achieves a fixed switching frequency, which gives good system performance. The paper examines the design and implementation of the modulation technique and simulation results verify the operation of the proposed modulation technique

Modulated model predictive current control of an indirect matrix converter with active damping

A modulated model predictive control (M²PC) scheme for an indirect matrix converter is proposed in this paper, including an active damping method to mitigate the input filter resonance. The control strategy allows the instantaneous power control and the output current control at the same time, operating at a fixed frequency. An optimal switching pattern is used to emulate the desired waveform quality features of space vector modulation and achieve zero-current switching operations. The active damping technique emulates a virtual resistor which damps the filter resonance. Simulation results present a good tracking to the output-current references, unity input displacement power factor, the low input-current distortions and a reduced common-mode voltage (CMV)

Predictive control for active split DC-bus 4-leg inverters

This paper proposes a Predictive Control, formally Dead-Beat (DBC), for a four-leg inverter having an Active Split DC-bus on the fourth leg and LC filters on phase-to-neutral outputs. Such a configuration permits to reduce the voltage ripple on the neutral point connected to inverter grounding. As only few control techniques have been investigated for Active Split DC-bus, the paper proposes to investigate the performance of DBC, which has been widely used for other power electronics applications. The main advantage of DBC over the classical PI or Resonant controller is that no tuning is required for control loop, while obtaining very fast transient response as well it can handle general constrained nonlinear systems with multiple inputs and outputs in a unified and clear manner. These features are highly valuable in power electronic converters used to supply the electrical utility loads in micro-grids. However, one of the main drawback of the DBC is the limited capabilities on harmonics compensations required when supplying unbalanced and non-linear loads. The paper presents continuous-time and discrete-time models of DBC applied to a four-leg VSI with Active Split DC-bus, highlighting the performance through simulation results as well as experimental tests